How AI Fund Is Building AI Builders AI-enabled coding empowers anyone build software that boosts productivity and makes life easier. Here’s now non-engineers at AI Fund are building apps for fun and profit.

Published
Reading time
2 min read
Robots building a wooden house frame under sunny sky. Teamwork, technology, and construction. Future automation in construction.
Loading the Elevenlabs Text to Speech AudioNative Player...

Dear friends,

Everyone can benefit by learning to code with AI! At AI Fund, the venture studio I lead, everyone — not just the engineers — can vibe code or use more sophisticated AI-assisted coding techniques. This empowers everyone to build with AI. The impact on team creativity and productivity has been exciting! I share my experience with this in the hope that more teams will invest in empowering everyone to build with AI.

Everyone at AI Fund who was not already an engineer started with our “AI Python for Beginners” course to learn the basics. I also shared with the team details of the tech stack I use to give everyone a default set of building blocks. Since then, many have gone on to acquire additional building blocks (such as additional third-party APIs) themselves either by taking courses, searching online, or learning from colleagues.

You can watch a video of our experience with this here.

Here are just a few examples of applications that non-engineers at AI Fund have built: 

  • Our CFO Ellen Li built an app that scans our Google docs system to flag updates to a portfolio company’s information, saving what was previously 5 to 6 hours of manual work per week.
  • Senior Executive Recruiter Jon Zemmelman built a system that lets him configure the relative ratings of screening criteria for job candidates (such as previous startup experience, technical expertise, etc.) and automatically evaluate resumes against the criteria.
  • Associate General Counsel Nikhil Sharma wrote code to automatically generate NDAs (non-disclosure agreements) in AI Fund’s standard template.
  • Office Coordinator Ellie Jenkins, as a fun project, built a visualization of the history of fashion design houses and their influence on each other.

It is very empowering when individuals don’t have to try to get scarce engineering resources allocated to their ideas in order to try them out. There are a lot fewer gatekeepers in the way: If someone has an idea, they can build a prototype and try it out. If it gets positive feedback from users, that lays the groundwork for scaling it up. Or, if the prototype does not work, this is also valuable information that lets them quickly move on to a different idea or take insights from critical feedback to decide what to try next.

In the future, one of the most important skills in any profession will be the ability to tell a computer exactly what you want, so the computer can do it for you. For the foreseeable future, writing code (with AI assistance, so the AI, rather than you, actually writes the code) will be the best way to do this.

This is a great time for everyone to code with AI!

Keep building,

Andrew 

Share

Subscribe to The Batch

Stay updated with weekly AI News and Insights delivered to your inbox