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Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

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Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#41

Grindmaxxing, a long form blog post that is actually just an advertisement for his website.

Should I apologize for being excited about something I built and use daily and for wanting people to try it, discuss it, critique it? Not sure by the tone of your message.

Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#43
Could it be that slop PRs are less frequently rejected/commented due to (unfortunate) increased acceptance of it? As it turns out when maxxing AI on leaf parts of a program, the quality of the code doesn't matter that much anymore when compared to building the fundament.

Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#44
post #26

And once you’ve written all these specs you realize it became so slow that it’s faster to do it yourself in editor

at which point you realize you never had a plan written down and you are using the code as a spec

Which takes us back to this:

https://haskellforall.com/2026/03/a-sufficiently-detailed-sp...

Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#45
> We are entering the post-slop era. My software is more robust, better tested, better integrated, and more observable than ever before. And my velocity keeps increasing!

Don't we just love the hard fact conclusions based on sample size N=1 and hand-waving arguments?

Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#46

Wow - I love programming in YAML! You know what would make this really fun? Sprinkle in some Jinja. Then we'll be cooking with gas.

Exactly. At some point, the specification becomes so complex, it's easier to just write the code yourself. It's why famously, programmers always say, the code is the documentation, because writing detailed docs is very tedious and nobody wants to do it.

There are middle-ways.

Behaviour Driven Development or Spec Driven Development are, loosely, forms of Test Driven Development where you encode the specification into the code base. No impedance, full insight, formality through code.

I think people get really dogmatic about “test” projects, but with a touch of effort a unit test harness can be split up into integration tests, acceptance tests, and specification compliance tests. Pull the data out as human readable reports and you have a living, verifiable, specification.

Particularly using something comparable to back-ticks in F#, which let test names be defined with spaces and punctuation (ie “fulfills requirement 5.A.1, timeouts fail gracefully on mobile”), you can create specific layers of compiled, versioned, and verifiable specification baked into the codebase and available for PMs and testers and clients and approval committees.

Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#48
Old ist new I guess. This is independent of whether A"I" or a human executes, the point is that you need this if specifying and execution lie apart, be it in time or space. This is basically the whole point of the V-Model and processes (if used correctly as a tool and not preferred as goals) and was already researched an formalized in the 60s and 70s.

Re: Specsmaxxing – On overcoming AI psychosis, and why I write specs in YAML

#49

I use OpenSpec for my spec management, and I scrolled down to the comparison. The gripe seems to be with a semantic difference. Specs describing a current system is the basis for AS/IS Gap Analysis. Also, I mainly pursue these tools so that I can have AI accelerate this process and broker an agreement after negotiating specs with the agent.

I'm also doing openspec for a few months now and it's really good if you invest enough in the specs (in the beginning I skimmed over much, now I pay attention to all details and fix anything that's wrong or where I see a gap).

The one thing I like that OP brings is to tie specs and code together. The openspec flow does help a lot in keeping code synced with specs, but when a spec changes, AI needs to find the relevant code to change it. It's pretty easy to miss something in large codebase (especially when there is lots of legacy stuff).

Being able to search for numbered spec tags to find relevant bits of code makes it much more likely to find what needs to be changed (and probably with less token use too).

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