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points by visarga 9 hours ago | 0 comments
I think it is a good approach for this year, but it misses something important - how do you know the code still reflects your intention after steering for weeks and months, across many sessions? Messages flow in the session and zoom out of view, and across compactions/new sessions they get forgotten. To solve this, I log every user message in a chat log, and review it from time to time to distill the latest form of user intent.

Another kind of review not mentioned here or in Anthropic's article is the plan review. I generate the plan for some stretch of work, then have the plan (saved as a file) reviewed by one or more agents. This checks the plan against project constraints before executing it.

If we can solve testing then coding is almost fully automated. The only remaining problem was always trust, why should we trust that code? If you read it manually then it's like walking a motorcycle. If you don't, then you need some way to derisk it. There are many ideas flowing around about how to do this, the OP and Anthropic showed their takes. I think the approach is project specific though, no general method.

[–] zsoltkacsandi 8 hours ago
What I do is that each of my requirements are captured in a yaml file, with a unique id, with the exact sentence I wrote. Each must be covered/proven at least with one test, a linter checks whether the requirement is covered (test exists annotated with that id), and a test inventory generated from it. Usually I browse and review the test inventory first to see I get what I asked. It does not guarantee that the agent implemented everything correctly, but if I ask another agent to review it and point out the gaps, it produces very good results.
[–] skinfaxi 4 hours ago
Is each file just one sentence? Trying to get a better sense of how you implemented this.