You Can Code 8x Faster With AI, But You Cannot Review 8x Faster

 First of all: I am not against AI. I use AI to work and I use AI to vibe code as a hobby. There is nothing wrong with using AI to write code, it can write better syntax than humans and it can write faster. My whole gripe with AI is the process of using it, which many people get wrong. I will elaborate and try to construct my train of thought step by step in this post, but in short: A human has to review 100% of the AI generated code and understand what it does and why. That is precisely why if you use AI to write code 8x faster you can't deliver code 8x faster, because you will need to read it all and investigate what, how and why, and that is what takes time. If you do not do it, you will lose track of your code base. If you are a programmer you know how much harder it is to work on a codebase you did not write and how smooth it is working on a codebase you wrote from scratch. If you don't review properly you will be in a perpetual state of "working in a new codebase" because the code base was not written, or better said, not reviewed, by you. # But do I know about AI?  Admitedly not so much as in I have never developed an AI model or created AI automation tools. I use it to code and I used it when I worked at Uber and I use it too now that I work at Pinterest. In both companies I did get training directly from frontier AI labs and we have access to almost all AI tools available. So I think that I can say that professionally I have contact and I use AI at a very high level. While admitedly I am not an AI developer I think I have earned the bragging rights to say that I am a developer who uses AI in projects that have global scale, managed by thousands of devs and reach millions of people, with billions of budget, in 2 publicly USA listed companies. Had to brag, I am sorry, couldn't hold it LOL. But now for the real post: # AI can write a lot very fast and the code can even work  AI can code absurdly faster, to the point that nowadays, with frontier models, you can ask for a full working app and it may get it right on the first try. The problem is that it will probably get it right but it will most likely be incomplete or have usability bugs or security vulnerabilities. Well, none of that is a problem, you can spend 100 hours running an AI to find and fix those problems, correct? No. # Context window and attention  The problem is multilayered. Context window is the first of the problems. I have read a nice Medium post that elaborates on the context window problem: https://medium.com/@tahirbalarabe2/understanding-llm-context-windows-tokens-attention-and-challenges-c98e140f174d But to try explaining it with my own words: The AI doesn't know your full codebase. The best AIs have 1 million tokens of context window. That is a lot, but the more context the worst attention it has. With worse attention comes worse code that fits poorly in the codebase or has issues. How do you prevent codebase issues form being pushed and merged into your code? You need to review the code the AI wrote. Well, if we automated the code writing, the code debugging and the security checks we surely can automate the reviewing process, right? No. # Reviewing and coding is the same for AI  When an AI reviews it does roughly the same processes it did when coding. As a tangent, you know what was one of the most signi […]