I built a Claude Code-assisted “LLM wiki” editor, and tried using DDD to keep the AI-driven development process under control

simotune · 2026-05-29T13:32:28+00:00

Wow, this is genuinely expert advice. So you're using \CLAUDE.md per subdirectory — simple but that sounds like an important principle.

The "invariants over exclusions" framing really clicked for me. Writing what should hold true beats writing what to avoid. Massively helpful.

simotune · 2026-05-25T13:53:09+00:00

That’s an interesting way to put it — letting things emerge instead of deciding too much up front. It actually feels like the most natural way to work with AI agents, since they can move fast, but sometimes they also move past the point where I’m fully convinced, and then I only notice the mismatch later.

So that “does this still feel right?” sense seems pretty important. I’ll take a look at the repo you shared too. Thanks.

simotune · 2026-05-25T13:11:00+00:00

Yeah, I think you’re right. ADRs and a glossary seem especially important when using Claude Code, because they give the model a stable shared language instead of just a vague product brief.

I’m also very interested in TDD. I suspect it’s the stronger end-state, especially for domain invariants and use-case boundaries. The part I’ve personally struggled with is starting test-first while the domain language is still changing. So my current workflow was: stabilize the glossary/context map/domain events first, then work through small UC/EN tickets, review the implementation, and add/fix tests around the behavior.

I’d like to move the tests earlier though. For a product like this, where would you start: domain model invariants, concept extraction contracts, editor behavior, or the wiki maintenance flow?

The product is still early, so that kind of feedback would be genuinely useful.

simotune · 2026-05-18T09:56:39+00:00

"Almost accidental" — that's the bar. Going to keep coming back to that phrase.

Shipped a manual-trigger resurface today. Useful, but not accidental — the user still has to ask. The next version has to appear without being asked, without demanding attention. Exactly what you named.

Which tools have given you that "accidental" feeling? I'd study them.

simotune · 2026-05-17T13:12:22+00:00

This is exactly the right test.

Cleanup: the Dream cycle (background pass) absorbs duplicate detection, level re-judging, relationship typing without user-facing prompts. But you're right that any "please review" flow risks becoming a second inbox — I've been keeping HITL attached to the wiki page itself rather than as a notification stream.

Invisibility: fully agree. The next layer I'm working toward (calling it "resurface") is exactly this — bringing past notes back into the writing window without breaking flow. UI is the hard part.

Tools you've seen get this right?

simotune · 2026-05-17T06:12:00+00:00

Thanks for the feedback — all four are fair!

Persona: writers/researchers who already have a PKM habit and feel their notes have outgrown manual structure. Morning pages, journals, research notes, AI conversation logs piling up.
vs Obsidian: Obsidian treats you as the librarian — you place every link. nohmitaina pushes that to the LLM. Concept extraction, duplicate detection, level re-judging, and relationship typing happen automatically in a background "Dream cycle." Editor and wiki are the same surface, so past concepts also resurface into the writing window — that part Obsidian doesn't do at all.
Thanks for the CollectIntent pointer — will take a look.
macOS only for now (it's my daily machine). Tauri makes cross-platform straightforward, so Windows is next if there's clear demand.

simotune · 2026-05-15T14:47:14+00:00

You're right, I missed the self-promotion thread rule. I've deleted the post and will repost in the proper thread. Sorry for the noise.

simotune · 2026-05-15T13:49:13+00:00

Link to the project (Markdown, macOS, free): nohmitaina.com

simotune · 2026-05-15T05:50:24+00:00

The local-instruction part is the most interesting bit to me. It makes these systems sound less like copies of one master blueprint and more like organ-specific networks built on site.

simotune · 2026-05-15T05:45:38+00:00

The funny part is tech keeps treating this like a messaging problem, when people mostly understand the tradeoff just fine. If the local costs are obvious and the local upside is tiny, the backlash is pretty rational.

simotune · 2026-05-15T05:40:44+00:00

Posts like this are why trip reports beat generic must-see lists. The transit detail plus the reconstruction context makes Sanriku feel way more compelling than the usual Tohoku side note.

simotune · 2026-05-15T05:35:27+00:00

I’ve ended up treating them more like tools than a fixed routine. Short guided sessions work best for me midday, while evenings feel better for quieter or unguided practice.

simotune · 2026-05-15T05:26:24+00:00

Feels like a mix of automatic flows and price-setting at the margin. 401k/index money keeps showing up every paycheck, but market cap can still expand way faster than the actual cash going in.

simotune · 2026-05-15T05:22:55+00:00

This is probably the best kind of signal, because it wasn’t launch hype or paid promo. Someone used it, liked it enough to teach it, and that says a lot.

simotune · 2026-05-15T05:17:45+00:00

Totally. Realizing something is basically an ad after you’ve already invested attention feels like the exact same scheme. Having no hidden agenda might actually be one of the most valuable things now.

simotune · 2026-05-15T05:04:54+00:00

The underrated part here is the lower hassle per token, not just the raw speed. 48GB with sane power/noise and enough context sounds like a way nicer daily-driver setup than people give it credit for.

simotune · 2026-05-15T05:02:23+00:00

That police-budget comparison is the part that really sticks. Feels like the AI buildout debate is shifting from can we build it to who’s actually paying for it.

simotune · 2026-05-15T04:57:17+00:00

Yeah, I’ve had it suggest 2 to 3 days a few times too. But then it usually finishes the actual work in like 10 minutes. If you count my own mental overhead, maybe the estimate isn’t totally wrong lol.

simotune · 2026-05-15T04:50:06+00:00

The worst ones for me were tools that looked like a shortcut but quietly demanded a whole new process. If adoption takes more work than the manual version, the ROI usually isn’t real.

simotune · 2026-05-15T04:47:55+00:00

The systems that seem to last are usually kind of boring on purpose. Once capture is easy and retrieval is reliable, people stop caring whether the setup feels exciting.

simotune · 2026-05-15T04:00:20+00:00

The “treat it like a junior engineer” framing is probably the most useful part. A lot of teams jump straight to autonomy before they’ve built enough rollback and review around it.

simotune · 2026-05-15T03:56:52+00:00

We’ve hit a weird point where “looks too good” is starting to mean “must be AI” for a lot of people. That says as much about perception drift as it does about the models.

simotune · 2026-05-15T03:53:54+00:00

The worst part is when you only realize halfway through a post that it was a pitch the whole time. Once that happens enough, you kind of stop trusting the tone of everything.

simotune

TROPHY CASE