[scwoodal]

When I run into those situations I debug and try to understand why. Agent harnesses that allow you to rewind (/tree) are useful for this.

It’s often because the context is full, I gave a bad prompt or context has conflicting guidance either from direct or indirect (agents.md) prompts.

[soulofmischief]

It's easy to get these models to introspect and give quite detailed and intelligent responses about why the erred. And to work with them to create better instructions for future agents to follow. That doesn't solve the steering problem however if they still do not listen well to these instructions.

I spend 8-20 hours a day coding nonstop with agentic models and you can believe I have tuned my approach quite a lot. This isn't a case of inexperience or conflicting instructions, The RL which gives Opus its fantastic ability to just knock out features is the same RL which causes it to constantly accumulate tech debt through short-sighted decisions.