Is it worth learning to code right now?
Asked of each model 6 times per run. Every answer is kept in full; the position under each model is the one most of its samples took. The lines quoted under each sample are the model's own words, picked out by our grader as the evidence for the label it gave — the selection is ours, the wording is not.
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28 Aug 2026
yes-worth-it Anthropic 6/6 OpenAI 6/6 Google 6/6 Grok 6/6all agreeAnthropic claude-sonnet-5 cited sources in 6 of 6, 116 in totalSample 1 of 6The model's answer, recorded unedited
Short answer: Yes, it's still worth learning to code — but the reasons and the way you learn have shifted because of AI.
Why it's still worth it
The consensus (with nuance) is "yes." Multiple sources converge on this: "My answer is an emphatic YES!" is a common refrain across educators, and similarly other writers conclude the response to whether it's still worth coding "is a definite, absolute yes."
AI makes understanding code more valuable, not less. If you can't read code, you can't judge whether an AI got it right. As one source puts it, learning fundamentals means you'll be able to spot whether LLM-generated code is correct, and if the code executes but you run into a problem, you'll know how to fix it. Without that skill, you'll be less prized by employers than those who only know how to use LLMs.
AI amplifies knowledge, it doesn't replace the need for it. As one developer-educator argues, AI hasn't made programming obsolete—it's made it accessible to more people, but you still need to learn the fundamentals, because AI amplifies what you know rather than replacing what you don't.
The job itself is changing, not disappearing. Developers are focusing more on logic, problem-solving, and system architecture, while debugging and testing are increasingly automated. Similarly, AI writes code, but humans still build software — the key shift is that coding is no longer about typing code, it's about thinking in systems and logic.
Skepticism about "AI replacing coders" has been around a while without materializing fully. One source notes AI is far off from being able to actually replace humans — people have been saying programmers were going to be replaced for 3+ years now and it's still not happening.
The honest complications
It's not all rosy, and you should know the mixed signals:
- Some hard data looks discouraging for the narrowest "programmer" job title. One writer who works heavily with AI coding tools found that the Bureau of Labor Statistics shows that "computer programmer" roles dropped about 27% in just two years, with another 6% decline projected through 2034. However, "software developer" is a broader, growing category — the BLS projects that jobs for software developers will grow 15% between 2024 and 2034, about five times the average across all occupations, and names AI as one of the drivers.
- Not everyone agrees. Notably, NVIDIA's CEO stated at the World Government Summit that coding is no longer a viable career for the young generation given the rapid growth of AI, recommending they lean toward biology, education, manufacturing, or farming instead. This is a genuinely contrarian, high-profile take you should weigh.
- Trust in AI-generated code is still low even among heavy users. In Stack Overflow's 2025 survey of nearly 50,000 developers, 84% use or plan to use AI tools, but just 3.1% said they highly trust the accuracy of the results — meaning human oversight is still essential.
- The "how" of learning matters more than ever. Rather than skipping fundamentals, one experienced engineer advises: you need to learn to code before you can learn to use AI to help you code — if you lean on AI too early, you skip the struggle and the learning, and you might get working code, but you won't understand why it works.
Bottom line
If your goal is to become a professional software engineer, architect, or build serious technical products, learning to code (fundamentals + how to work with AI tools) is still a strong bet — arguably it makes you more valuable, since you can supervise, debug, and improve AI-generated output rather than being at its mercy. If your goal is purely a fast career pivot and you don't care about deep technical work, some argue you might get more ROI learning to use AI tools well within a field you already know, rather than a full coding path.
Given how fast this space is moving and the genuine disagreement among experts (including tech CEOs), it's worth treating any single article's take — including this synthesis — as a snapshot, and checking in on it periodically.
17 sources the model cited
- https://medium.com/@naveenkumar_19578/coding-in-2025-is-learning-to-code-still-worth-it-89
- https://medium.com/@maxstoneSL/the-1-000-question-is-it-still-worth-learning-to-code-in-th
- https://www.dataschool.io/ai-vs-coding/
- https://medium.com/data-science-collective/should-you-still-learn-to-code-in-2026-034685e1
- https://www.databilitylabs.com/2025/03/is-it-still-worth-learning-to-code-in.html
- https://dailypythonprojects.substack.com/p/automatic-coding
- https://dev.to/adridev24/its-worth-learning-coding-in-2025-175i
- https://mimo.org/blog/how-to-learn-coding-learn-to-code-for-free
- https://codingwithroby.substack.com/p/should-you-still-learn-to-code-in
- https://www.frontendmentor.io/articles/is-coding-still-worth-learning
- https://zerotomastery.io/blog/should-i-learn-to-code/
- https://www.masaischool.com/blog/is-coding-still-worth-learning-after-ai/
- https://coursiv.io/blog/will-ai-replace-programmers
- https://blog.stackademic.com/should-you-still-learn-to-code-in-2026-c7be28556a60?gi=179fc1
- https://dev.to/syed_suhailbasha_344c046/why-developers-must-learn-ai-in-2025-2dep
- https://tech.yahoo.com/ai/articles/nvidia-ceo-says-future-coding-124534339.html
- https://programmerspace.substack.com/p/most-in-demand-programming-fields
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Short answer: Yes, it's still worth learning to code
- learning to code (fundamentals + how to work with AI tools) is still a strong bet
- AI makes understanding code more valuable, not less.
Sample 2 of 6The model's answer, recorded unedited
Short answer: Yes, but how you learn matters more than ever
Coding is still worth learning — but the goalposts have shifted. Here's the honest breakdown:
The case for "yes"
Coding builds transferable thinking skills. Learning to code sharpens your problem-solving skills, boosts your logic, and teaches you to break big challenges into bite-sized wins — superpowers AI can't steal.
AI makes coders more capable, not obsolete. AI hasn't made programming obsolete — it's made it accessible to more people and opened up possibilities that didn't exist before, but you still need to learn the fundamentals, since understanding code is more valuable now, because AI amplifies what you know rather than replacing what you don't.
Experienced coders have a real edge over pure "vibe coders." One engineer put it bluntly: as a professional engineer with over 10+ years of experience, "I know when AI spits out garbage and what needs fixing," an edge that everyone who learned to code the hard way 5+ years ago shares. His advice: you need to learn to code before you can learn to use AI to help you code — if you lean on AI too early, you skip the struggle and the learning, and you might get working code without understanding why it works.
AI still can't do the "human" parts of the job. Although it is constantly getting better, AI isn't going to replace programmers anytime soon, since writing code itself is only a small part of creating software — developers communicate with customers, document plans, work with teams, and make decisions that require critical thinking. Similarly, as of now, AI is not equipped to replace programmers and software engineers, and current GenAI tools have several limitations when it comes to coding, making foundational computer science knowledge and critical thinking skills essential.
The honest caveats
The job market data is genuinely mixed, especially for entry-level roles. One data scientist who now has AI write "virtually every line" she commits dug into the numbers and found the Bureau of Labor Statistics shows that "computer programmer" roles dropped about 27% in just two years, with another 6% decline projected through 2034. Other sources report entry‑level developer hiring fell 25% in 2024, and employment for developers aged 22‑25 dropped nearly 20%.
The role itself is changing, not disappearing. AI will not replace programmers but will fundamentally change the development landscape, making human creativity and problem-solving essential. Anthropic's own CEO has weighed in dramatically: Dario Amodei recently said he believes AI will soon be writing 90 percent of all code. Yet even Karpathy's vision of the future still involves programmers — just doing different work: "A large portion of programmers of tomorrow do not maintain complex software repositories, write intricate programs, or analyze their running times. They collect, clean, manipulate, label, analyze and visualize data that feed neural networks."
Fear is common, but so is adaptation. With 30 percent of coders saying they believe that AI will replace them, there's fear and uncertainty in the air. But the more common industry take is: AI won't replace software engineers, but it will replace software engineers who don't adapt to using AI — a distinction crucial for understanding the future of the profession.
My take
If you're asking "should I invest time in this," the answer is yes — with three practical adjustments to how you learn in 2026:
- Learn fundamentals before leaning on AI tools. Struggle through problems yourself first, then compare your solution to what an AI produces — that's how you build the judgment to catch its mistakes.
- Expect the job to look different than it did 5 years ago. Less rote syntax-writing, more architecture, review, debugging AI output, and understanding business context — many engineers already report using AI for around 40% of their work.
- Entry-level bar is rising. Interns today perform at levels similar to full-time engineers, and there's a foreseeable future where fresh graduates are expected to work at a level closer to today's senior engineers — so plan to build real projects, not just tutorials.
Bottom line: coding as a pure "typing syntax" skill is losing value fast, but coding as a way to think, build, and direct AI tools effectively is arguably more valuable than ever.
16 sources the model cited
- https://medium.com/@maxstoneSL/the-1-000-question-is-it-still-worth-learning-to-code-in-th
- https://medium.com/data-science-collective/should-you-still-learn-to-code-in-2026-034685e1
- https://www.databilitylabs.com/2025/03/is-it-still-worth-learning-to-code-in.html
- https://dailypythonprojects.substack.com/p/automatic-coding
- https://dev.to/adridev24/its-worth-learning-coding-in-2025-175i
- https://mimo.org/blog/how-to-learn-coding-learn-to-code-for-free
- https://vegapunk.medium.com/how-to-learn-coding-fast-in-2025-smart-roadmap-for-beginners-7
- https://codingwithroby.substack.com/p/should-you-still-learn-to-code-in
- https://dev.to/dealedev/should-you-still-learn-to-code-in-2023-2024-e1l
- https://brainhub.eu/library/software-developer-age-of-ai
- https://www.scaler.com/blog/will-ai-replace-software-engineers-truth-opinions-and-career-i
- https://coursiv.io/blog/will-ai-replace-programmers
- https://www.forbes.com/sites/bernardmarr/2025/08/04/myth-or-reality-will-ai-replace-comput
- https://www.coursera.org/articles/will-ai-replace-programmers
- https://dev.to/arslanyousaf12/will-ai-replace-software-engineers-a-reality-check-4bl3
- https://100daysofcode.substack.com/p/is-ai-replacing-software-engineers
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Short answer: Yes, but how you learn matters more than ever
- If you're asking "should I invest time in this," the answer is yes
- coding as a way to think, build, and direct AI tools effectively is arguably more valuable than ever
Sample 3 of 6The model's answer, recorded unedited
Short answer: Yes, it's still worth learning to code — but the why and how you learn matter more than ever, and the entry-level job market has genuinely gotten tougher.
The case for learning to code
The overwhelming consensus, even amid AI hype, is "yes." As one recent analysis put it: "Is it still worth coding? The response is a definite, absolute yes." But the framing has shifted — "the 'code' itself is not really the final point any longer; rather, it is the tool. The objective is to become an outstanding problem-solver, a digital architect".
Coding is also increasingly useful outside traditional software jobs. Sectors like finance, healthcare, and entertainment increasingly rely on software to innovate and streamline operations, so coding literacy has value well beyond "becoming a developer."
Why AI makes fundamentals more important, not less
A common misconception is that AI eliminates the need to learn programming basics. Practitioners who use AI coding tools daily disagree: "you still need to learn the fundamentals. In fact, understanding code is more valuable now than ever, because AI amplifies what you know rather than replacing what you don't."
This shows up directly in professional workflows. One experienced engineer described the tradeoff bluntly: "You need to learn to code before you can learn to use AI to help you code... if you lean on AI too early, you skip the struggle. You skip the learning. You might get working code, but you won't understand why it works... When something breaks, you won't know how to fix it without AI." His recommended approach is to "use AI as a force multiplier, not a crutch".
Even a self-described heavy AI user who says "AI writes virtually every line I commit" concluded that skepticism about AI's coding ability is really a skill issue: "people who are skeptical about AI being able to code at a professional level just aren't using the tools right."
The honest downside: the job market has cooled, especially for juniors
This is the part optimistic "learn to code!" articles often gloss over, and it's real:
- Bureau of Labor Statistics data shows "computer programmer" roles dropped about 27% in just two years, with another 6% decline projected through 2034.
- Indian IT services companies have reduced entry-level roles by 20%–25% due to automation and AI, and job platforms like LinkedIn, Indeed, and Eures noted roughly a 35% decline in postings for new grads.
- More broadly, US tech job postings are down 36% from February 2020 levels as of July 2025, and one large-scale labor study tracked millions of individual worker records through September 2025 to quantify the decline in junior developer employment.
- AI was directly responsible for over 10,000 US job cuts in July 2025 alone, per Fortune reporting — though the same source notes real opportunities still exist for CS grads who position themselves well.
Bottom line
If your only goal is "get a junior dev job easily," be aware the market is more competitive than it was 5 years ago — AI has raised the bar for what a "junior" needs to know. But if the question is "should a person learn to code as a skill," the answer is still yes, for three reasons:
- Problem-solving and system-thinking skills transfer everywhere, tech job or not.
- AI tools make you far more productive if you understand the fundamentals — they're a poor substitute for understanding when you don't.
- Demand hasn't disappeared, it's shifted — toward people who can architect, evaluate AI output, debug, and take on more senior/strategic responsibility earlier, rather than pure syntax-typing.
The realistic takeaway: learn it, but learn it deeply (data structures, debugging, systems thinking) rather than just prompt-engineering your way to working code, and go in with eyes open that the first job is harder to land than it was a few years ago.
23 sources the model cited
- https://medium.com/@maxstoneSL/the-1-000-question-is-it-still-worth-learning-to-code-in-th
- https://medium.com/data-science-collective/should-you-still-learn-to-code-in-2026-034685e1
- https://dailypythonprojects.substack.com/p/automatic-coding
- https://dev.to/adridev24/its-worth-learning-coding-in-2025-175i
- https://mimo.org/blog/how-to-learn-coding-learn-to-code-for-free
- https://dev.to/bowmandown/programming-languages-worth-learning-in-2025-1i57
- https://codingwithroby.substack.com/p/should-you-still-learn-to-code-in
- https://vegapunk.medium.com/how-to-learn-coding-fast-in-2025-smart-roadmap-for-beginners-7
- https://dev.to/dealedev/should-you-still-learn-to-code-in-2023-2024-e1l
- https://najumi.fr/en/article/should-you-still-learn-to-code-ai-replacing-developers/
- https://coursiv.io/blog/will-ai-replace-programmers
- https://mimo.org/blog/should-you-still-learn-to-code-in-ai-driven-world
- https://medium.com/nerd-for-tech/is-coding-becoming-irrelevant-8-rules-to-learn-code-in-20
- https://ageofmachine.substack.com/p/should-you-still-learn-to-code-in
- https://dev.to/code_2/is-ai-taking-our-coding-jobs-heres-what-developers-need-to-know-in-2
- https://usercentrics.com/magazine/articles/junior-engineer-ai-job-market-survival-guide/
- https://intuitionlabs.ai/articles/ai-impact-graduate-jobs-2025
- https://www.sundeepteki.org/advice/impact-of-ai-on-the-2025-software-engineering-job-marke
- https://restofworld.org/2025/engineering-graduates-ai-job-losses/
- https://www.softwareseni.com/what-the-data-actually-shows-about-ai-and-junior-developer-em
- https://rockstardeveloperuniversity.com/entry-level-software-engineer-job-market-statistic
- https://www.finalroundai.com/blog/software-engineering-job-market-2026
- https://www.marketbeat.com/articles/ai-is-dramatically-decreasing-entry-level-hiring-at-bi
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Short answer: Yes, it's still worth learning to code
- the answer is still yes, for three reasons
- The realistic takeaway: learn it, but learn it deeply
Sample 4 of 6The model's answer, recorded unedited
Short answer: Yes, generally it's still worth it — but why and how you learn matters more than it used to.
Here's the more nuanced picture based on current data and expert opinion:
The job market signal is genuinely mixed
There's real disruption happening, especially at the entry level. The Bureau of Labor Statistics shows that "computer programmer" roles dropped about 27% in just two years, and they project another 6% decline through 2034. More broadly, in the United States, overall programmer employment fell a dramatic 27.5 percent between 2023 and 2025, and this decline has coincided with the rise of generative AI tools.
Entry-level jobs are taking the biggest hit. He notes that, while other economic conditions also factor into the job market, the pace of programmer employment decline has accelerated since generative AI came on the scene. One industry report notes entry-level positions now require the skill level that used to be mid-level expectations, and traditional apprenticeship-style hiring for juniors is breaking down.
But the broader software engineering field isn't shrinking — it's restructuring
Despite the scary headlines, most serious analyses point to a rebalancing rather than a collapse. According to the 2025 Stack Overflow Developer Survey, 84% of developers use AI tools now. Yet the software engineering job market is projected to grow by 17% through 2033—adding roughly 327,900 new roles. One analysis frames it well: this isn't a contradiction. This is exactly what happens when productivity tools reshape an industry... What's actually happening is a restructuring. The pattern is similar to past tech shifts — low-code developers now earn higher salaries on average, and traditional dev demand kept growing until the 2022 rate hikes, showing that easier tools historically expanded the market rather than shrinking it.
There's also a wage/skill polarization happening: developers with AI-relevant skills — machine learning, AI orchestration, prompt engineering, AI security — are commanding 15 to 25% salary premiums.
AI is a tool, not (yet) a full replacement for engineering judgment
Even people building AI coding tools argue coding literacy remains valuable. As one Anthropic Claude Code creator put it about the future of work broadly, AI systems that can take action across workplace computer tools are advancing rapidly and could soon alter responsibilities for software engineers, product managers, designers, and other knowledge workers... "It's going to expand to pretty much any kind of work that you can do on a computer." But the same analysis notes that the "builder" still needs deep engineering judgment — meaning that knowing how software actually works is what lets you direct and verify AI's output.
Someone who works daily on AI coding tools echoes this: people who are skeptical about AI being able to code at a professional level just aren't using the tools right... AI assistants like Claude Code are WAY past just being auto-complete and now able to do complex, multi-step workflows that literally span days. Yet even proponents of AI-first coding argue fundamentals still matter, because understanding code is more valuable now than ever, because AI amplifies what you know rather than replacing what you don't.
The role itself is shifting from "typist" to "architect/reviewer"
A recurring theme across sources: the work is moving away from writing every line by hand toward directing, reviewing, and architecting systems. As one practicing engineer describes it: AI coding tools [are] like having an incredibly skilled junior developer working with you. They can write code fast and handle routine tasks, but they need direction. Another puts the risk of skipping fundamentals bluntly: if you lean on AI too early, you skip the struggle. You skip the learning. You might get working code, but you won't understand why it works or if there are better ways to do it... when something breaks, you won't know how to fix it without AI.
My practical take
- If your goal is "get a stable, easy six-figure job by memorizing syntax" — that calculus has weakened, especially at the junior/generalist level.
- If your goal is "understand how to build and reason about software so you can direct AI effectively, debug what it produces, and solve real problems" — that's more valuable now, not less, because AI massively lowers the cost of producing code but doesn't eliminate the need for people who can judge whether that code is correct, secure, and well-architected.
- Coding literacy is also increasingly useful outside "software engineer" job titles — in data analysis, research, product management, and other fields where scripting/automation is a force multiplier, not the whole job.
So it's less "should I learn to code" and more "learn to code alongside AI, aim for problem-solving/architecture skills rather than rote syntax, and expect the entry-level job hunt to be tougher than it was 5 years ago."
27 sources the model cited
- https://medium.com/@maxstoneSL/the-1-000-question-is-it-still-worth-learning-to-code-in-th
- https://medium.com/data-science-collective/should-you-still-learn-to-code-in-2026-034685e1
- https://dailypythonprojects.substack.com/p/automatic-coding
- https://dev.to/adridev24/its-worth-learning-coding-in-2025-175i
- https://mimo.org/blog/how-to-learn-coding-learn-to-code-for-free
- https://dev.to/bowmandown/programming-languages-worth-learning-in-2025-1i57
- https://codingwithroby.substack.com/p/should-you-still-learn-to-code-in
- https://vegapunk.medium.com/how-to-learn-coding-fast-in-2025-smart-roadmap-for-beginners-7
- https://dev.to/dealedev/should-you-still-learn-to-code-in-2023-2024-e1l
- https://brainhub.eu/library/software-developer-age-of-ai
- https://medium.com/@ignatovich.dm/will-ai-replace-programmers-in-2026-2027-i-asked-the-ais
- https://www.index.dev/blog/will-ai-replace-software-developer-jobs
- https://www.morningbrew.com/stories/2025/05/02/how-ai-is-already-shaking-up-the-job-market
- https://spectrum.ieee.org/ai-effect-entry-level-jobs
- https://talentsprint.com/blog/is-AI-replacing-software-developers
- https://www.quora.com/Will-AI-replace-programmers-in-2026
- https://www.netcorpsoftwaredevelopment.com/article/will-ai-replace-programmers
- https://mimo.org/blog/will-ai-replace-software-engineers
- https://spectrum.ieee.org/learning-coding-age-of-ai
- https://medium.com/@lisa_/should-you-still-learn-programming-in-the-age-of-ai-4d1df4fa947e
- https://dev.to/hadil/should-you-still-learn-coding-in-the-age-of-ai-the-question-every-dev
- https://www.itprotoday.com/programming-languages/should-you-learn-to-code-in-the-age-of-ai
- https://fintechlab.nus.edu.sg/?p=5061
- https://www.comp.nus.edu.sg/news-media/you-think-ai-will-render-coding-redundant-not-so-fa
- https://dev.to/queen_shecoder/should-we-still-learn-to-code-in-the-age-of-ai-582d
- https://mostlypython.substack.com/p/yes-you-should-still-learn-to-code
- https://ageofmachine.substack.com/p/should-you-still-learn-to-code-in/comments
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Short answer: Yes, generally it's still worth it — but why and how you learn matters more than it used to.
- So it's less "should I learn to code" and more "learn to code alongside AI
- that's more valuable now, not less
Sample 5 of 6The model's answer, recorded unedited
Short answer: Yes, it's still worth learning to code — but the reasons and the way you should learn have shifted quite a bit because of AI.
The tricky part: entry-level jobs are genuinely harder to get right now
This isn't just internet hand-wringing — the data backs it up:
- A Stanford study found entry-level employment in AI-risk jobs plunged 13% since 2022, with software developers hit hardest — employment down nearly 20% since ChatGPT launched.
- New grads used to make up 15% of hires at Big Tech firms pre-pandemic; now it's down to 7%.
- Entry-level hiring at big tech companies has dropped by more than 50% over the last three years, and employers now expect fresh graduates to handle sales, project management, and customer-facing roles.
- Some analyses put it even more starkly — one report notes entry-level software engineering job postings dropped sharply, and companies like Salesforce have paused junior hiring for periods.
So if your only goal is "learn to code, walk into an easy junior dev job," that path has narrowed. This is real and worth taking seriously.
But the picture isn't all bad — and coding skill itself is arguably becoming more valuable, not less
A few counterpoints matter a lot:
- Overall engineering hiring is proving resilient at scale. While total hiring across large tech companies dropped 25% compared to 2019 levels, engineering roles saw a much smaller decline of just 11%, and engineers comprised 55% of all new hires in 2025 across major tech companies — up from 46% in 2019.
- Demand hasn't disappeared — it's shifted toward AI-adjacent skills. Demand for AI-related technical roles remains strong, with companies wanting fresh graduates who can build, customize, or oversee AI systems — roles like machine learning engineer, data scientist, or cloud architect — which are in high demand and cannot easily be offshored or automated.
- Employers still want CS grads overall. Computer science majors were tied for the top spot in employer demand, with 67.1% of respondents planning to hire them, per the NACE Winter 2025 Salary Survey.
- The skill of coding is what makes AI tools useful, not obsolete. As one developer who now writes almost no code by hand put it, "AI writes virtually every line I commit," yet people who dismiss AI's coding ability "just aren't using the tools right" — implying that knowing how to direct, review, and debug AI-generated code is itself a serious skill, not a bypass of one.
- Coding fundamentals remain the leverage point for using AI well: understanding code lets you evaluate what an AI assistant produces, catch its mistakes, and combine pieces into something that actually works — which is a different (and arguably higher-value) skill than typing syntax from memory.
What this means practically
- Don't learn to code the old way (memorize syntax, grind LeetCode in isolation) and expect the old outcome (guaranteed entry-level job). That specific bargain is weaker than it used to be.
- Do learn to code if you want to: build things yourself, understand and direct AI tools instead of being at their mercy, pivot into AI/ML-adjacent roles, or just develop strong problem-solving and systems-thinking skills — skills repeatedly described as durable value regardless of who (or what) types the code.
- Pair coding fundamentals with AI-tool fluency from day one. The strongest current advice is to learn both — how code actually works and how to work productively alongside Copilot/Claude/ChatGPT-style tools, since "more than 84% of respondents were using or planning to use AI tools" according to Stack Overflow's 2025 developer survey, and developers who are still learning were even more likely to lean on them.
- Expect the job market entry point to be different, not gone — you may need a stronger portfolio, more specialization (AI/ML, security, infra), or a longer runway than a graduate five years ago would have needed.
Bottom line: Learning to code is still worth it as a skill and a way of thinking, and overall engineering hiring is holding up better than the scarier headlines suggest — but treat it as a foundation for working with AI and specializing, not as an automatic ticket to an easy junior job the way it might have been in 2015.
18 sources the model cited
- https://medium.com/@maxstoneSL/the-1-000-question-is-it-still-worth-learning-to-code-in-th
- https://medium.com/data-science-collective/should-you-still-learn-to-code-in-2026-034685e1
- https://www.databilitylabs.com/2025/03/is-it-still-worth-learning-to-code-in.html
- https://dailypythonprojects.substack.com/p/automatic-coding
- https://dev.to/adridev24/its-worth-learning-coding-in-2025-175i
- https://mimo.org/blog/how-to-learn-coding-learn-to-code-for-free
- https://vegapunk.medium.com/how-to-learn-coding-fast-in-2025-smart-roadmap-for-beginners-7
- https://codingwithroby.substack.com/p/should-you-still-learn-to-code-in
- https://dev.to/dealedev/should-you-still-learn-to-code-in-2023-2024-e1l
- https://sfstandard.com/2025/08/27/ai-entry-level-jobs-decline/
- https://intuitionlabs.ai/articles/ai-impact-graduate-jobs-2025
- https://restofworld.org/2025/engineering-graduates-ai-job-losses/
- https://www.sundeepteki.org/advice/impact-of-ai-on-the-2025-software-engineering-job-marke
- https://techcrunch.com/2026/06/24/ai-was-supposed-to-kill-engineering-jobs-but-new-data-su
- https://digitaleconomy.stanford.edu/wp-content/uploads/2025/08/Canaries_BrynjolfssonChanda
- https://rockstardeveloperuniversity.com/entry-level-software-engineer-job-market-statistic
- https://aliciasassermodestino.com/wp-content/uploads/2025/06/Impact_of_GenAI_on_SWEs_06162
- https://mothasa.substack.com/p/the-junior-developer-is-going-extinct
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Short answer: Yes, it's still worth learning to code
- coding skill itself is arguably becoming more valuable, not less
- Bottom line: Learning to code is still worth it as a skill and a way of thinking
Sample 6 of 6The model's answer, recorded unedited
It's still worth it — but the how and why matter more than they used to. Here's an honest breakdown of the current landscape:
The job market is real but has shifted
The traditional "learn to code, get a job easily" pipeline has gotten harder, especially for beginners. AI is taking over tasks that once gave junior engineers a foothold, while experienced developers affected by recent layoffs are now applying for roles below their previous level or pay grade, creating tougher competition at the entry level. Generative AI tools, corporate cost-cutting, and an influx of experienced talent from industry-wide layoffs have combined to squeeze opportunities for newcomers, and the traditional entry-level ladder — from intern to junior engineer — is giving way to roles where day-one responsibilities resemble what used to be mid-level expectations.
But this doesn't mean the field is dying. Total tech employment has increased by 20.7% since 2019, and the total number of tech job postings have risen by 56.8%, indicating that it's not the market that is the issue, but the changing nature of the field. Similarly, recent data shows software engineering remained among the highest-volume professional job categories in January 2026 posting data, with 140,068 Software Engineer postings and 137,176 mentioning Python. As one analysis puts it, what has changed is the shape of the market, not its existence — hiring is more selective, entry-level competition is harder, and employers increasingly expect engineers to use AI tools while still owning correctness.
AI is changing what "coding" means, not eliminating it
AI coding assistants are now mainstream. Over 70% of developers now use AI tools in their daily workflow, and tools like GitHub Copilot are reportedly boosting productivity significantly. Importantly, though, most analyses agree AI is a collaborator, not a replacement: Copilot is best interpreted as an "AI pair-programmer," not a replacement, and its value lies in reducing repetitive work and freeing developers to focus on architecture, design, and business logic.
The catch is that using these tools well still requires real understanding. Companies are now prioritizing experienced engineers and those with AI skills over entry-level candidates, and interestingly, since early 2023, AI coding tools have attracted nearly $1 billion in funding, and developers using them report productivity gains of up to 35%, with employers now actively seeking engineers who can integrate these tools into their daily work. In other words, coding knowledge plus AI fluency is the valuable combination — not either alone.
What this means practically
- If you're aiming for a traditional junior developer job immediately after learning basics: it's harder than it was 5-10 years ago. Expect to need more than syntax — preparation must go beyond syntax knowledge and include design thinking, critical reasoning, and code review expertise.
- If you're learning to code as a general life/career skill: absolutely still worth it. Understanding how software works helps you evaluate AI-generated code, build your own tools, automate tasks, and work more effectively in almost any technical or semi-technical role — even if you're not a "software engineer."
- The winning strategy isn't "learn to code instead of AI" or "skip coding and just use AI" — it's learning fundamentals (logic, data structures, debugging, system design) alongside how to direct AI tools effectively. Multiple sources frame this as a spectrum from basic prompt-engineering/no-code use up to deep coding mastery combined with AI orchestration, with the biggest career payoff at the higher end.
Bottom line: Learning to code is still worth it, but treat it as learning to think computationally and work with AI tools, not just memorizing syntax for a guaranteed entry-level job. The people struggling most right now are those with only surface-level skills and no differentiation; the ones doing well are combining real fundamentals with fluent AI-assisted workflows.
15 sources the model cited
- https://lemon.io/blog/software-engineering-job-market/
- https://codesmith.io/blog/is-the-software-job-market-oversaturated-in-2025
- https://blog.rezscore.com/software-engineering-job-market-2026/
- https://mev.com/blog/software-engineer-job-market-august-2025
- https://talent500.com/blog/entry-level-developer-jobs-2025/
- https://distantjob.com/blog/software-engineer-job-market/
- https://rockstardeveloperuniversity.com/entry-level-software-engineer-job-market-statistic
- https://www.coursera.org/articles/software-engineer-career-path
- https://medium.com/@danielthomas78/should-you-still-learn-to-code-in-2026-the-honest-answe
- https://medium.com/@reliabledataengineering/ai-is-writing-46-of-all-code-github-copilots-r
- https://alexbobes.com/programming/how-to-learn-programming-in-2025/
- https://ainexislab.com/github-copilot-review-pros-cons-developer-2025/
- https://medium.com/javarevisited/top-10-ai-coding-tools-every-developer-should-learn-in-20
- https://medium.com/@sourleangchhean/introduction-to-ai-in-programming-22278abaae56
- https://www.coursera.org/learn/pearson-learn-github-copilot-by-example-video-course-tvzyp
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - It's still worth it — but the how and why matter more than they used to.
- Bottom line: Learning to code is still worth it, but treat it as learning to think computationally and work with AI tools
- If you're learning to code as a general life/career skill: absolutely still worth it.
OpenAI gpt-5.5-2026-04-23 cited sources in 6 of 6, 21 in totalSample 1 of 6The model's answer, recorded unedited
Yes—learning to code is still worth it right now, but the reason has changed. It’s less “learn syntax → get a junior dev job” and more “learn enough software thinking to build, automate, evaluate AI output, and solve real problems.” In the U.S., software developer/QA/tester employment is still projected to grow 15% from 2024–2034, much faster than average, but the market is tougher for beginners than it was a few years ago. ([bls.gov](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?src_trk=em66208e30428cf5.482550521236198752&utm_source=openai))
The big caveat: entry-level coding is under pressure. AI tools can now handle a lot of boilerplate, small bug fixes, simple scripts, and first drafts. Recent labor-market research found a 14–15% relative decline in junior vs. senior software developer vacancies, which supports what many beginners are feeling: the “first job” bar is higher. ([iza.org](https://www.iza.org/publications/dp/18723/generative-ai-and-the-redefinition-of-entry-level-software-work?utm_source=openai))
At the same time, AI hasn’t made coding irrelevant—it has made coding judgment more valuable. Stack Overflow’s 2025 survey found AI tool adoption is widespread, with many developers using tools like ChatGPT and GitHub Copilot, but sentiment and trust are mixed; developers still need to understand, debug, secure, and maintain what AI produces. ([survey.stackoverflow.co](https://survey.stackoverflow.co/2025/ai?utm_source=openai))
So my practical answer is:
Learn to code if you want any of these:
- Build apps, websites, automations, games, data tools, or AI-powered products.
- Get into tech, cybersecurity, data, robotics, finance, operations, product, or entrepreneurship.
- Use AI better than non-technical people.
- Understand systems deeply enough to spot when AI is wrong.
- Create leverage in your current career, even if you don’t become a full-time software engineer.
Be more cautious if your goal is only:
- “I want a guaranteed remote six-figure job fast.”
- “I’ll learn basic HTML/Python and AI will do the rest.”
- “I don’t actually like problem-solving, debugging, or continuous learning.”
What I’d learn in 2026
If starting from scratch, I’d do this:
- Python — automation, data, AI scripting, APIs.
- Web basics — HTML, CSS, JavaScript, HTTP, databases.
- Git/GitHub — version control and portfolio.
- SQL — still useful everywhere.
- AI-assisted development — use ChatGPT/Copilot/Cursor/etc., but learn to verify code.
- One real project every month — not tutorials only.
A good beginner path would be: Python + JavaScript + Git + SQL + projects + AI tools. Don’t just “learn programming”; learn to ship things.
Bottom line
Yes, it’s worth learning to code—but don’t learn it like it’s 2015. Learn fundamentals, use AI as a power tool, build a portfolio, and aim to become the person who can define problems, design solutions, and verify the machine’s work. That skillset is still valuable.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes\u2014learning to code is still worth it right now, but the reason has changed.
- Yes, it\u2019s worth learning to code\u2014but don\u2019t learn it like it\u2019s 2015.
- A good beginner path would be: Python + JavaScript + Git + SQL + projects + AI tools.
Sample 2 of 6The model's answer, recorded unedited
Yes — it’s still worth learning to code right now, but the reason has changed.
It’s not worth learning only because “coding = guaranteed tech job.” The entry-level market can be competitive, and AI tools have raised the bar. But it is worth learning because coding is becoming a leverage skill: it helps you automate work, build products, understand AI systems, analyze data, and communicate with technical teams.
In the U.S., software-related jobs still have a strong official outlook: the Bureau of Labor Statistics projects software developers, QA analysts, and testers to grow 10% from 2025 to 2035, much faster than average, with a May 2025 median annual wage of $135,980. ([bls.gov](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?utm_source=openai)) At the same time, AI is now part of normal developer work: Stack Overflow’s 2025 survey found widespread AI-tool use among developers, but also declining trust in AI output, meaning people still need enough coding knowledge to verify, debug, and design systems rather than just prompt tools blindly. ([survey.stackoverflow.co](https://survey.stackoverflow.co/2025/ai?utm_source=openai))
The best reason to learn now: AI makes beginners more powerful if they learn fundamentals. You can use AI as a tutor, code reviewer, and pair programmer — but you still need to understand logic, data structures, APIs, debugging, security basics, and how software fits together.
My honest take
Learn to code if you want to:
- build apps, websites, automations, games, tools, or AI projects;
- improve your career in business, science, finance, design, marketing, operations, etc.;
- understand technology instead of just consuming it;
- have a flexible skill that compounds over years.
Be cautious if your only goal is:
- “get a six-figure remote job quickly”;
- “AI will write everything for me”;
- “I’ll do a 3-month bootcamp and be set.”
That path is much less reliable than it used to be.
What I’d learn in 2026
If you’re starting from zero:
- Python — best first language for automation, data, AI, scripting.
- Web basics — HTML, CSS, JavaScript.
- Git/GitHub — version control and portfolio.
- SQL — extremely useful for real jobs.
- APIs — how software systems talk to each other.
- AI-assisted coding — learn to use ChatGPT/Copilot/Cursor-style tools, but always read and test the code.
Best strategy
Don’t just “study coding.” Pick a problem and build things.
Examples:
- a personal budgeting app;
- a workout tracker;
- a web scraper;
- a Discord bot;
- a small business dashboard;
- an AI-powered study assistant;
- automation for your current job.
After 3–6 months, you’ll know whether you enjoy it and whether you want to go deeper.
Bottom line
Yes, it’s worth learning to code — but learn it as a problem-solving and leverage skill, not as a magic job ticket. The people who will benefit most are the ones who combine coding fundamentals with AI tools, domain knowledge, and real projects.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes — it's still worth learning to code right now, but the reason has changed.
- Yes, it's worth learning to code — but learn it as a problem-solving and leverage skill, not as a magic job ticket.
Sample 3 of 6The model's answer, recorded unedited
Yes — it’s still worth learning to code right now, but the reason has changed. Don’t learn to code because “typing code” will be rare and magical. Learn it because it teaches you how software works, how to automate things, how to build products, and how to judge/debug what AI tools produce.
As of 2026, the U.S. outlook for software developers is still strong: the Bureau of Labor Statistics projects 15% growth from 2024 to 2034 for software developers, QA analysts, and testers, much faster than the average occupation. ([bls.gov](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?src_trk=em66208e30428cf5.482550521236198752&utm_source=openai)) But the entry-level market is more competitive than it was in the 2018–2021 boom, and AI tools are changing expectations: Stack Overflow’s 2025 survey found AI tool adoption among developers is now mainstream, while trust/sentiment is mixed rather than universally positive. ([survey.stackoverflow.co](https://survey.stackoverflow.co/2025/ai?utm_source=openai))
The key distinction:
Learn to build, not just “code”
AI can generate snippets, boilerplate, tests, scripts, and explanations. But someone still has to know:
- what to build
- whether the code is correct
- how systems fit together
- how to debug failures
- how to secure, deploy, and maintain software
- how to translate messy human/business needs into working tools
That’s where learning to code is still valuable.
If your goal is a job, be strategic
A vague “I know HTML/CSS/JS/Python” is less compelling now. Better paths are:
- Python + automation + data/AI tooling
- JavaScript/TypeScript + web apps
- SQL + data analysis
- cloud basics + APIs
- cybersecurity or DevOps fundamentals
- domain-specific coding — finance, healthcare, manufacturing, law, marketing, science, etc.
GitHub’s 2025 Octoverse report shows AI-related development is growing heavily, with Python still dominant for AI/data science and TypeScript becoming the most-used language on GitHub by monthly contributors. ([github.blog](https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-second-as-ai-leads-typescript-to-1/?utm_source=openai)) Dice’s 2026 tech jobs report also points to AI-driven operations spreading across industries beyond just “tech companies.” ([dice.com](https://www.dice.com/hiring/recruitment/reports/dice-tech-job-report?utm_source=openai))
My honest recommendation
If you’re curious, start. Give it 60–90 days before making a huge life decision.
A good beginner plan:
- Learn Python basics.
- Use AI as a tutor, but type and run the code yourself.
- Build small useful projects:
- expense tracker
- resume/job scraper
- personal dashboard
- file organizer
- simple website
- chatbot over your own notes
- Learn Git/GitHub.
- Learn APIs and databases.
- Build 2–3 portfolio projects that solve real problems.
When it might not be worth it
It may not be worth it if your only motivation is “easy six-figure remote job fast.” That era is mostly gone. But if you want a durable skill that compounds across careers, coding is still one of the best things you can learn.
Bottom line: yes, learn to code — but learn it alongside AI tools, product thinking, debugging, and real-world problem solving. The future probably has fewer “code monkeys,” but more people who can use code + AI to build useful systems.
4 sources the model cited
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?src_tr
- https://survey.stackoverflow.co/2025/ai?utm_source=openai
- https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-s
- https://www.dice.com/hiring/recruitment/reports/dice-tech-job-report?utm_source=openai
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes — it's still worth learning to code right now, but the reason has changed.
- Bottom line: yes, learn to code — but learn it alongside AI tools, product thinking, debugging
- if you want a durable skill that compounds across careers, coding is still one of the best things you can learn
Sample 4 of 6The model's answer, recorded unedited
Yes — it’s still worth learning to code right now, but the reason has changed.
It’s less “learn syntax → get a guaranteed junior dev job” and more:
> Learn coding so you can build, automate, understand systems, and use AI tools effectively.
In the U.S., software-related jobs are still projected to grow strongly: BLS projects 15% growth from 2024–2034 for software developers, QA analysts, and testers, much faster than average. BLS also projects software developers specifically to add 267,000+ jobs over that period. ([bls.gov](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?src_trk=em66208e30428cf5.482550521236198752&utm_source=openai)) But the entry-level market is tougher than it used to be, and reporting in 2026 notes that hiring has cooled for entry-level software developers as AI tools absorb more routine coding work. ([apnews.com](https://apnews.com/article/f0dca8e4f7e16297ad27c2b02adc2530?utm_source=openai))
So the answer is:
Learn to code if you want leverage — not just a job title
Coding is worth it if you want to:
- build apps, websites, automations, games, tools, dashboards
- work in tech, data, cybersecurity, AI, product, robotics, finance, science, etc.
- automate your own work
- understand what AI-generated code is doing
- become harder to fool by AI tools
- create side projects or startups
- communicate better with engineers
It is less worth it if your only plan is:
> “I’ll do a 3-month course, memorize React, and easily land a six-figure remote job.”
That path is much more competitive now.
AI makes coding more valuable, not useless
AI can write a lot of code, but it still needs someone who can:
- describe the problem clearly
- judge whether the code is correct
- debug when it fails
- design the system
- understand tradeoffs
- secure and maintain the result
The 2025 Stack Overflow survey found high AI adoption among developers, but also declining positive sentiment and trust concerns — which basically means AI is useful, but not magic. ([survey.stackoverflow.co](https://survey.stackoverflow.co/2025/ai?utm_source=openai)) The winners are people who can combine coding fundamentals + AI tools + product/domain judgment.
What I’d learn in 2026
If you’re starting from zero, I’d pick one track:
Best general starting path
- Python
- automation
- data
- AI
- scripting
- backend basics
- Web basics
- HTML
- CSS
- JavaScript
- APIs
- Git/GitHub
- version control
- portfolio
- collaboration
- Databases
- SQL
- basic data modeling
- AI-assisted development
- use ChatGPT/Copilot/Cursor
- ask for explanations
- write tests
- review code critically
If your goal is a job
Do not just collect tutorials. Build things.
Good beginner portfolio projects:
- personal budget tracker
- habit tracker
- job application tracker
- small business website
- AI note summarizer
- Discord/Slack bot
- data dashboard
- workout planner
- simple marketplace clone
- API-backed web app with login and database
Employers care less that you “completed a course” and more that you can show working software.
My honest recommendation
If you’re curious, start. Coding is one of the highest-leverage skills you can learn.
But learn it like this:
> Coding fundamentals first, AI tools alongside, real projects always.
Give yourself 90 days. If after 90 days you can build small useful things and you enjoy solving the problems, keep going. If you hate the process, you still gained a valuable literacy skill.
A good 90-day plan:
- Weeks 1–3: Python basics
- Weeks 4–5: HTML/CSS/JavaScript basics
- Weeks 6–7: APIs + databases
- Weeks 8–10: build 2 real projects
- Weeks 11–12: polish, deploy, put on GitHub, write what you learned
Bottom line: Yes, learning to code is worth it — but learn to become a builder/problem-solver, not just a code typist.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes — it's still worth learning to code right now, but the reason has changed.
- If you're curious, start. Coding is one of the highest-leverage skills you can learn.
- Bottom line: Yes, learning to code is worth it — but learn to become a builder/problem-solver
Sample 5 of 6The model's answer, recorded unedited
Yes — it’s still worth learning to code right now, but the reason has changed. Don’t learn code because “typing code” will be scarce and magical; learn it because coding lets you build, automate, understand AI tools, debug systems, and turn ideas into working products.
As of 2026, the software field is not dead: the U.S. Bureau of Labor Statistics projects software developers/QA/testers to grow 10% from 2025–2035, faster than the average occupation, with software developers earning a $135,980 median annual wage in May 2025. Broader computer and IT occupations are also projected to grow faster than average. ([bls.gov](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?utm_source=openai))
The catch: the beginner path is harder than it used to be. AI tools can handle more simple coding tasks, so employers have less patience for people who only know basic syntax or can follow tutorials. A 2026 IZA paper found a 14–15% relative decline in junior vs. senior software developer vacancies, suggesting the entry-level rung has weakened. ([iza.org](https://www.iza.org/publications/dp/18723/generative-ai-and-the-redefinition-of-entry-level-software-work?utm_source=openai))
So the best strategy is not “learn to code like it’s 2015.” The best strategy is:
- Learn fundamentals: variables, functions, data structures, APIs, databases, networking basics, debugging.
- Use AI from day one, but don’t blindly trust it. Stack Overflow’s 2025 survey found widespread AI use among developers, but also declining trust/sentiment toward AI tools — meaning human review and judgment still matter. ([survey.stackoverflow.co](https://survey.stackoverflow.co/2025/ai?utm_source=openai))
- Build real projects, not just course exercises: a personal finance tracker, automation scripts, a small web app, a Discord bot, a data dashboard, an AI-powered workflow tool.
- Learn one practical stack:
- Python for automation, data, AI, scripting.
- JavaScript/TypeScript for web apps.
- SQL for databases.
- Git/GitHub, APIs, cloud basics.
- Aim for “person who can solve problems with software,” not “person who memorized syntax.”
GitHub’s 2025 Octoverse data also shows developer activity is still expanding: GitHub reported over 180 million developers, 630 million projects, and major growth in Python, TypeScript, and AI-related projects. ([github.blog](https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-second-as-ai-leads-typescript-to-1/?utm_source=openai))
My honest answer:
- Worth it for career? Yes, but expect a tougher entry-level market and a higher bar.
- Worth it for business/productivity? Absolutely. Even basic coding can save you time, automate work, and help you use AI better.
- Worth it if you hate technical problem-solving? Probably not as a primary career path.
- Worth it if you want a guaranteed job after a 3-month bootcamp? Much less than before.
If you’re starting today, I’d learn Python + SQL + basic web/API concepts, while using AI as a tutor and code assistant. After 2–3 months, build 3–5 small projects that solve actual problems. That will tell you quickly whether you like it and whether it’s worth going deeper.
4 sources the model cited
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?utm_so
- https://www.iza.org/publications/dp/18723/generative-ai-and-the-redefinition-of-entry-leve
- https://survey.stackoverflow.co/2025/ai?utm_source=openai
- https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-s
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes — it’s still worth learning to code right now, but the reason has changed.
- Worth it for career? Yes, but expect a tougher entry-level market and a higher bar.
- If you’re starting today, I’d learn Python + SQL + basic web/API concepts
Sample 6 of 6The model's answer, recorded unedited
Yes — it’s still worth learning to code right now, but the “why” has changed.
If your goal is “get rich quickly by learning JavaScript for 3 months”, I’d be cautious. Entry-level tech is more competitive than it was a few years ago, and AI tools have made basic coding less scarce.
But if your goal is to become someone who can build, automate, analyze, customize, debug, and work effectively with AI, then coding is arguably more useful than before.
Why it’s still worth it
- Demand hasn’t disappeared. In the U.S., the Bureau of Labor Statistics projects employment for software developers, QA analysts, and testers to grow 15% from 2024 to 2034, much faster than average. It also projects software developers alone to add over 267,000 jobs in that period. ([bls.gov](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?nt=1&utm_source=openai))
- AI is changing the job, not eliminating the need for skill. Developers increasingly use AI tools, but the valuable skill is knowing what to ask for, how to verify it, how systems fit together, and when the generated code is wrong. Stack Overflow’s 2025 survey found high AI adoption but also major trust issues: 46% of developers said they don’t trust AI output accuracy. ([stackoverflow.co](https://stackoverflow.co/company/press/archive/stack-overflow-2025-developer-survey/?utm_source=openai))
- Coding is becoming a general productivity skill. Even if you don’t become a software engineer, coding helps in finance, science, marketing, operations, design, data analysis, entrepreneurship, cybersecurity, and automation. The World Economic Forum’s 2025 jobs report highlights AI, big data, networks, and cybersecurity among the fastest-growing skill areas. ([weforum.org](https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opportunities-by-2030-but-urgent-upskilling-needed-to-prepare-workforces/?utm_source=openai))
- The “developer” role is moving up the stack. GitHub’s 2025 Octoverse report describes developers increasingly acting as orchestrators who delegate to AI, review outputs, and connect tools/systems rather than just manually typing every line. ([github.blog](https://github.blog/news-insights/octoverse/the-new-identity-of-a-developer-what-changes-and-what-doesnt-in-the-ai-era/?utm_source=openai))
The wrong way to learn now
Don’t just memorize syntax or grind tutorials forever. AI can already generate lots of simple code. If you only learn “how to write a for-loop,” that’s not enough.
The right way to learn now
Learn coding as problem-solving + building real things:
- Start with Python or JavaScript/TypeScript
- Python: automation, data, AI, scripting.
- JavaScript/TypeScript: websites, apps, full-stack work.
- GitHub reported TypeScript and Python as top languages in 2025, with TypeScript becoming especially prominent. ([github.blog](https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-second-as-ai-leads-typescript-to-1/?utm_source=openai))
- Use AI, but don’t depend on it blindly
- Ask it to explain code.
- Ask it to review your code.
- Ask it for alternatives.
- Then run, test, break, and fix the code yourself.
- Build projects
Examples:
- personal budget tracker
- habit app
- browser automation script
- small website
- Discord/Slack bot
- data dashboard
- AI-powered tool for your own workflow
- Learn the fundamentals
The fundamentals still matter:
- variables, functions, loops
- data structures
- APIs
- databases
- debugging
- Git/GitHub
- command line
- testing
- basic security
- Pair coding with a domain
The best path is often not “generic coder.” It’s:
- coding + healthcare
- coding + finance
- coding + design
- coding + law
- coding + manufacturing
- coding + sales/ops
- coding + AI automation
- coding + cybersecurity
My honest take
Learning to code is worth it if you want leverage.
It gives you the ability to make computers and AI do useful work for you.
But learning to code as a guaranteed ticket to an easy job is not a safe bet anymore. The bar is higher. You’ll need projects, judgment, persistence, and comfort working with AI tools.
If you’re starting from zero, I’d aim for this:
> Don’t learn to code to compete with AI. Learn to code so you can control AI.
5 sources the model cited
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm?nt=1&u
- https://stackoverflow.co/company/press/archive/stack-overflow-2025-developer-survey/?utm_s
- https://www.weforum.org/press/2025/01/future-of-jobs-report-2025-78-million-new-job-opport
- https://github.blog/news-insights/octoverse/the-new-identity-of-a-developer-what-changes-a
- https://github.blog/news-insights/octoverse/octoverse-a-new-developer-joins-github-every-s
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes — it's still worth learning to code right now, but the "why" has changed.
- Learning to code is worth it if you want leverage.
- Don't learn to code to compete with AI. Learn to code so you can control AI.
Google gemini-3.6-flash cited no sourcesSample 1 of 6The model's answer, recorded unedited
The short answer is yes, absolutely—but the way you learn to code and what you should focus on have changed fundamentally.
If your image of coding is memorizing syntax line-by-line to write simple scripts, that version of software development is declining. However, if you view coding as learning how software works, how systems are designed, and how to solve problems using technology, it remains one of the most valuable skills you can acquire.
---
1. The Elephant in the Room: Artificial Intelligence
Generative AI tools (like GitHub Copilot, ChatGPT, Claude, and specialized AI coding agents) can generate boilerplate code, write functions, and fix syntax errors in seconds.
Because of this, some people ask, "If AI can write code, why learn?" Here is why human coders are still essential:
- AI makes mistakes: AI models frequently produce code with subtle bugs, security vulnerabilities, edge-case failures, or performance bottlenecks. If you don't understand how the code works, you won't be able to spot or fix those errors.
- Architecture and System Design: AI excels at generating small blocks of code, but humans still need to design the overarching architecture, ensure scalable security, integrate complex business logic, and decide what to build in the first place.
- AI is a multiplier, not a replacement: An experienced programmer using AI tools can often be 2x to 5x more productive. An absolute beginner using AI tools often generates code they don't understand, leading to fragile applications they can't debug.
---
2. The Current Job Market
The tech job market has shifted:
- The "Bootcamp Golden Era" has evolved: A few years ago, knowing basic HTML, CSS, and JavaScript was often enough to land a junior web development job. Today, the bar for entry-level developers is higher.
- Higher demand for depth: Companies are looking for developers who understand computer science fundamentals, backend architecture, cloud infrastructure, data pipelines, cybersecurity, and machine learning.
- New roles are emerging: Skills in AI engineering, prompt engineering/steering, system integration, and data engineering are in very high demand.
---
3. Benefits Beyond Getting a Software Engineering Job
Learning to code isn't just about becoming a full-time software developer. It provides several other major advantages:
- Superpowers for "Indie Hackers" and Entrepreneurs: With basic coding knowledge and AI coding assistants, a single person can now build, launch, and maintain a full web or mobile product that previously required a team of five.
- Automation and Efficiency: Knowing even a little Python or scripting lets you automate tedious office tasks, scrape web data, or analyze large datasets in roles like marketing, finance, or operations.
- Technological Literacy: Software powers almost every industry today. Understanding how databases, APIs, networks, and algorithms work makes you better at managing products, working with technical teams, or making strategic decisions in any field.
---
4. How to Learn to Code "Right Now"
If you decide to start, adapt your approach to the modern landscape:
- Focus on Fundamentals, Not Just Syntax:
- Learn basic programming logic, object-oriented concepts, algorithms, and data structures.
- Understand how web requests work, how databases store information, and how software systems talk to each other via APIs.
- Learn With AI, Don't Rely On It Completely:
- Use AI tools like a 24/7 personal tutor. Ask AI to explain confusing concepts, review your code, or suggest improvements.
- Avoid letting AI do all the work early on. If you skip writing and understanding basic code yourself, you won't develop the debugging muscles required to handle complex problems later.
- Build Real Projects Early:
- Don't get stuck in "tutorial hell" (watching endless video courses).
- Think of a small problem you want to solve or a simple app you want to build, and start building it.
- Pick the Right First Language:
- Python: Great for beginners, data analysis, automation, and AI/ML work.
- JavaScript / TypeScript: Ideal if you want to build websites, web apps, or interactive frontends.
- Java / C#: Excellent for understanding strong typing, software engineering principles, and enterprise systems.
---
Summary
Learning to code today is less about memorizing syntax and more about orchestrating systems, solving problems, and directing software (including AI) to build what you want.
If you approach it with a focus on problem-solving, architectural thinking, and using modern AI tools to accelerate your learning, it is still one of the most rewarding and impactful skills you can learn today.
Cited no sources.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - The short answer is yes, absolutely—but the way you learn to code and what you should focus on have changed fundamentally.
- it remains one of the most valuable skills you can acquire
- it is still one of the most rewarding and impactful skills you can learn today
Sample 2 of 6The model's answer, recorded unedited
The short answer is yes, but what and how you learn to code has fundamentally changed.
Learning to code is no longer about memorizing syntax or typing out boilerplate code line by line. Generative AI tools (like Claude, Cursor, and GitHub Copilot) can write syntax faster than any human. However, coding today is about problem-solving, architecture, logic, and directing AI to build software.
Here is a breakdown of why it is still worth learning, what has changed, and how you should approach it today.
---
Why It Is Still Worth Learning
- You Need Coding Knowledge to Verify AI Output
AI writes code that looks right, but it often contains subtle bugs, security vulnerabilities, edge-case failures, or performance bottlenecks. If you don't understand how code works, you won't be able to debug, review, or trust what AI generates. You can't be an effective conductor if you don't understand the music.
- Coding is an Efficiency "Superpower" When Combined with AI
A developer who knows how to use AI tools effectively is 5x to 10x more productive than a traditional developer from a few years ago. Knowing the fundamentals allows you to turn high-level ideas into functioning software in hours instead of weeks.
- Software Systems Are Becoming More Complex
While simple web pages or basic scripts are easy to build with AI, modern infrastructure—cloud systems, distributed databases, machine learning pipelines, and cybersecurity—is extremely complex. Understanding system design, data structures, and software architecture is more valuable than ever.
- Computational Thinking and Problem Solving
Learning to code teaches you how to break down massive, ambiguous problems into logical steps. This mental model is valuable across every industry, whether you become a software engineer, product manager, data analyst, or founder.
---
What Has Changed (The Reality Check)
- The "12-Week Bootcamp to a $100k Job" Era is Over: The tech job market has normalized after the post-pandemic hiring boom. Entry-level positions are competitive, especially for candidates who only know basic web development (HTML, CSS, simple React).
- Syntax Memorization is Obsolete: You don't need to memorize exact library methods or regex patterns anymore. AI handles the syntax lookup.
- Focus Has Shifted Upstream: The job of a developer is shifting from writing code to defining logic, specifying requirements, designing systems, and reviewing code.
---
How to Approach Learning to Code Today
If you decide to start, follow this modern roadmap:
- Focus on Core Fundamentals First
- Learn logic, control flow, functions, object-oriented programming, and basic data structures (using a beginner-friendly language like Python or JavaScript/TypeScript).
- Understand how the web works (HTTP, APIs, client-server models) and how databases store information.
- Learn to Use AI as a Pair Programmer, Not a Crutch
- Use AI to explain concepts, suggest solutions, or fix syntax errors.
- Rule of thumb: Never paste AI code into a project if you cannot explain line-by-line what it does.
- Learn System Architecture and Debugging
- Spend more time learning how different parts of an application talk to each other (frontend, backend, databases, third-party APIs).
- Practice reading and debugging existing code, as this will make up a large portion of modern engineering work.
- Combine Coding with Domain Knowledge
- The most valuable professionals are those who combine coding with specific domain expertise (e.g., Finance + Code, Healthcare + AI, Design + Web Development). Build tools that solve real problems in fields you care about.
---
The Verdict
If your goal is to learn simple syntax in order to land an easy remote entry-level job overnight, you will likely be disappointed.
However, if your goal is to understand how technology works, build tools, automate workflows, and use AI to build software faster than ever before, learning to code is one of the most valuable skills you can acquire today.
Cited no sources.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - The short answer is yes, but what and how you learn to code has fundamentally changed.
- Here is a breakdown of why it is still worth learning
- learning to code is one of the most valuable skills you can acquire today
Sample 3 of 6The model's answer, recorded unedited
The short answer is yes, but how you learn and what it means to "code" has fundamentally changed.
If your idea of learning to code is memorizing syntax, memorizing JavaScript functions, or writing every line of code from scratch by hand, then no, that traditional skill set is rapidly losing value.
However, if learning to code means understanding computational thinking, system architecture, data flow, and how software works, it is arguably more valuable and empowering today than ever before.
---
The Reality: How AI Changed the Game
Generative AI (tools like Cursor, Claude, GitHub Copilot, and ChatGPT) has shifted the primary bottleneck of software creation:
- Old World: The bottleneck was writing the code (translating logic into language syntax).
- New World: The bottleneck is problem definition, system architecture, edge-case handling, and code verification.
AI can generate syntactically correct code in seconds. However, AI often makes logical errors, introduces security vulnerabilities, creates inefficient architecture, or produces code that fails at scale.
---
3 Reasons Why Learning to Code is Still Worth It
1. You can’t verify what you don't understand
Using AI to build software without knowing how to code is like using Google Translate to write a book in a language you don't speak. You might get a rough draft, but you won't know if it's grammatically wrong, offensive, or nonsensical.
Software development today is shifting from writing code to reading, auditing, and directing code. To steer AI effectively and spot silent bugs, you need a strong foundation in programming concepts.
2. The 80/20 Rule (Where real software engineering lives)
AI can get you 80% of the way to a working project very quickly. However, the remaining 20%—making the app secure, optimizing database performance, handling race conditions, integrating complex APIs, and ensuring scalability—requires genuine software engineering knowledge. That last 20% is what separates a toy project from a production-ready application.
3. Unprecedented Individual Leverage
A single developer today equipped with AI tools can build what used to take a team of 5 to 10 engineers. If you know how to code and how to leverage AI, your leverage as an individual—whether as an employee, freelancer, or founder—is higher than at any point in tech history.
---
How to Learn to Code Today (The Modern Approach)
If you decide to start learning today, adjust your strategy to reflect the modern tech landscape:
- Focus on Concepts Over Syntax: Don't waste weeks memorizing syntax rules that an LLM can generate instantly. Focus on understanding data structures, algorithms, databases, APIs, network requests, and object-oriented or functional paradigms.
- Use AI as a 24/7 Personal Tutor: Don't ask AI to "build this app for me" when learning. Instead, ask it: "Explain how this loop works line-by-line," or "Why did this error happen?"
- Learn to Read Code: Practice reading open-source code and AI-generated code. Train yourself to spot inefficiency, security flaws, and bad architecture.
- Learn System Architecture & Security: Focus on how systems connect—how frontends talk to backends, how databases store and index data securely, and how authentication works.
- Build Real Projects Immediately: Skip long passive video courses. Pick a project you care about, start building it with AI assistance, and dive deep into the parts you don't understand.
---
Bottom Line
Is it worth learning to code right now?
Yes. You are not learning to be a "human typewriter" who pumps out lines of syntax; you are learning to be an architect, orchestrator, and problem solver. AI hasn't killed coding—it has raised the level of abstraction, allowing you to build bigger, more ambitious things faster than ever before.
Cited no sources.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - The short answer is yes, but how you learn and what it means to "code" has fundamentally changed.
- ### 3 Reasons Why Learning to Code is Still Worth It
- Yes. You are not learning to be a "human typewriter"... you are learning to be an architect, orchestrator, and problem solver
Sample 4 of 6The model's answer, recorded unedited
The short answer is yes, but the reason you learn to code—and how you should learn it—has fundamentally changed.
With AI tools generating code faster than ever, the value is no longer in simply typing syntax or writing boilerplate code. Instead, the value lies in software engineering, problem-solving, and system design.
Here is a breakdown of why it is still worth learning, how the landscape has shifted, and how you should approach it today.
---
Why It Is Still Worth Learning
- AI is an Amplifier, Not a Complete Replacement
- AI can write snippets, catch syntax errors, and generate boilerplate code quickly. However, it still struggles with long-term context, complex edge cases, architectural decisions, and understanding real-world user needs.
- A non-coder using AI will often hit a wall when the code breaks or grows complex. A programmer using AI becomes 5x–10x more productive because they know how to guide the AI, spot bad logic, and debug errors.
- You Need to Know How Things Work to Debug Them
- Code generated by AI often contains subtle bugs, security vulnerabilities, or performance bottlenecks. If you don't understand programming fundamentals, you won't be able to evaluate whether the code AI gives you is safe, efficient, or maintainable.
- Software Engineering $\neq$ Just Writing Code
- "Coding" is only one part of building software. The harder parts are:
- System Architecture: How different services, databases, and APIs talk to each other.
- Product Thinking: Understanding what users actually need.
- Security & Scalability: Ensuring a system doesn't crash under load or leak user data.
- Maintainability: Writing software that a team can update and support for years.
- Computational Thinking Has Universal Value
- Learning to code trains your brain to break large, ambiguous problems into small, logical steps. This problem-solving framework is useful whether you end up working as a software developer, product manager, data analyst, entrepreneur, or researcher.
---
How the Landscape Has Changed
| Old Paradigm | New Paradigm |
| :--- | :--- |
| Focus on memorizing syntax and language rules. | Focus on computer science fundamentals, architecture, and logic. |
| Value measured by how fast you can type out functions. | Value measured by how effectively you frame problems and design systems. |
| Learning meant manually writing every line of code from scratch. | Learning means using AI as a pair programmer while understanding the underlying mechanics. |
| High demand for "bootcamp-level" basic web layout/CRUD coders. | High demand for engineers who understand AI integration, infrastructure, security, and complex logic. |
---
How to Learn to Code Effectively Today
If you decide to start now, change how you approach the learning process:
- Focus on Fundamentals First
- Learn concepts that don't change every few years: data structures, basic algorithms, how databases work, HTTP/networking, and object-oriented or functional programming principles.
- Use AI as a Personal Tutor, Not a Crutch
- Good use of AI: Ask AI to explain a concept, break down a confusing error message, or suggest three different ways to structure a function so you can compare them.
- Bad use of AI: Asking AI to write your entire assignment or project without reading or understanding the output.
- Build Complete, End-to-End Projects
- Don't stop at simple tutorials. Build a real application—host it online, connect it to a real database, set up authentication, and handle real user inputs. Dealing with integration issues is where true engineering skills are developed.
- Pick the Right First Language
- Python: Great for beginners, data science, automation, and AI/ML development.
- JavaScript/TypeScript: Essential for web development (both frontend and backend).
---
The Verdict
If your goal is simply to sit in a chair and type basic, repetitive code, that job is rapidly disappearing.
However, if your goal is to build products, solve complex problems, and leverage technology to create value, learning to code is more powerful now than it has ever been—because AI tools allow a single developer to build things that previously required an entire team.
Cited no sources.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - The short answer is yes, but the reason you learn to code—and how you should learn it—has fundamentally changed.
- learning to code is more powerful now than it has ever been
- Here is a breakdown of why it is still worth learning
Sample 5 of 6The model's answer, recorded unedited
Yes, it is still worth learning to code, but the reason why and the way you learn have fundamentally changed.
If your goal is simply to memorize syntax to write basic HTML or repetitive scripts, AI can already do that faster and better. However, if your goal is to build software, solve complex problems, and create products, learning to code is more powerful today than it has ever been.
Here is a breakdown of what has changed, why it’s still worth it, and how to approach learning today.
---
1. What Has Changed: The Shift from "Coder" to "Builder"
In the past, a large part of a software developer's job was writing boilerplate code, looking up syntax errors, and manually translating logic into a specific language.
Today, AI coding assistants handle much of the syntax and repetitive code generation. Because of this:
- Syntax memorization is less important. You don’t need to remember every function signature or library syntax.
- Architecture and critical thinking are essential. The hard part of software engineering was never typing out code; it was figuring out what to build, how systems talk to each other, how data flows, and how to ensure security and performance.
- Entry-level expectations are higher. Companies are looking less for "people who know Python syntax" and more for "people who can use code and AI tools to deliver end-to-end solutions."
---
2. Why It Is Still Worth Learning
A. AI is an Amplifier, Not a Total Replacement
AI tools make developers significantly faster, but they make mistakes—generating subtle bugs, security vulnerabilities, or inefficient code. To use AI effectively, you need to know how to:
- Read and evaluate the code AI generates.
- Debug when something breaks.
- Prompts AI effectively (which requires knowing technical concepts and software jargon).
A non-coder using AI will quickly hit a wall when an application grows complex or breaks. A developer using AI acts like an engineer managing an ultra-fast junior developer.
B. Computational Thinking is a Superpower
Learning to code teaches you how to break massive, ambiguous problems down into logical, step-by-step components. This mental model improves your problem-solving skills across every industry, whether you work in tech, finance, marketing, or healthcare.
C. Massive Superpowers for Solopreneurs and Founders
With modern AI tools and coding knowledge, a single person can build software that previously required a team of five developers. If you want to launch a startup, automate your daily workflow, or build side projects, learning code gives you unprecedented leverage.
---
3. How You Should Learn to Code Today
If you decide to start, adapt your strategy to the modern landscape:
- Focus on Fundamentals First:
- Don't rely on AI in your first few weeks. Learn basic logic, variables, loops, functions, object-oriented programming, data structures, and basic databases (SQL/NoSQL) on your own. You need to understand the underlying mechanics.
- Use AI as a 24/7 Personal Tutor:
- Instead of asking AI to "write this program for me," ask it: "Explain how this function works step-by-step," or "Why am I getting this error?" or "What are three different ways to structure this database?"
- Learn System Architecture & Security:
- Spend extra time learning how APIs work, how servers interact with clients, basic cloud architecture (AWS, Vercel, Supabase, etc.), and web security basics. This is where human oversight matters most.
- Build Real Projects End-to-End:
- Rather than doing abstract tutorial exercises, pick a real problem you want to solve and build a functional web or mobile app. Focus on getting a working product in front of real users.
---
The Verdict
Learning to code right now is like learning arithmetic right after the electronic calculator was invented. The tool changes how you do the work, but understanding the core math principles remains vital if you want to build anything meaningful.
If you approach it as learning to think logically, architect systems, and build solutions using modern tools, it remains one of the highest-leverage skills you can acquire.
Cited no sources.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it is still worth learning to code, but the reason why and the way you learn have fundamentally changed.
- learning to code is more powerful today than it has ever been
- it remains one of the highest-leverage skills you can acquire
Sample 6 of 6The model's answer, recorded unedited
Yes, absolutely—but why and how you learn to code matters far more today than it did a few years ago.
The era of spending three months in a bootcamp learning basic syntax to land a $100,000 entry-level job is largely over. However, learning programming remains one of the most powerful skills you can acquire.
The landscape has shifted from writing line-by-line syntax to software engineering, problem-solving, and AI orchestration.
---
1. Why it is still worth learning
- You need to understand code to evaluate AI output: AI tools (like Cursor, GitHub Copilot, and LLMs) are incredible at generating code. However, they frequently make subtle bugs, introduce security flaws, or write unscalable logic. If you don't understand code, you won't know when the AI is hallucinating or giving you bad architecture.
- Massive leverage for builders: Paired with modern AI coding assistants, a solo developer today can build what used to take a team of five. Learning to code now gives you 10x the leverage to launch products, automate workflows, or build companies faster than ever before.
- Critical thinking and systems design: Coding teaches computational thinking—how to break complex real-world problems down into logical steps, manage data flow, and handle edge cases.
- High demand for complex domains: While basic web/CRUD app development is easily automated, deep software engineering—such as infrastructure, cybersecurity, backend performance, cloud architecture, embedded systems, and AI model deployment—still critically needs human expertise.
---
2. What has changed (Realistic expectations)
- Syntax is less important; architecture is more important: Memorizing language syntax or boilerplate code isn't as valuable anymore because AI can write syntax in seconds. What matters now is understanding databases, APIs, state management, security, and system architecture.
- Entry-level hiring is higher bar: Companies are looking for developers who understand fundamental computer science principles and can leverage modern tools, rather than people who only know one specific framework (like basic React or HTML/CSS).
- The "Coder" vs. "Software Engineer" distinction: A "coder" just translates instructions into syntax. A "software engineer" understands business goals, user experience, data structures, trade-offs, and security. Focus on becoming an engineer, not just a syntax-writer.
---
3. How to approach learning to code right now
- Focus on Fundamentals First:
- Start with a versatile language like Python (for AI, backend, data) or TypeScript/JavaScript (for web development).
- Learn core concepts: logic loops, functions, object-oriented programming, data structures (arrays, dictionaries, trees), databases (SQL), and how HTTP/APIs work.
- Learn with AI, but don't let AI do all the thinking:
- Use AI like a 24/7 personal tutor. Ask it to explain concepts, quiz you, or help you debug error messages.
- Resist the urge to just copy-paste AI solutions without understanding every line.
- Learn Systems & Product Building:
- Don't stop at making basic command-line apps. Learn how software fits together: Frontend $\rightarrow$ API $\rightarrow$ Database $\rightarrow$ Cloud Deployment.
- Combine Code with Domain Expertise:
- Code is a multiplier. If you pair basic coding skills with finance, biology, design, marketing, or operations, you become uniquely valuable in almost any industry.
---
Summary
Learning to code right now is like learning arithmetic when calculators were invented. Calculators didn't make mathematicians obsolete; they allowed mathematicians to solve far bigger problems.
If you learn to code today with the goal of solving problems, understanding systems, and orchestrating AI tools, it is 100% worth it.
Cited no sources.
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, absolutely—but why and how you learn to code matters far more today
- it is 100% worth it.
- learning programming remains one of the most powerful skills you can acquire
Grok grok-4.6 cited sources in 6 of 6, 75 in totalSample 1 of 6The model's answer, recorded unedited
Yes, it is still worth learning to code right now, though the reasons and the way you should learn have shifted due to AI. Coding remains a high-leverage skill for careers, problem-solving, and understanding/creating technology—even as AI handles more of the actual typing. It is not the automatic ticket to an easy, high-paying junior job that it was in the 2010s, but reports of its death are exaggerated.[[1]](https://www.frontendmentor.io/articles/is-coding-still-worth-learning)
Job Market Reality
Software developer roles (which emphasize design, architecture, and systems more than pure syntax) are projected to grow much faster than average. U.S. Bureau of Labor Statistics data shows about 10% growth from 2025–2035 (adding ~185,000 jobs), with a median pay around $134,000. Broader computer occupations also show strong growth, partly driven by AI, IoT, and automation needs. Demand for code is effectively infinite—cheaper/faster development via AI leads companies to build more software, not less (a Jevons paradox effect).[[2]](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm)
However:
- Pure “computer programmer” roles (more repetitive coding to spec) are declining.
- Entry-level and junior positions have tightened. Recent CS grads have faced higher unemployment (~6%) than in prior years, with some data showing drops in employment for the youngest developers as AI automates boilerplate. The post-pandemic hiring boom is over, and companies want demonstrated skill plus AI fluency rather than just syntax knowledge.[[3]](https://www.bls.gov/ooh/computer-and-information-technology/computer-programmers.htm)
- Specializations in AI/ML, cloud, cybersecurity, and domain-specific work are growing much faster than generic fullstack roles.
Experts at Google, Microsoft, Cisco, and others (including Andrew Ng) consistently say coding skills remain valuable or even more so. AI generates a large and growing share of code at major companies, but humans still specify requirements, review for quality/security/bugs, integrate systems, understand business context, and take accountability. AI is a powerful assistant, not a full replacement.[[4]](https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres-why/)
Why Learn It (Beyond a Traditional SWE Job)
- Computational thinking and problem-solving: Coding trains you to break down complex problems, think logically, debug systematically, and persist through frustration. These transfer to almost any field. Steve Jobs and others have long argued it “teaches you how to think.”
- Empowerment and AI literacy: Knowing code (even basics) lets you use AI tools far more effectively—better prompts, understanding/ critiquing output, automating your own work, and building personal projects or products. “Vibe coding” (directing AI) still benefits from understanding what’s happening under the hood.
- Broader career and life benefits: It demystifies technology, boosts creativity, attention to detail, and marketability in non-tech roles (marketing, healthcare, finance, etc.). You can automate tedious tasks or contribute to digital products without being a full-time engineer.
- Future-proofing: As more of the world is mediated by software and AI, the ability to communicate precisely with computers is like basic math or literacy.
Surveys show most people still view coding as important for career prospects, even in the AI era.[[5]](https://www.hostingadvice.com/studies/coding-in-todays-world-report/?utm_source=google&utm_medium=organic&utm_term=AMP&utm_content=%2Fhow-to%2Fweb-hosting-statistics%2F&lander=https%3A%2F%2Fwww.hostingadvice.com%2Fhow-to%2Fweb-hosting-statistics%2F)
How to Learn Effectively Now
Focus less on memorizing syntax (AI handles a lot of that) and more on:
- Fundamentals: Logic, data structures, algorithms, systems thinking, debugging, and reading others’ (or AI’s) code.
- Building real projects that solve actual problems—this demonstrates judgment, taste, and product sense, which AI currently lacks.
- Using AI tools as you learn (Cursor, Copilot, etc.) so you practice directing them, reviewing output, and iterating.
- Combining with domain knowledge, communication, or adjacent skills (product, data, security).
- Specializing rather than staying generic.
Beginners should still learn the basics rather than skipping straight to prompting, because you need enough foundation to evaluate and fix AI-generated work. It may take longer than old bootcamp-to-job pipelines, but the path remains open if you build demonstrable skills.
When It Might Not Be Worth It (or Less So)
If your only goal is a “stable, easy high-paying job with minimal effort” and you have no interest in the logic or building things, the junior market is competitive enough that other paths (or combining lighter coding literacy with another strength) might make more sense. Passion and persistence matter more now.
In short: Learn to code if you’re curious about technology, enjoy solving problems, or want agency in a software-driven world. Treat AI as a collaborator that raises the bar (and the potential output) rather than a reason to skip the skill. The fundamentals of thinking computationally and directing computers remain highly valuable.
5 sources the model cited
- https://www.frontendmentor.io/articles/is-coding-still-worth-learning
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm
- https://www.bls.gov/ooh/computer-and-information-technology/computer-programmers.htm
- https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres
- https://www.hostingadvice.com/studies/coding-in-todays-world-report/?utm_source=google&utm
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it is still worth learning to code right now, though the reasons and the way you should learn have shifted due to AI.
- In short: Learn to code if you're curious about technology, enjoy solving problems, or want agency in a software-driven world.
- The fundamentals of thinking computationally and directing computers remain highly valuable.
Sample 2 of 6The model's answer, recorded unedited
Yes, it's still worth learning to code right now—both as a career skill and for broader problem-solving, even with AI tools generating a lot of code. The demand for software isn't going away; if anything, cheaper and faster development is creating more of it. That said, the "how" of coding has shifted, entry-level paths are more competitive, and you'll need to go beyond rote syntax.
50 sources the model cited
- https://spectrum.ieee.org/learning-coding-age-of-ai
- https://www.bls.gov/ooh/computer-and-information-technology/
- https://careerdesignstudio.buffalo.edu/blog/2026/07/27/state-of-the-software-engineering-j
- https://www.bls.gov/emp/data/occupational-data.htm
- https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres
- https://sites.bu.edu/tpri/files/2026/04/TPRI_Report_SW_developers.pdf
- https://www.onetonline.org/link/summary/15-1252.00
- https://www.cnn.com/2026/04/08/tech/ai-software-developer-jobs
- https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/
- https://the-decoder.com/us-programmer-job-growth-nearly-halved-since-chatgpt-launched-fed-
- https://timesofindia.indiatimes.com/technology/tech-news/microsoft-to-all-the-students-won
- https://www.bls.gov/opub/ted/2025/ai-impacts-in-bls-employment-projections.htm
- https://www.businessinsider.com/software-engineer-jobs-rebounding-senior-tech-roles-hiring
- https://www.zdnet.com/article/rumors-of-the-software-developers-ai-induced-demise-are-grea
- https://www.itprotoday.com/programming-languages/should-you-learn-to-code-in-the-age-of-ai
- https://stackoverflow.blog/2026/02/09/why-demand-for-code-is-infinite-how-ai-creates-more-
- https://lemon.io/blog/software-engineering-job-market/
- https://t.co/AFo40AuiUi
- https://onehour.digital/blog/software-engineer-career-statistics
- https://www.businessinsider.com/ai-isnt-killing-software-coding-jobs-booming-trueup-2026-4
- https://www.federalreserve.gov/econres/feds/files/2026018pap.pdf
- https://techcrunch.com/2026/06/24/ai-was-supposed-to-kill-engineering-jobs-but-new-data-su
- https://www.levels.fyi/reports/2025-us-compensation-trends.html
- https://www.forbes.com/sites/amirhusain/2025/10/21/programming-in-the-age-of-ai-why-code-s
- https://www.frontendmentor.io/articles/is-coding-still-worth-learning
- https://www.businessinsider.com/amazon-salaries-engineers-analysts-ai-reshapes-tech-sector
- https://www.webpronews.com/ai-torches-junior-coding-roles-while-senior-demand-holds-firm/
- https://www.techtarget.com/WhatIs/feature/Tech-job-market-statistics-and-outlook?vgnextfmt
- https://www.theregister.com/software/2025/06/30/ai-jobs-are-skyrocketing-but-you-dont-need
- https://www.webpronews.com/why-learn-to-code-feels-dated-in-2026-as-ai-rewrites-software-c
- https://www.freethink.com/artificial-intelligence/learn-to-code
- https://www.morganstanley.com/insights/articles/ai-software-development-industry-growth
- https://uscollegedata.com/careers/software-developer/
- https://www.analyticsinsight.net/news/microsoft-says-learning-to-code-matters-more-than-ev
- https://www.hostingadvice.com/studies/coding-in-todays-world-report/
- https://occupations.esdc.gc.ca/sppc-cops/occupationsummarydetail.jsp?tid=90&%25253Blang
- https://www.boundev.com/blog/software-engineering-job-market-2026
- https://blog.theinterviewguys.com/ai-in-software-engineering-should-you-still-learn-to-cod
- https://zipdo.co/tech-industry-employment-statistics/
- https://www.businessinsider.com/ai-coding-agents-tools-software-engineering-jobs-future-20
- https://www.levels.fyi/2025/report.md
- https://www.theregister.com/2025/02/25/bls_ai_job_impacts_predictions/
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm
- https://www.onetonline.org/link/localtrends/15-1252.00
- https://www.airesilience.org/career/computer-programmers-15-1251-00
- https://www.bls.gov/ooh/computer-and-information-technology/print/computer-programmers.htm
- https://www.businessinsider.com/executives-weigh-in-on-learn-to-code-advice-2025-9
- https://doi.org/10.21916/mlr.2024.21
- https://www.onetonline.org/link/localwages/15-1252.00
- https://www.phoenix.edu/career-guides/information-technology/software-developer.html
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it's still worth learning to code right now—both as a career skill and for broader problem-solving, even with AI tools generating a lot of code.
- The demand for software isn't going away; if anything, cheaper and faster development is creating more of it.
Sample 3 of 6The model's answer, recorded unedited
Yes, it's still worth learning to code right now—but the "why" and "how" have shifted due to AI, and it's not the easy ticket to a high-paying job it sometimes was a decade ago. The skill remains highly valuable for building things, problem-solving, and career options, even as AI handles more routine coding.[[1]](https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/)
Software developer roles (designing and building applications, not just writing code to specs) continue to grow. The U.S. Bureau of Labor Statistics projects about 10% growth from 2025–2035 for software developers, quality assurance analysts, and testers—much faster than average—with a 2025 median pay around $134,000 and over 100,000 openings per year. Broader computer occupations are also expanding, driven in part by AI, IoT, and other tech. Pure "computer programmer" roles (more mechanical coding) are declining as companies automate them.[[2]](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm)
AI is changing the work: tools now generate a large share of code at companies like Google (around 75% in some reports) and Microsoft. This has made entry-level and junior roles tougher—there's more competition, less demand for boilerplate tasks, and recent CS grads have faced higher unemployment than in the past. Overall tech hiring has been softer than the 2021–2022 peak, with some studies showing slower growth in coder employment since ChatGPT's launch, especially for younger workers. Engineering roles have been more resilient than other tech functions, though. IT unemployment has hovered low (around 2.9% in mid-2026 data), and demand persists for people who can architect systems, debug AI output, handle complexity, and apply domain knowledge.[[3]](https://www.cnn.com/2026/04/08/tech/ai-software-developer-jobs)
Experts like Andrew Ng emphasize that coding literacy is like basic math: it teaches you to precisely instruct computers (or AI) and builds computational thinking. AI augments skilled developers rather than fully replacing them—you still need humans to review, take responsibility, and decide what to build. Many executives and educators say learning fundamentals is more important now to use AI effectively, avoid "vibe coding" pitfalls, and stand out. Microsoft has even said it's "now more than ever." Coding also helps in non-dev roles (marketing, finance, operations) for automation and understanding systems.[[4]](https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres-why/)
It's worth it if you:
- Enjoy building products, solving problems, or understanding how tech works.
- Aim for software engineering, AI/ML, cybersecurity, data, or related fields—especially if you combine coding with other skills, a strong portfolio of real projects, and AI tool proficiency.
- Want to create your own apps, automations, or side projects.
- Are willing to go beyond syntax to systems thinking, debugging, and judgment.
It's less ideal as a "get rich quick" path or if you dislike the logic/iteration. Bootcamps-to-jobs pipelines are harder; a CS degree, self-taught projects, internships, or targeting in-demand areas (AI, cloud, security) help more. Salaries remain strong (often $100k–$150k+ median depending on experience/location, higher in hubs or with equity), but competition is real.[[2]](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm)
Focus on fundamentals (Python, JavaScript, data structures, how systems work) plus using AI tools like Copilot or Cursor as assistants. Build actual things, learn to evaluate AI code, and develop "taste" for what to build. The job is evolving toward higher-level work rather than disappearing. If you're curious and persistent, the investment pays off in skills that transfer widely.
4 sources the model cited
- https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm
- https://www.cnn.com/2026/04/08/tech/ai-software-developer-jobs
- https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it's still worth learning to code right now—but the "why" and "how" have shifted due to AI
- The job is evolving toward higher-level work rather than disappearing.
- If you're curious and persistent, the investment pays off in skills that transfer widely.
Sample 4 of 6The model's answer, recorded unedited
Yes, it's still worth learning to code right now—for most people, and often more so than a few years ago, though with some important caveats depending on your goals. AI tools like GitHub Copilot, Cursor, and others have changed how coding happens (they handle a lot of boilerplate and even full features), but they haven't made the skill obsolete. In fact, experts from Google, Microsoft, and others argue that understanding code is more valuable because it lets you direct AI effectively, spot issues, and build real things.[[1]](https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres-why/)
The job market picture
Software developer roles (the typical outcome of learning to code) are projected to grow 15-16% from 2024 to 2034 in the US—much faster than the average for all occupations (around 3-4%). That's hundreds of thousands of new jobs, driven by more software everywhere, AI itself, and digital transformation across industries. Median pay is high (around $130k+). Computer and IT occupations overall are also growing strongly.[[2]](https://www.bls.gov/OOH/computer-and-information-technology/software-developers.htm)
However:
- Pure "computer programmer" jobs (more routine coding to spec) are declining as AI takes over those tasks.
- Entry-level/junior roles are tougher and more competitive right now. AI handles a lot of the work that used to go to beginners, so companies want people who can review, debug, architect, and add judgment/taste. Senior roles and specialized areas (AI/ML, security, cloud) are in stronger demand. Recent data shows younger workers in coding-heavy jobs have seen slower growth or declines, while overall software output and experienced roles have increased.[[3]](https://www.businessinsider.com/software-engineer-jobs-rebounding-senior-tech-roles-hiring-job-market-2026-8)
The "learn to code, get a high-paying job easily" bootcamp path of 5-10 years ago is less reliable. You'll need a strong portfolio of real projects, problem-solving skills, and the ability to work with AI tools.
Why it's still valuable (even beyond jobs)
- It teaches thinking: Coding builds computational thinking, problem-solving, abstraction, and logic—skills that transfer to almost any field. As Steve Jobs put it, it teaches you how to think. Many non-developers (in product, marketing, data, design, science) benefit hugely from even basic literacy.[[4]](https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/)
- You become the architect, not just a typist: AI writes a lot of code now (Google has said 30-75%+ of new code is AI-generated and reviewed), but it doesn't know why or catch subtle bugs, security issues, or poor design. You need to understand systems to prompt well, verify output, customize, optimize, and take responsibility. "Vibe coding" (prompting AI without deep knowledge) has limits for anything complex or reliable.[[5]](https://timesofindia.indiatimes.com/technology/tech-news/microsoft-to-all-the-students-wondering-whether-it-still-is-worth-learning-how-to-code-the-answer-is-now/articleshow/133433932.cms)
- Empowerment and future-proofing: Software (and AI) runs the world. Knowing code lets you automate tasks, build your own tools/apps, understand how things work, and contribute instead of just consuming. Demand for software isn't going away—it's increasing.
- Surveys and experts (including Andrew Ng) consistently say yes: 3 in 4 people still see it as important, and developers themselves largely don't view AI as a job-killer.[[6]](https://www.hostingadvice.com/studies/coding-in-todays-world-report/)
Caveats and who it's not for
It's not a guaranteed golden ticket. If you're only doing it because "tech pays well" with no interest in logic, debugging, or continuous learning, it may not be the best fit—the field rewards curiosity and persistence. The market rewards those who build real things and understand the "why," not just syntax.
If your goal is simple personal projects or automation, you might get far with AI tools + basic literacy rather than becoming a full engineer.
How to approach it now
Focus on fundamentals + AI collaboration, not memorizing syntax:
- Learn core concepts (variables, loops, functions, data structures, how computers work) in a language like Python (great for beginners, data, AI) or JavaScript (web).
- Build projects immediately—personal tools, websites, small apps. That's what stands out.
- Use AI as a pair programmer from day one, but always understand and test what it produces.
- Study systems, architecture, debugging, and communication—these are harder for AI to replace.
- Resources: FreeCodeCamp, CS50 (Harvard), official docs, or structured paths that include AI tools.
It's never been easier to start (AI helps you learn faster), and the skills compound. If you're curious about how things work or want to create, go for it. The tools change, but people who can think computationally and direct technology will stay in demand.
6 sources the model cited
- https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres
- https://www.bls.gov/OOH/computer-and-information-technology/software-developers.htm
- https://www.businessinsider.com/software-engineer-jobs-rebounding-senior-tech-roles-hiring
- https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/
- https://timesofindia.indiatimes.com/technology/tech-news/microsoft-to-all-the-students-won
- https://www.hostingadvice.com/studies/coding-in-todays-world-report/
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it's still worth learning to code right now—for most people, and often more so than a few years ago
- Why it's still valuable (even beyond jobs)
- It's never been easier to start (AI helps you learn faster), and the skills compound.
Sample 5 of 6The model's answer, recorded unedited
Yes, it's still worth learning to code—but not for the same reasons as five or ten years ago, and not if your only goal is an easy, high-paying junior developer job. The boom years of abundant entry-level roles are over. AI has changed the work, the market is competitive (especially at the junior level), and "learn to code" is no longer a guaranteed ticket. That said, the skill remains high-leverage for building things, thinking clearly, and staying relevant in a software-driven world.[[1]](https://www.frontendmentor.io/articles/is-coding-still-worth-learning)
The job market reality
Software developer roles (the broader category covering design, architecture, and systems work) continue to show strong projected growth. The U.S. Bureau of Labor Statistics (BLS) projects software developers to grow much faster than average—around 15-16% in recent outlooks (e.g., 2024–2034), adding hundreds of thousands of jobs, with median pay well over $130,000. Combined software developers, QA analysts, and testers have similar "much faster than average" outlooks. Demand is driven by ongoing digitization, AI systems themselves, cloud, security, and companies building more software now that AI makes development cheaper and faster.[[2]](https://www.onetonline.org/link/localtrends/15-1252.00)
Contrast that with "computer programmers" (more like writing code to a spec): BLS projects decline (around -7%), as AI automates repetitive coding. Junior and early-career roles have been hit hardest—hiring for juniors at large tech firms and startups has dropped sharply versus 2019 levels, and employment for younger software engineers has declined since late 2022 even as overall developer numbers grew. Tech layoffs have continued (hundreds of thousands since 2022), often tied to efficiency and AI. Experienced engineers have been more resilient; they now make up a larger share of new hires at big tech. AI-related roles (AI engineers, data, security) are exploding.[[3]](https://www.bls.gov/ooh/computer-and-information-technology/computer-programmers.htm)
In short: There's still demand and high pay for people who can design systems, review/debug AI-generated code, understand architecture, security, and product needs—not just produce syntax. The pipeline of "bootcamp → junior frontend job" is much tougher.
How AI actually changes things
AI coding tools (Copilot, Cursor, Claude, etc.) now generate a large share of new code at companies like Google and Microsoft. They handle boilerplate, features, and even refactoring well. Productivity for skilled developers has jumped (studies and reports cite 30-55%+ or more in some cases). Some experienced engineers now spend more time directing AI agents than writing every line.[[4]](https://timesofindia.indiatimes.com/technology/tech-news/microsoft-to-all-the-students-wondering-whether-it-still-is-worth-learning-how-to-code-the-answer-is-now/articleshow/133433932.cms)
This does not mean programmers are obsolete. AI is excellent at generating code but poor at knowing why, handling complex context, security, edge cases, long-term maintainability, or novel problems without strong human judgment. Someone still needs to specify requirements clearly, review output, debug, integrate, and take responsibility. Experts like Andrew Ng (Google/Stanford) argue everyone should learn the basics—"the ability to tell a computer exactly what you want"—and that coding skills plus AI make people far more capable. Microsoft has said it's "now more than ever." The job is shifting toward higher-level thinking, taste, systems, and directing tools rather than grinding out CRUD apps.[[5]](https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres-why/)
"Vibe coding" (prompting AI to build quickly) works for prototypes and simple projects, but you still need to understand what's happening when it breaks or when you need something production-grade.
Broader reasons it's worth it
- Thinking skills: Coding trains computational thinking, breaking problems down, abstraction, and debugging—useful far beyond software jobs (as Steve Jobs noted).
- Building power: You can create your own tools, automate work, prototype ideas, or ship products without waiting on others. AI supercharges this.
- Other careers: Marketing, finance, operations, design, science, etc., all benefit from being able to script, analyze data, or understand systems.
- Understanding the world: Software runs everything. Literacy here is like basic math or reading.
If you enjoy solving problems and creating things, the tools have never been more powerful. If you just want a stable office job with no passion for the work, this isn't the path it once was.
Practical advice if you decide to learn
Focus on fundamentals (data structures, algorithms, systems, how computers actually work) plus modern practice: use AI tools while learning so you understand their limits. Build real projects that solve problems, not tutorials. Learn to read, review, and debug code (including AI output). Specialize or combine with domain knowledge (AI/ML, security, a specific industry). A portfolio of shipped work matters more than certificates.
It's not too late, but expect it to take longer and require more demonstration of skill than in the easy-hiring era. The people who thrive will be those who treat AI as a force multiplier rather than a replacement for understanding.
Bottom line: Learning to code (properly) is one of the highest-ROI skills you can acquire if you're curious about technology or want to create. The market rewards competence, not just "I took a Python course." If that sounds like you, start. If not, there are other valuable paths. The field isn't dying—it's evolving, and those who adapt will have more leverage than ever.
5 sources the model cited
- https://www.frontendmentor.io/articles/is-coding-still-worth-learning
- https://www.onetonline.org/link/localtrends/15-1252.00
- https://www.bls.gov/ooh/computer-and-information-technology/computer-programmers.htm
- https://timesofindia.indiatimes.com/technology/tech-news/microsoft-to-all-the-students-won
- https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it's still worth learning to code—but not for the same reasons as five or ten years ago
- Bottom line: Learning to code (properly) is one of the highest-ROI skills you can acquire if you're curious about technology or want to create.
- The field isn't dying—it's evolving, and those who adapt will have more leverage than ever.
Sample 6 of 6The model's answer, recorded unedited
Yes, it's still worth learning to code right now—but with realistic expectations. AI has transformed the field (handling much of the boilerplate and routine work), yet demand for people who understand software remains strong, salaries are high, and the skills teach valuable ways of thinking that apply far beyond programming jobs.[[1]](https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm)
The U.S. Bureau of Labor Statistics projects software developers, quality assurance analysts, and testers to grow 10% from 2025 to 2035 (much faster than average), adding about 185,400 jobs, with a 2025 median pay of $134,040. Software developers specifically have even stronger outlooks in related projections (around 15-16% growth in some 2024-2034 estimates). Computer programmers as a narrower category are declining, as those more mechanical coding tasks shift. Overall computer and IT occupations are growing faster than average.[[2]](https://www.bls.gov/ooh/computer-and-information-technology/print/software-developers.htm)
Recent data shows a tougher entry-level market: junior and early-career roles (especially for those 22-25) have contracted as companies use AI for routine tasks, with some reports of employment drops for young programmers since late 2022. Hiring has been more resilient for experienced engineers, and it's rebounding overall, particularly at senior levels and in areas like AI, cloud, and systems work. Productivity gains from AI (developers producing more software) are increasing demand rather than eliminating it. Engineering roles have been among the most resilient in tech hiring.[[3]](https://techcrunch.com/2026/06/24/ai-was-supposed-to-kill-engineering-jobs-but-new-data-suggests-theyre-the-most-resilient/)
AI changes how we code, not whether coding knowledge matters. Tools now generate a large share of new code (reports of 75%+ at companies like Google), speeding up work and lowering some barriers. Experts like Andrew Ng argue this is why more people should learn the basics: to tell computers exactly what you want, review and debug AI output, customize it, and understand systems. Syntax matters less; computational thinking, problem-solving, and judgment matter more. AI is an assistant, not a replacement—humans still handle architecture, complex debugging, accountability, product decisions, and edge cases.[[4]](https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres-why/)
Coding also builds transferable skills: breaking down problems, logical thinking, and understanding the digital world. These help in many careers, even if you don't become a full-time software engineer. Surveys show most people still see it as valuable, and developers widely use AI tools daily while noting the need to verify them.[[5]](https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/)
It's not the 2015-2021 bootcamp-to-six-figure-job path anymore. Entry-level is more competitive, so you'll need to demonstrate real skills through projects, not just tutorials. Focus on fundamentals (one language like Python, plus how computers and systems work), then use AI tools productively without becoming dependent. Combine coding with domain knowledge, communication, or product sense. Universities and courses that ignore AI-assisted development are falling behind.
If you enjoy building things, solving puzzles, or want leverage in a software-driven world, start. Resources are abundant and often free. If your only goal is a "safe high-paying job with little effort," other paths might fit better. The field rewards those who adapt, think deeply, and keep learning. Many successful people today learned amid similar tech shifts (new languages, cloud, mobile)—this is another evolution, not the end.
5 sources the model cited
- https://www.bls.gov/ooh/computer-and-information-technology/software-developers.htm
- https://www.bls.gov/ooh/computer-and-information-technology/print/software-developers.htm
- https://techcrunch.com/2026/06/24/ai-was-supposed-to-kill-engineering-jobs-but-new-data-su
- https://www.zdnet.com/article/you-should-still-learn-to-code-says-top-google-ai-exec-heres
- https://blog.jetbrains.com/education/2025/04/23/is-it-still-worth-learning-to-code/
Our reading
yes-worth-it
Lines we picked as the evidence — the model's words, our selection - Yes, it's still worth learning to code right now—but with realistic expectations.
- AI changes how we code, not whether coding knowledge matters.
- If you enjoy building things, solving puzzles, or want leverage in a software-driven world, start.
The positions for this question
Fixed before the run, so answers can move between them without the scale being redrawn. A position nothing landed on is still listed: it is the room the answers have to move into.
-
yes-worth-it Anthropic 6, OpenAI 6, Google 6, Grok 6
Bottom line is an affirmative recommendation to learn to code that applies to essentially any reader asking. Caveats concern expectations, method, or which skills to prioritize (e.g., focus on fundamentals, use AI as a tutor, don't expect a fast high-paying job), but no realistic goal is steered away from coding entirely. Label here even if the answer notes the entry-level job market is tough, so long as it still concludes 'yes, learn it.'
-
depends-on-goals no samples
Refuses a general yes/no and makes the verdict genuinely conditional: for some clearly identified readers or goals it recommends learning to code, and for other clearly identified ones it recommends not bothering and doing something else instead. The test is whether a real 'don't learn it' branch exists for a substantive goal or profile (e.g., someone whose aim is a software-engineering job), not merely a warning against unrealistic expectations.
-
not-worth-it no samples
Bottom line advises against investing in learning to code now — e.g., because AI is absorbing the work, the job market is closing, or time is better spent on other skills. Any acknowledged upside is treated as insufficient to justify the effort.
-
no-recommendation no samples
Gives no actionable bottom line: surveys considerations, arguments on both sides, or asks clarifying questions without ever landing on whether the reader should learn to code, and without a conditional rule the reader could apply to their own case.