At AI Fund, we’ve watched AI automate increasing amounts of office work. We’ve discovered a shift in what makes people valuable: everyone needs to become more technical.
“Technical” doesn’t mean learning Python or understanding databases anymore. It means developing fluency with frontier AI. The barrier to entry has never been lower.
Across our portfolio companies, the people who thrive understand and use frontier AI. They know what LLMs can do. They understand context windows and hallucinations. They know mitigation techniques—grounding AI outputs, controlling error rates through frameworks and human-in-the-loop checkpoints.
The people staying relevant are overwhelmingly software engineers. Why? Engineers learn by building. They read papers, attend conferences, but most importantly—they build things.
This matters because the AI landscape is noisy. Some believe AI will achieve recursive self-improvement within months. Others dismiss LLMs as pattern matchers incapable of reasoning. You can’t know the truth without getting your hands dirty. Reading hot takes won’t give you intuition. Building will.
AI is alien intelligence with jagged capabilities—superhuman in some dimensions, weak in others. Developing intuition for these capabilities takes practice. You need to understand context windows, token generation, where models excel and fail. Using AI well is art, not science.
Start with AI-assisted coding tools. Install Cursor or Claude Code. Pick any project—automating a spreadsheet, building a web app. The project matters less than the building.
Create something that uses LLMs. A chatbot. A document summarizer. Get familiar with prompts, temperature settings, token limits. Learn what happens when you send text to an LLM. Understand tokenization, context windows, stateful versus stateless APIs. Skip the math, grasp the concepts.
When AI writes code for you, ask it to explain each part. Ask about alternatives. Treat it like a tireless teaching assistant.
This will feel uncomfortable. You’ll feel slow, clumsy. That’s learning.
The barrier to becoming technical has collapsed. You don’t need years learning programming languages or memorizing syntax. AI handles that. You need curiosity and persistence.
A product manager can prototype features without engineering resources. A salesperson can automate their funnel. An operations manager can create productivity tools.
Technical fluency is becoming table stakes. The marketing manager who can’t use AI for customer analysis will be outpaced. The financial analyst relying solely on Excel will fall behind. The HR leader who doesn’t understand AI screening tools will lose ground.
Success means augmenting human capabilities with alien intelligence while preserving judgment. Knowing when to leverage AI’s strengths and when to apply human insight.
If you’re entering the workforce now, you have an advantage: you’re starting fresh in an AI-native world. No pre-AI habits to unlearn. You can build the right intuitions from day one.
Start today. Open Claude or ChatGPT. Build something simple. A to-do list. A recipe organizer. Pay attention to where it excels and struggles. Build intuition through experience.
Young professionals who develop these skills early will shape the future of work. Companies need people who intuitively understand how to leverage alien intelligence.
Becoming technical is your competitive edge. It’s about time and attention. While others debate whether AI matters, you can be mastering it.