# Stage 03: Scenario-Situate & Interrogate (aq03_interrogate_sources / DB-UNIT-12)

Situates observations across thousands of concrete tech-stack, industry, and constraint scenarios first (aq85) before interrogating gaps for Problemize.

- Atomic micro-queue: `aq03_interrogate_sources` (visibility: `public_commons`)
- Backing database unit: `DB-UNIT-12` (`Context Interrogation, Persona Matrix & Problem-Situation Core`)
- Database cell: `entities-db.teleon.dev` (`teleon_core.acquired_observations`, `teleon_core.interrogation_personas_and_rubrics`, `teleon_core.problem_situations`)
- Claim row hydration: `single_self_contained_flat_task_row` (100% context inline, normalized writeback)
- Track 2 Sister queue (`SISTER-12`): `sq12-improve-interrogation-queue.teleon.dev` (Add sharper interrogation questions, expand domain personas, and prioritize high-leverage problem scenarios.)
- Lanes: Scenarios First (aq85), Persona & 5W1H Matrix, Failure Probe

## Execution engines & AI Agent freedom contract

- **Deterministic (0 model calls)**: `interrogation_template_and_gap_compiler_v1` (Situated scenario fan-out & 5W1H coverage-gap runner)
- **Hybrid (<=1 model call)**: `persona_scenario_problemizer_hybrid_v1`
- **AI Agent & Bot Fleet (1..6 calls)**: `bot_fleet_persona_interrogator_v1` (Multi-stack scenario & persona adversarial interrogator)
  - Contract: **Instructions + Resources + Freedom to search for new resources and new ways not bound by instructions**

## Database invariants

- Partial problem situations remain valid when opportunity, context, and parent observation digests are recorded.
- Every bot-generated interrogation row records exact bot_harness, bot_version, and llm_model metadata.

## External & internal bot fleet actions

- Fan out thousands of concrete legacy/modern stack scenarios before framing problems
- Apply 5W1H, persona, activation, and failure probes inside each situated world
- Flag unverified claims or spawn upstream Stage-01/02 research loopbacks

## Sister self-tuning areas

- Add domain personas and who/what/where/when/why question sets (DIM-02, DIM-04)
- Tune urgency weights across humanitarian SDG, competition ML, math, and science labels (DIM-01)
- Compile recurring structured-observation anomaly checks into deterministic code_blocks (DIM-03, DIM-06)