Two open projects
Experts defined by their corpora, over one small resident model.
active Each expert is a QLoRA adapter with a library it has learned to navigate; a router sends each request to the expert whose corpus it falls in, or out to a frontier model. Numbers on this page are checked nightly.
Version control for live-patched agent systems.
revived — validation in progress Change your harness while it runs and still know what worked: every step stamped with the harness version that produced it.
The flagship · lora-kernel · Apache 2.0
One GPU, one small resident model, and a shelf of QLoRA adapters — each an expert defined by its corpus. An OpenAI-compatible API reads every request, serves it with the expert whose corpus it falls in, and sends everything else to a frontier model. The client names no model.
Version 1.0 adds what a small expert cannot hold in its weights: a library of short notes per subdomain, and an adapter trained on the habit of navigating it. The weights hold the navigation; the notes hold the content, and a person can read, diff and correct them.
Read the architecture article → En español The memory Repository
The finding that reorganised the project
Same adapter, same cases. Only the serving path changed.
A fluid-mechanics expert — 6-to-9-step chains with a calculator and a
per-case handbook — scored 11/90 when tool results came back as
tool_calls messages. Written inline, the way its corpus taught it to read them,
it scores 90/90 (79 : 0, paired). For four days that gap had been read as
“small models cannot reason”.
Tool block, argument order, system prompt, result format.
Under a foreign system prompt 2 of 32 live turns call a tool; under its own, 19 of 32. Serve an expert the way its corpus taught it, and suspect the path before the model.
Same corpora, same recipe, a new base.
Both released members were retrained on Qwen3.5-4B and each
ties its own earlier release: inbox triage 471/475, desk commitments
240/240.
What deliberately never becomes a weight?
The library. A weight delta cannot be read, cited or corrected by a person; a half-page note can. Site rules override the textbook before the expert ever sees the note.
The core of version 1.0
search, open, calc —
with results written inline. A software referee turns the pages, applies the site's rules
and cuts a walk that skips a required step.being built The first library exists — the step-by-step procedures of an open textbook (CC BY 4.0), as short linked notes that pass a lint, and the referee that walks them. The central claim is untested: that a library extends an expert to a procedure it never trained on.
What is measured
| what | the number | run |
|---|---|---|
| A reasoning expert served the way its corpus taught | 90/90 against 11/90 through tool_calls, 79 : 0 paired | M7 arm 0b |
Inbox triage, retrained on Qwen3.5-4B |
471/475, a tie with its earlier release; the bare base scores 346/475 | M1 |
| A second expert on the same inbox, a different question | 240/240, a tie with its earlier release | M1 |
| The API routes per request; the client names no model | 0.546 → 0.775 on a 240-case replay, 0 misrouted | P41, P62 |
| A procedure merely pasted into a 3B’s prompt is not followed | 0 tool calls on 351/351; the trained expert beats it 137 : 1 | P61 |
What is not, or does not work
The full ledger, including everything that failed and the instruments that lied: RECORD.md. The position: PLAN.md.
Where it sits in an organisation
Under the agent column, not beside it.
An organisation that runs on agents draws the same picture: people in a few roles, an agent runtime with one agent per role, the applications they operate, the channels people already use, and one database underneath. In that picture every agent is a system prompt over the same remote model. Here each role becomes an expert — an adapter trained on how this organisation does that job — and the role a message arrives from is the route.
Records, habits, knowledge.
Records stay in the database. Habits go in the adapter. Knowledge stays in notes a person can read and correct — two drawers per role: how we do it here, and what we know. What an expert is measured to handle is answered on the organisation’s own machine; the rest goes to the frontier, or to a person where policy says nothing leaves the building.
| organisation | roles that become experts | what goes in the two drawers |
|---|---|---|
| a distributor | customer service, receiving, dispatch, purchasing, claims | the site’s handling procedures · catalogue, carriers, service levels |
| an accounting or law office | intake, document review, deadlines, billing | the firm’s checklists and templates · the rules of its jurisdiction |
| a school or training centre | enrolment, teaching support, communications, purchasing | how this school handles each case · programme, calendar, regulations |
| a repair or field-service company | equipment intake, diagnosis, spare parts, warranties | the procedure for each kind of repair · manuals, parts lists, warranty terms |
| a club or community centre | memberships, activity sign-ups, facilities, collections | how this club handles each case · activities, fees, house rules |
| a property manager | tenant requests, maintenance, collections, suppliers | the escalation procedure per building · contracts, by-laws, supplier terms |
not measured These are where the design points, not results. What they share is what makes a region worth an expert: the same few procedures, repeated daily, with local rules that differ from the textbook, over data that should not leave. The first library in the repository is built from an open textbook’s step-by-step procedures.
For a team running agents together
The second project · agentvcs · Apache 2.0
Version control for live-patched agent systems: change your harness while it runs and still know what worked.
revived — validation in progress Every step of a long multi-model run is stamped with the exact harness version that produced it — prompts, models, sampling, tools, adapters, router — so a patch applied while the system runs can be gated, attributed, rolled back, or resumed from a checkpoint instead of re-running from the start. It was frozen in 2026 and is active again.
Research Lab · ANFAIA
agentvcs is among the projects that passed the ANFAIA Research Lab. The work it carries there is the one described above: version control for agent systems that are patched while they run.