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daimon has a home: bilingual docs, and what shipped this week

· 3 min read
daimon maintainers
daimon maintainers
Daily-Nerd

daimon now has a documentation site — the one you are reading — in English and Spanish, with a quickstart that takes you from install to your first briefing, and concept pages for the ideas that make daimon different: trust classes, carry, receipts, and the item lifecycle. This blog is the new canonical home for releases, feature explainers, and field incidents; every announcement you see from us elsewhere will link back here.

What shipped this week​

daimon 0.18.0 is on PyPI (uv tool install 'daimon-briefing[pretty]'). The headline experiment: opt-in per-item scene traces, indexed for recall. It ships behind a flag while we A/B it against our own benchmark — if the numbers don't earn it, it doesn't go default-on. That's the deal we make with every feature.

daimon forget is merged and ships in the next release: item removal with a tombstone event. The item leaves the live checkpoint, the recall index, and the audit trail's content — but the event stream keeps a content-hash tombstone, and with receipts enabled the post-removal checkpoint is re-signed. Deletion you can prove happened, without keeping what was deleted. The item lifecycle page covers the mechanics.

The docs went bilingual. Every page — quickstart, concepts, hosts, configuration, team memory — is available in Spanish. Not machine-dumped: written for Spanish-reading developers, because the es-speaking agent-dev community deserves first-class docs, not an afterthought.

Windsurf is live-validated. The capture loop (native-transcript serialize) has now been tested end-to-end in real Windsurf use, joining Claude Code. Codex ships next; Gemini waits on an upstream fix.

Why this project exists, in one paragraph​

Your agent forgets everything between sessions, and most memory systems "fix" that by storing text a model wrote about what happened — with no way to tell which parts are quotes and which parts are guesses. daimon marks every remembered item as verbatim (an exact quote, mechanically verified against the transcript by a deterministic checker — no LLM grading its own homework) or inferred (allowed to evolve, flagged for verification). A recent survey of agent-memory research calls claim-level provenance an open problem; we think the answer is to make memory provable, and that is the axis everything here is built on.

More soon — releases, war stories from the field, and deep dives into how the verification machinery works. Subscribe via RSS or follow the repo on GitHub.