4,266 karma · joined August 13, 2011
I have my own skill: 5 rounds of research/planning/test-planning. Interactive with me in loop for all important decisions. Starts with high level shape, then details. Planning can take 2-3 days of my time, then the implementation agent can take many hours (Opus 4.7). It splits the implementation across many phases/commits, each with its own code-review fix loop. Deep code review at the end can take another hour or two. It opens a PR, Gemini reviews, it reads out and resolves those issues.
Projects still take days or weeks, but 5x faster than doing it all myself.
Edit: the skill - https://github.com/scosman/vibe-crafting
We're not talking abstract language concepts, this is a specific case. The data was taken without license/rights/approval. It's stolen. AA calling it "our data" is disingenuous. Legally it isn't theirs. While you could use "ours"/"theirs" loosely in English, they knew it wasn't true in a legal sense when publishing this.
Hard to outperform the model you distill...
Same approach is useful for everything: model, params, prompt, sub-agents, skills, rag, etc?
Not all extra tokens help, but optimizing for minimal length when the model was RL'd on task performance seems detrimental.
Often you can find these during design. Design phases felt like a waste of time when you could just start coding and find the issues as you go. Now I find it faster to do a detailed design, then hand it over to agents to code. You can front-load the hard decisions and document the plan.
Sometimes the agent might discover a real technical constraint during dev, but that's rare if the plan is detailed. If so you can always update the plan, and just restart the agent from scratch.
This is my (cheesily named) process: https://github.com/scosman/vibe-crafting