confidence-engine/docs/v0.5-release-notes.md

v0.5 Release Notes

Purpose of v0.5

v0.5 stabilises the graph-backed one-turn update flow so the engine can resolve an answered unknown, surface consequential new unknowns, prioritise the next unknown deterministically, and formulate a deterministic follow-up question without changing the UI or adding more model turns.

Capabilities proven

v0.5 includes:

• resolving an existing unknown
• surfacing consequential new unknowns
• limiting emergent unknowns
• deterministic information-value prioritisation
• deterministic question formulation
• generalisation across five decision types
• graph-backed one-turn UI update

Five-case generalisation result

All five deterministic fixture scenarios passed:

1. Should we hire another engineer?
2. Should we replace the delivery vans?
3. Should we launch in another country?
4. Should we continue a project that is over budget?
5. Should we introduce a paid support tier?

The selector chose a foundational unknown first in each case, avoided the downstream leaf first, required no model call, and preserved graph immutability during question formulation.

Key deterministic safeguards

• proposal application re-selects the active unknown deterministically after validation
• information-value scoring penalises downstream or prerequisite-blocked unknowns
• emergent unknown validation limits additions and requires explicit answer-derived linkage
• final question wording is reformulated from graph context without an extra model turn
• question validation rejects compound, awkward, or pricing-led fallback phrasing

Known limitation

A correctly selected threshold node can still be phrased using an actor/customer strategy when surrounding graph context strongly references customers or value recipients.

This limitation is recorded for the next experiment and is not being fixed in the v0.5 release-prep task.

Deliberately excluded work

• no reasoning-logic expansion beyond the small deterministic formulation fixes already landed on the branch
• no new features
• no UI changes
• no persistence
• no additional model turn
• no Ollama calls for validation
• no evaluator-suite runs
• no Playwright runs

Next experimental question

Can the question formulation strategy remain aligned with the selected node's role when surrounding graph context contains competing signals?