The Importance of Coding for AI Founders
Every founder in generative AI, and most tech founders generally, should know how to code. Without this fundamental skill, you’re building on shaky ground. My journey from product leadership roles at Coinbase and Google to building AI company Ema from the ground up has shown me that those with coding experience consistently make better product decisions. The ability to understand what’s happening under the hood isn’t just useful — it’s essential for making informed strategic choices.
Why Coding Matters
When you can’t tinker with your technology directly, you’re operating at a disadvantage. You can’t understand what your team is creating if you can’t interact with it at a basic level. This isn’t about becoming the best engineer on your team; it’s about gaining insights that only come from hands-on experience. Even though a founder and CEO probably won’t spend much time in the weeds with a product, they have to know how the technical aspects work. Without coding knowledge, you’ll always be at a disadvantage.
How to Get Started with Coding
I practice what I preach by dedicating time to coding every weekend, often exploring new concepts or techniques I’m curious about. What surprises many non-technical founders is how accessible coding has become. Today’s tools have dramatically lowered the barrier to entry. AI coding assistants like GitHub Copilot and Claude can write substantial portions of code based on natural language instructions. No-code and low-code platforms provide visual interfaces for building applications, serving as excellent on-ramps for those intimidated by traditional programming.
Benefits of Coding for Founders
The most respected founders in our space aren’t just visionaries; they’re builders who understand their technology from the inside out. Not every founder starts as an engineer, but you should be able to prototype ideas, understand technical discussions, and evaluate engineering trade-offs firsthand. Knowing the basics of AI infrastructure helps you make informed decisions about your product’s technical direction. For instance, if your team proposes using a closed-source generative AI model for personalized recommendations, you can evaluate the trade-offs between speed to market and long-term scalability.
Conclusion
If you’re running an AI company but can’t code, start learning today. Begin with small projects that interest you, use AI assistants to accelerate your progress, and join communities where beginners are welcome. The investment will pay dividends in your ability to lead, make decisions, and ultimately build products that truly matter. Your company’s future may depend on it.
