Thanks for the poem, the feedback and the interest.
Yes, I think to your point: I do review the decision records, and when I approve them, it's because they've articulated something fully that makes sense. My job as the human is to ensure that the record doesn't contain bullshit. It requires me to be epistemically discerning, it requires me to be able to discern bad/broken/fallacious reasoning from epistemic reasoning. That's what colloquially is called "critical thinking."
The kind of approval I do on records is different from the approval of a lot of permission dialogs in CLI harnesses, where you basically see the command-line is harmless, but you don't necessarily fully understand what is going on.
You're right that this has a cost, and the ORRCF (Options, Recommendation, Rationale, Confidence, Falsifier) question format was surgically, or perhaps more honestly "iteratively", designed to reduce the cognitive load on the human: It essentially asks the model to prefetch all the information I might need to even think about a decision, including what the right call is likely to be and why, to bring it all into view for me, for my human context window limits, so that in a few minutes I can load the context in my working memory and be forever satisfied once I'm done that this decision will never have to be made again. It will transfer to other use cases, and other projects. Sometimes the models get things incredibly right, both from their latent space or the rest of our records, and sometimes there's an opportunity to introduce more of my philosophy that will help ensure this deliberation is made correctly now and in the future.
My understanding of your implication is that this isn't worthwhile: But I guess that's where my experience is different. I know (a) how to program, and I know (b) how to justify decisions and evaluate recommendations and reasonings, and I find that exercizing (b) in the context of software building is a better value-add, because I have found to both compound faster and also to make better use of my cognitive abilities. Instead of implementing my idea, I'm being scaffolded into narrowing it down so it can be understand non-ambiguously by current (and future) models.
And to your question, this has absolutely helped me build a software factory. For instance, when Anthropic deprecated Sonnet 4.5 from their platform, I built a harness in Rust and TypeScript that I can host on free tiers and uses various meshes of APIs. Over the summer, every morning, I would get a demo of the features built overnight, with open question raised; I would answer those, specify new features, and go to other projects until the next morning.
Where you are right is that the ADRs4AI framework itself is not all of the components for this formula, it's just the epistemic continuity — the preservation of the "why?" behind everything. There are other components, like pneumatic, the cross-vendor inter-model communication, and the general philosophy behind how I work with agents (which is as extended minds, moreso than extended hands).
The poem made me laugh and I think it's very creative and thoughtful. Thank you for that again! I hope my comment is more genuinely stimulating.
Yes, I think to your point: I do review the decision records, and when I approve them, it's because they've articulated something fully that makes sense. My job as the human is to ensure that the record doesn't contain bullshit. It requires me to be epistemically discerning, it requires me to be able to discern bad/broken/fallacious reasoning from epistemic reasoning. That's what colloquially is called "critical thinking."
The kind of approval I do on records is different from the approval of a lot of permission dialogs in CLI harnesses, where you basically see the command-line is harmless, but you don't necessarily fully understand what is going on.
You're right that this has a cost, and the ORRCF (Options, Recommendation, Rationale, Confidence, Falsifier) question format was surgically, or perhaps more honestly "iteratively", designed to reduce the cognitive load on the human: It essentially asks the model to prefetch all the information I might need to even think about a decision, including what the right call is likely to be and why, to bring it all into view for me, for my human context window limits, so that in a few minutes I can load the context in my working memory and be forever satisfied once I'm done that this decision will never have to be made again. It will transfer to other use cases, and other projects. Sometimes the models get things incredibly right, both from their latent space or the rest of our records, and sometimes there's an opportunity to introduce more of my philosophy that will help ensure this deliberation is made correctly now and in the future.
My understanding of your implication is that this isn't worthwhile: But I guess that's where my experience is different. I know (a) how to program, and I know (b) how to justify decisions and evaluate recommendations and reasonings, and I find that exercizing (b) in the context of software building is a better value-add, because I have found to both compound faster and also to make better use of my cognitive abilities. Instead of implementing my idea, I'm being scaffolded into narrowing it down so it can be understand non-ambiguously by current (and future) models.
And to your question, this has absolutely helped me build a software factory. For instance, when Anthropic deprecated Sonnet 4.5 from their platform, I built a harness in Rust and TypeScript that I can host on free tiers and uses various meshes of APIs. Over the summer, every morning, I would get a demo of the features built overnight, with open question raised; I would answer those, specify new features, and go to other projects until the next morning.
Where you are right is that the ADRs4AI framework itself is not all of the components for this formula, it's just the epistemic continuity — the preservation of the "why?" behind everything. There are other components, like pneumatic, the cross-vendor inter-model communication, and the general philosophy behind how I work with agents (which is as extended minds, moreso than extended hands).
The poem made me laugh and I think it's very creative and thoughtful. Thank you for that again! I hope my comment is more genuinely stimulating.