{"by":"lumbroso","descendants":20,"id":50227041,"kids":[50238389,50239860,50238662,50239680,50238406,50239684,50234205,50240190,50238388,50240327,50240130,50236119,50227047,50238980],"score":37,"text":"Why is this worth your time? Essentially, this solves two problems of AI-assisted programming:

(a) the first problem is how to do oversight and what do oversight of and this is solved through the ORRCF (for Options, Recommendation, Rationale, Confidence, Falsifier) question format (in which models are supposed to surface all their doubts with fully fleshed out recommendations, with falsifier, to be approved or overridden)

(b) the second problem is how to scaffold sustainable AI-written code; the ADRs (Architectural Deliberation Records, after Nygard's decision records) written by the models, summarize all the thought process involved in any design decision and provides the blueprint for the code.

In tandem, the records provide both the reason why certain non-obvious design choices were made, from a constant, to a library choice, to an ordering in an operation; and also under what conditions different decisions would be made, for instance, in a different platform, or under different latency requirements, or for a different audience, and so on.

This is a framework I've been working for over a year, that is the starting point of all my projects. It involves a lot of moving parts and my challenge is figuring out onboarding. I'm hoping the plugin, ADRs4AI/plugins, just created and now also submitted to Anthropic's marketplace, will make it easier. I am also in the process of recording introductory videos.

I would like feedback on the onboarding, on what you make of the currently online materials, and how I could make any of this clearer. Thanks!","time":1792889027,"title":"Show HN: ADRs for AI – Deliberation records for human–AI work, versioned in Git","type":"story","url":"https://adrs.systems"}