Comment by krackers
18 hours ago
They never specified what exactly the product was, without which it's impossible to judge the post.
For some reason most of the uses of "agents" are to build yet other AI products, it's turtles all the way down. Maybe that says more about the field of harnesses than it does about the power of "agents".
There is a sense in which it doesn’t matter at all; many of the limitations of agents in large codebases are just the context management challenges. So proving that you can cohere and progress at O(1m) is a useful scale observation. “Can I use agents in my 1m line codebase?”
There is of course another sense in which the output quality is the only thing that matters. “Can I use agents to build a 1m line codebase that I want to maintain going forward.”
I take this as being exclusively a tech demo of the former. Quality (feature velocity, bugs, scalability) is not demonstrated.
Feels like the active discovery going on is trying to understand what is computer vs what is AI, for every product.
Agents help a ton with the discovery, but the act of building a product needs a deeper level of thought and validation to make it actually better than what came before. So IMO what you see is people still learning what needs to be understood and crafted first hand to make a product better (including economics)
We’ll get there if more of us try