Lazar Jovanovic: observation

Transcript context

…Oh, my God. There's so much here. This is so awesome. Okay. So essentially, what's happening here is you start a project, try a bunch of stuff, pick a direction that feels most correct. And once you have a set direction, you spend essentially a day, not building, but working with this AI agent to plan. And then, and well, I want to talk about that. And once you have the plan, then it's ... And it's amazing that you could do stuff like this with what some people may feel are not sophisticated tools that can build incredibly powerful things. You can do a lot of this with tools like Lovable, like have plans and rules and MD files. A lot of people may not know that. And so the idea is, okay, spend all this time planning because again, that'll save you a lot of time down the road. And then only once you have a plan, you get it going. And a key part of this, this three-wishes rule is really important. The reason you're doing this in large part beyond just being really clear about the plan is this idea of one task at a time keeps the agent's context window small so that it doesn't lose track of where it's at. That part seems important. It's like, "Do this thing." And then, "Okay, cool. Now do the next thing." Right? Yes, yes, because again, let's say you didn't do this. Let's talk about you ignoring this and you're like, "I just want to vibe my way." Okay, great. No problem. You work, you work, you work. At one point, something breaks, right? You haven't documented anything. There's no reference points. You report a problem. You're not referencing files or architecture at all, you're just describing the issue. Here's what's going to happen. Any tool, Lovable or Cursor or Claude, whatever tool you talk about is going to do this. It's going to be like, "Okay, let me start investigating." And then your code base gets bigger and bigger and bigger and bigger and bigger. When you first start, you have 20 files. It can read 20 files. But what happens when you have ... I'm just building a project right now that has 60, 70 edge functions. What happens then when I say, "This broke and there's no reference which edge function does what?" Guess what? Lovable's going to read all of those and it's going to consume 80% of the token allocation on reading to get clarity, leaving only the final 20% for thinking and executing. What I'm guessing, and I can't prove this, an LLM expert in the comments may say that I'm wrong, but this is my best guess as a non-educated person. These tools are very obedient and very agreeable. They're going to lie to you. They're going to tell you that they fixed the problem, even though they didn't. They're just going to try to make you feel happy and say, "Yes, I found what the problem is and I fixed it," when a lot of times when they don't, people blame the machine. And to an extent, I will say that's true. It's your fault, my friend. You did not provide any clarity or context to this tool. You just used its raw power and dug a deeper hole with spinning your wheels into the mud. And obviously, I think we're heading into a world where AI is more honest than obedient in saying, "Hey, I only partially fixed this. You did not give me enough of a context." The bigger mistake that people make then is they trust the tool fixed it. They test, they see it didn't, then they get mad at it, start cursing and yelling, as we say, and then it gets even worse because guess what? Another bad trait of AI, is it does its best not to hurt your feelings and never say, "You're the dumb one." It says, "No, I'm the dumb one." So it focuses ... In the next request, instead of focusing on reading, it spends another 30% of tokens trying to come up with an apology. Again, I'm not educated, but if you ever read a stream of ChatGPT's thinking in thinking models, you see exactly what I mean. When I insult it, I see that the first message says, "Okay, the user is mad, so I need to think of ways how to reduce their anxiety or whatever." I'm like, "Oh man, I just fell for the worst trick in the book. I made it spend the most scarce resource, which is those tokens on thinking how it should address my anxiety versus focusing on the actual problem." h man, I just fell for the worst trick in the book. I made it spend the most scarce resource, which is those tokens on thinking how it should address my anxiety versus focusing on the actual problem." So my advice for people is, yes, vibe your way for fun and vibe your way while you're prototyping because that's the exploration part. I love that part. But when exploration is done, please, please, please use referencing, documentation. Use all the agent files that you can because that token allocation is so scarce. It's going to get expanded over time. Things are going to get cheaper, faster, but right now it's still so valuable and precious, you really need to make sure that they are allocated in the right direction.…

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