Comment by rbehrends
1 day ago
This is a different argument from Karpathy's prompt-and-forget one.
I personally have had good success with using agents as virtual pair programmers following some simple rules for how to make that process productive, but that is a very, very different approach. One that recognizes that both humans and agents are prone to errors and attempts to mitigate the problem rather than expecting it will magically work out through the power of AI.
I think of it in generational terms. Opus 3 required me to prompt and edit, iterating over functions almost one at a time. Opus 4 started to show agentic capacity but it largely bloated code and still needed frequent course corrections. If it churned for more than 15-20 minutes you knew something was off.
Opus 5 takes that and changes the game. A simple prompt goes through research, design, verification, review and self-corrects constantly. Agentic workflows can run for days without stopping, without losing the thread or devolving into slop.
I can’t even imagine what Opus 6 is going to bring.
The biggest thing holding AI back is people. People can only change so fast and yet AI doesn’t care. It just keeps accelerating.
I am sorry, but current benchmarks do not bear out that claim. Yes, frontier models can fairly reliably one-shot standard CRUD apps (and you don't even need frontier models for that), but when we're getting to harder problems, reliability nosedives when they're operating autonomously.