docs(s53): knowledge-base recipe (D-H item 1) — team process, honest 1-2 week expectation, no wizard
New English docs/knowledge-base-recipe.md grounded strictly in the D-H decision record (revisjonspakke-DF-DI.md §3): setup is always a small team (technical + domain expert), the deliverable is a recipe NOT a wizard (B9 onboarding interview + guided verdict command rejected), domain expert delivers files in their own formats never schema/JSON, phased process (inventory -> skeleton -> seed verdicts -> iterate), reading via Obsidian/VS Code. The honest 1-2 week expectation is stated early and SOURCED verbatim to the record. Factory-dependent parts (free-format verdict translation, clone-to-demo) are explicitly marked future/blocked-on-toolkit so the doc never claims above the evidence level. Linked from README's Docs section with the 1-2 week expectation in context. SC5 (ASCII-only greps): file exists, '1-2 weeks' x2, 'knowledge-base-recipe' in README. src/ untouched; 431 passed. Co-Authored-By: Claude Opus 4.8 (1M context) <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_01KNNiJRk1sSwxgVLS5AobT1
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## Docs
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- [Building a knowledge base](docs/knowledge-base-recipe.md) — the team recipe (technical +
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domain expert) for curating a bundle, with the honest expectation that a good base takes 1–2
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weeks of dedicated work.
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- [Target picture](docs/plan/2026-06-26-maalbilde-agentic-loop.md) — the agentic loop + OKF
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knowledge architecture (north star).
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- [Prior-art & platform research](docs/research/2026-06-23-prior-art-platform.md) (incl.
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# Building a knowledge base — the team recipe
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> **This is a documented team process, not a wizard.** Setting up a knowledge base for
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> portfolio-optimiser is always done by a small team — a technical person and a domain expert
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> working together — because the framework side (MAF configuration, bundle structure) is
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> genuinely involved. There is deliberately **no onboarding interview and no guided verdict
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> command**: both were evaluated and rejected (operator decision D-H,
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> [`docs/plan/2026-07-14-revisjonspakke-DF-DI.md`](plan/2026-07-14-revisjonspakke-DF-DI.md) §3).
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## The honest expectation
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A good knowledge base takes **1-2 weeks of dedicated work**, and the quality of that investment
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determines the quality of the result. This is not a limitation to engineer around — it is the
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realistic cost of curating a body of knowledge an agent can reason over. Budget for it up front.
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> Sourced, not invented: this is verbatim in the operator decision record
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> (`docs/plan/2026-07-14-revisjonspakke-DF-DI.md` §3, item 1 — «en god base tar 1–2 uker dedikert
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> arbeid — kvaliteten på investeringen avgjør resultatet»).
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## Who does what
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The team is always **two roles** — never one person, and never a self-service form:
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- **The domain expert** contributes subject-matter knowledge. Their interface is deliberately
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minimal: *what* to contribute, *how*, and *where* — nothing more. They deliver **files in their
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own formats** (documents, spreadsheets, notes) — **never schemas or JSON**. What they should
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contribute next is steered by the evaluator's sufficiency feedback ("is this comprehensive
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enough to be useful? what is missing?"), which becomes the expert's worklist during buildup.
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- **The technical person** runs the pipeline: builds the OKF bundle, runs ingest and the
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evaluator, and manages the framework configuration.
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The verdict is always the human's; the machine only ever translates and structures.
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## The process, in phases
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1. **Inventory** — the domain expert gathers the source material in whatever formats they already
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have it in. No reformatting into schemas — that is the technical side's job.
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2. **Bundle skeleton** — the technical person builds the OKF bundle: `index.md`, the concept
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files, and the cross-links, from the inventoried material.
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3. **Seed verdicts** — prior expert judgements are seeded so the first run's hypotheses start from
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what experts actually decided (the ExpeL fold reads them). *See the factory note below: today
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verdicts are authored directly in the strict format; free-format translation is a future
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capability.*
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4. **Iterate** — run the evaluator, read its sufficiency feedback, and have the domain expert fill
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the gaps it names. Repeat until the base is comprehensive enough to be useful. This iteration
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loop is where most of the 1-2 weeks is spent.
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## Reading the bundle
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Bundles are plain markdown, so **Obsidian or VS Code** are enough to read and navigate them — no
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dedicated tool is required. (A dedicated reading view is a possible future toolkit building block,
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not a prerequisite — per D-H §3 item 5.)
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## Future / factory-dependent (not available today)
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The following are part of the intended process but depend on the **bundle factory** and the
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external toolkit repo, which are not built yet (D-G / T0). They are named here so the recipe stays
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honest about what ships today versus what is planned — never claiming above the evidence level:
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> - **Free-format verdict translation.** The intended flow: the expert delivers a free-format file
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> and the factory AI-translates it into the strict verdict format (manual translation does not
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> scale to large volumes), with the structured verdict always pointing back to the expert's
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> original file so a spot-check can compare "what the expert wrote" against "what the system
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> understood". Until the factory exists, verdicts are authored directly in the strict format.
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> - **Clone-to-demo path.** The intended demo: a fresh clone → drop the example into a bundle
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> inbox → the factory builds it → the whole loop runs. Until the factory exists, use the
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> committed example bundle and the offline simulation
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> (`uv run python -m portfolio_optimiser.simulation`).
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Where this recipe is thinner than your situation needs, treat the gap as an open question for the
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team to resolve together: the process is deliberately not over-specified beyond the decision record
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it is grounded in.
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