Comment by gregwebs

I saw your response before it was deleted- that you are doing multi agent persona reviews and a very intensive review process. So having fewer review items saves you money.

One thing that I have found is that as the frontier models get better there is less need for agents with specialized personas. I actually don't don't use those anymore- I just use agents that have different models and reasoning levels. I have a generated CODING_STANDARDS.md document and a skill for architecture design and a skill for implementing testing [2] that are referenced by a single reviewer. I do implement a 2-pass review though [3].

I would be interested to know if you have found anything similar as models get better. It seems though that you are sharing a single exploration and then sharing the context across the specialized reviewers to dramatically reduce the cost of your approach. Does this have to be in the harness- that is if you write out the shared context to a file does that increase your costs a lot?

I also wonder how intensively are the models able to test their changes? The number one quality improvement I have found is not review but having the model properly test its code. I have a skill that is helping [4], but I also have to spend time to establish a pattern of testing with tools beyond just unit tests. The testing takes significant effort, and this is again where the cost savings of DeepSeek shine.

  [1] https://github.com/mattpocock/skills/blob/main/skills/engineering/codebase-design/SKILL.md

  [2] https://github.com/gregwebs/skills-sdlc/blob/main/skills/verify/SKILL.md

  [3] https://github.com/mattpocock/skills/blob/main/skills/engineering/code-review/SKILL.md

  [4] https://github.com/gregwebs/skills-sdlc/blob/main/skills/verify/SKILL.md