AI & Your Tech Career

Created and maintained by Segun Akinyemi

This site is always available at aka.ms/nocap

A practical, continuously updated collection of resources on AI and its impact on tech careers. Answers to the questions I keep getting asked, plus the skills, tools, and courses to actually go do something about it. Built by a software engineer who uses AI every day at work and is tired of watching people panic.

Quitting programming as a career right now because of LLMs would be like quitting carpentry as a career thanks to the invention of the table saw.
Simon Willison, co-creator of Django
One of the most respected voices on AI-assisted software development. Read his blog.

Reality Check Industry Outlook What to Learn Where to Learn Tools Who to Follow What to Read Get Connected

Hello there! I'm Segun Akinyemi, a software engineer at a company you've probably heard of. This site exists because I got tired of watching people get misled into thinking they should quit computer science, give up on software engineering, and go sit in a hole while waiting for AI to destroy the world.

At work. At events. At conferences. On LinkedIn. In emails. Everywhere I go, people ask me the same thing about AI's impact on the software development industry. It never stops. Most of the time it's some version of "is your entire career field gone now because AI writes code?" That's like asking if mathematics disappeared when calculators were invented, or if accounting died when Excel came out. The tool changed. The work didn't go away. It never does. Coding manually is dead, but software engineering isn't.

Even before AI, people generally have never understood what software engineers actually do. It's always been a lot more than just writing code. The confusion these days is totally understandable if you only listen to hype peddling CEOs, journalists, and influencers who need clicks and investors. But if you listen to the technical practitioners, the people who actually build the stuff, it's a very different story.

I keep seeing students, job seekers, and new grads ask whether they should quit their whole life and move somewhere rural to become a farmer. Why? Because some money loving, non-technical, shareholder groveling CEO said AI is going to replace all white collar jobs. Or some AI CEO claiming software engineers will be replaced in months, the same guy who's been saying this for years while his company aggressively hires software engineers.

Those kinds of statements exist to convince investors that the billions being spent on data center build out is worth it. Never mind that many of their AI products flat out suck. It's insane. This site exists to combat AI hot take nonsense and thus calm anxieties. AI is making CEOs delusional, and they'll say anything to avoid looking like they're falling behind, even when they clearly don't understand what they're talking about. They're not leading. They're following each other off a cliff while dragging public perception with them.

I keep this site updated. Connect with me on LinkedIn.

Reality Check

Before you doom spiral about AI's impact on software development, read these. Short answers here, links to the longer essays if you want depth.

No. Coding as manual labor has been automated. Software engineering, the judgment, the systems thinking, the accountability, is becoming more valuable, not less. Companies building AI are still hiring engineers by the thousands. OpenAI, Anthropic, Google, Apple, Meta, Amazon, and Microsoft all have open engineering roles right now. If AI could do all the work, they wouldn't be hiring. Read my full take.

No. We don't have AGI. We don't have Jarvis. We don't have movie level AI. What we have is a text-generating non-deterministic probability engine that's incredible, but falls apart when you introduce sufficient complexity outside its training data, no matter how much context engineering you apply. These models predict the next token (word) in a sequence. They do not understand what they're saying. They're tools, not replacements for thinking. Read more.

Yes. Anyone telling you not to is wrong. People far smarter than me have said as much. AI tools amplify existing expertise. They make you faster if you know what you're doing. If you don't know what you're doing, AI just makes you faster at being wrong. A technical foundation is what separates someone who can use AI effectively from someone who copies and pastes and prays. Read more.

No. People have been predicting developers would be replaced since COBOL came out in the 1960s. This is a great graphic depicting that history. Every decade, new tools arrive, the "no more developers" dream persists, and then reality sets in. The complexity of software is intellectual, not mechanical. No tool has ever eliminated the need for humans who think clearly about hard problems. As Simon Willison, co-creator of Django, put it: "Quitting programming as a career right now because of LLMs would be like quitting carpentry as a career thanks to the invention of the table saw." Read the history.

Yes. AI can generate code, but your job is to deliver code you have proven to work. That requires understanding what the code does, catching when the AI is confidently wrong, and knowing how to debug it when things break. And things always break. AI amplifies existing expertise. The more you know, the more productive it makes you. The less you know, the more dangerous it makes you. Read more.

CEOs say things that make investors want to give them money. That's literally their job. Follow the actions, not the words. OpenAI, Anthropic, Google, Apple, Meta, Amazon, and Microsoft are aggressively hiring engineers right now. If their own AI could do all the work, they'd save the billions they're spending on salaries. They can't, so they're hiring.

Mostly no. The layoffs you're seeing aren't because AI did those people's jobs. They're because AI is ridiculously expensive to run. Companies need to free up cash for data centers, GPUs, and compute infrastructure, so they're cutting headcount to fund the build out. Tech giants like Google, Amazon, Meta, and Microsoft are cutting to fund GPU purchases, not because AI replaced those workers. Their revenues are growing. Their stock prices are climbing. They're firing people to reallocate money from payroll to compute. You can track tech layoffs here.

As Harvard Business Review put it, companies are laying off workers because of AI's potential, not its performance. Some CEOs are just using AI as a convenient excuse for cost-cutting. Case in point: Block (Jack Dorsey's company, he also founded Twitter) cut nearly half its workforce and blamed AI, but current employees told The Guardian that 95% of AI-generated code still needs human fixes and the real motive was posturing for investors. Even Sam Altman, CEO of OpenAI (creators of ChatGPT), admitted that some companies are "AI washing" their layoffs. Matheus Lima said it best:

Will some companies use AI as an excuse to cut headcount? Absolutely. Some already have. There will be layoffs blamed on 'AI efficiency gains' that are really just cost-cutting dressed up as something else.
Matheus Lima, AI Can Write Your Code. It Can't Do Your Job.

Don't let headlines scare you out of a career.

What to Learn

Not just what matters, but exactly where to go learn it. Every area listed below is still relevant in the age of AI coding. Every resource below is free. These are listed in a rough progression, start at the top and work your way down.

At some point in school, everyone got to use a calculator. Yet, some kids still failed the test. If you don't understand the material, a calculator won't save you. You won't even know what to type in. AI in software development works the same way. You can vibe code your way to something that works, but without real understanding, you'll never build anything that lasts. Employers don't pay for vibes. If you want to get paid, learn the fundamentals.
Segun Akinyemi, creator of this site. Shameless self-quote.

The foundation everything else builds on. Programming, algorithms, how computers work. If you skip this, you can vibe code all day, but you won't be able to pass a technical interview to get a real software engineering job. There are no shortcuts to mastery.

Take these Harvard CS50 courses and you are set. Seriously. They are free, world class, and they will give you the knowledge you actually need. Everything else on this page becomes 10x more useful once you have these basics down.

CS50: Introduction to Computer Science The starting point. The most famous CS course in the world.
CS50: Introduction to Programming with Python Python is the language of AI. Start here if you want to code.
CS50: Introduction to Databases with SQL Data is everything. This teaches you how it's stored and queried.
CS50: Web Programming with Python and JavaScript How the internet actually works, and how to build for it.
CS50: Introduction to Artificial Intelligence with Python Optional. Gets into machine learning territory, which is a different discipline from software engineering. Worth exploring if you're curious, but not required to be a productive developer.

Also check out The Missing Semester from MIT, which covers the practical tools (shell, Git, debugging, dev environments) that CS programs skip. It was updated in 2026 with AI tools now folded into every lecture.

Been coding in Python with the help of LLMs. That would have been impossible without the grounding that CS50 gave me.
u/extopico, a CS50 student who came back two years later to confirm the fundamentals paid off.

How you track changes to code and collaborate with others. With AI writing code for you, version control has never been more important. You need branches, you need backups, you need to stop AI from blowing away your codebase.

The moment you're on a team with other developers, if you don't understand Git, you cannot function. Merge conflicts, rebasing, cherry-picking. You don't have to memorize terminal commands. GUI tools like the one built into VS Code work great. But you have to understand what's happening under the hood.

Pro Git Book The official Git documentation. Free, thorough, and the definitive resource for understanding version control from the ground up.
GitHub Skills Gold mine. Every tutorial on this page is worth doing. This is what turned things around for me in college.
Learn Git Branching Interactive, visual, and the best way to actually understand branching, merging, and rebasing.

How data is stored, organized, and retrieved. AI has not made database knowledge obsolete. It has made it more important. AI retrieval systems (RAG, vector search, agentic queries) all depend on well-designed databases. SQL is everything.

SQLBolt Interactive SQL lessons. Start here.
SQL Murder Mystery Learn SQL by solving a murder. Seriously. It's fun.
SQL Zoo Practice with real queries across progressively harder exercises.
FreeCodeCamp Relational Database Certification Hands-on with PostgreSQL and Bash. Covers database design, normalization, and administration. Goes beyond just SQL syntax.

Application Program Interface. How software systems talk to each other. An MCP server is only as good as the API behind it. Without APIs, AI literally cannot do any of the agentic stuff people want. Good API design is critical for efficiency, cost, and preventing AI from touching what it shouldn't.

APIs for Beginners FreeCodeCamp. Clear, practical, beginner-friendly.
Public APIs List Hundreds of free APIs. Pick one, fire up your AI coding tool, and build something with it.

How you know your code actually works. This is exponentially more important now that AI writes code. "I told AI to make the button blue and I see it's blue" is not testing. Real software has thousands of invisible behaviors that break silently. You need automated tests to catch them.

Software Testing Guide Martin Fowler. A legend in software engineering. Read this to understand why testing matters.
Software Testing Fundamentals Practical overview of testing types and strategies.

Continuous Integration, Continuous Deployment. Automating the process of testing and shipping code. The easiest way to get started is GitHub Actions. At work you'll use whatever your company has (Azure Pipelines, Bitbucket Pipelines, Bamboo, Terraform, Jenkins, whatever), but GitHub Actions lets you practice right now without needing an enterprise job.

What is CI/CD? Clear conceptual explanation.
GitHub Actions The official docs. Start automating your projects today.

Choosing architecture and components to meet a goal under constraints: reliability, security, cost, performance, maintainability. This includes understanding how computers communicate over the internet. Networking, DNS, HTTP, load balancing. None of that went away because of AI. It still matters, no be small.

System Design for Beginners FreeCodeCamp. Start here if the topic is new to you.
The System Design Primer The gold mine. Used by thousands to prepare for interviews and understand real-world architecture.
Networking Basics Cisco Networking Academy. Free course on how computers communicate over the internet.
Fundamentals of Computer Networking Microsoft Learn. Free, self-paced, covers the core networking concepts.

"There is no cloud. It's just someone else's computer." AWS (Amazon Web Services), Azure (Microsoft's cloud), and GCP (Google Cloud Platform) are the big three. Each has hundreds of products, each complex enough to build a career around. There is no such thing as "knowing" a cloud platform. It's a continual learning process. Start with the fundamentals certificate for whichever one interests you. If you're unsure, go with AWS. It was the first major cloud provider, it's the biggest, and the skills you learn there transfer to Azure and GCP.

AWS Certified Cloud Practitioner Amazon's entry-level cloud certification path.
Azure Fundamentals Microsoft's entry-level cloud certification path.
Google Cloud Fundamentals Google's entry-level cloud certification path.

AI Engineering is the evolution of software engineering. You're not building the models. You're taking them and building with them. RAG, MCP, vector databases, embeddings, context engineering, model evaluation. This is the capstone. Everything above feeds into it.

AI Engineer Roadmap By Priyanka Vergadia. The best step-by-step breakdown of what to learn and what mistakes to avoid.
HuggingFace Courses Free courses on NLP, agents, MCP, and more from the GitHub of AI models.
My AI Engineering GitHub List A curated list of tutorials, courses, and repos I keep updated for learning AI Engineering.
GitHub Copilot: Video Tutorials, Written Tutorials, Community Learning Hub Three different ways to learn Copilot. Videos if you prefer watching, docs if you prefer reading, and hands-on recipes if you prefer doing.
Claude Code in Action Free course from Anthropic. Lessons covering setup, context management, custom commands, MCP servers, and GitHub integration.
Codex for Builders OpenAI Academy. Covers what Codex is, how to use it across CLI, IDE, and web, plus hands-on workshops from 101 to 103.

Use AI as your tutor. Open ChatGPT, Claude, Gemini, Microsoft Copilot, whatever chatbot you have access to. Ask it to explain a topic. When the explanation doesn't make sense, ask it to explain it differently. Keep going until it clicks. This is the single most underused learning strategy available to you right now, and it's free.

Where to Learn

General purpose learning platforms and free student perks beyond the specific resources listed above.

Microsoft Learn Free training across every Microsoft product and career path.
Google Skills Google's free learning platform. Cloud, AI, data, and more.
AWS Skill Builder Amazon's free training platform for cloud and AI skills.
Anthropic Courses Learn about Claude, prompting, and building with their models.
FreeCodeCamp Free full-stack curriculum. Thousands of hours of content.
GitHub Skills Interactive tutorials on Git, GitHub, Actions, Copilot, and more. Gold mine.
Vercel Academy Free courses on web development, React, and Next.js from the company deeply integrated with both.
HuggingFace Learn Free courses on Natural Language Processing, AI Agents, Model, Context, Protocol, and more straight from the platform known as the GitHub of AI models.
Codecademy Student Center Discounted access to Codecademy's coding courses for students. Codeacademy is free but for premium features there's a charge, for students its cheaper.

Most big tech companies offer free credits, tools, and courses to students. Take advantage of all of them.

GitHub Student Developer Pack Free Copilot Pro, domain names, cloud credits, and more. The single best student perk in tech.
Azure for Students $100 in Azure credits, no credit card required.
Microsoft Student Certifications Free certification exams while you're a student.
OpenAI for Students Student community, resources, and access from OpenAI.
Google Cloud for Students Free cloud credits and learning resources.
Gemini for Students Free access to Google's AI tools for students.
AWS Free Tier Free access to core AWS services. Not student-specific, but free is free.