# Known Limits Before Field Eval

## Current Stage Limits
- Retrieval layer is stubbed in assistant mode:
  - system returns execution plan and routing trace,
  - not a full factual extraction from 1C/OData/MCP yet.
- Session memory is in-memory only:
  - resets on backend restart,
  - no durable storage for long dialog continuity.
- No production-grade orchestration:
  - no multi-agent planner,
  - no long-horizon tool chain.
- Clarification policy is deterministic baseline:
  - adequate for sandbox,
  - will need tuning from real field traces.

## What Is Intentionally Deferred
- Large conversation memory (100+ turns).
- Automatic re-labeling and synthetic auto-eval expansion.
- Full data retrieval hardening for every route.
- Deep route fallback optimization beyond current deterministic policy.
- Production SLO/SLA, auth, tenancy, and governance controls.

## Risks to Track
- User may interpret planned route as final factual answer.
- Partial fallback wording can still be too technical for non-debug users.
- Out-of-scope vs clarification boundary may drift on ambiguous prompts.
- Without field replay set (30-40 real questions), optimization remains speculative.

## Exit Criteria for Next Hardening Step
- Collect real assistant-mode traces from live operators.
- Build labeled set from real interactions (not synthetic-only).
- Run targeted policy eval for:
  - clarification precision/recall,
  - false no-route rate,
  - partial fallback quality.
- Connect at least one route to factual retrieval and validate answer-grounding.
