title: Selection of Reasoning-Class Models for Abstract Synthesis (Phase 0) authors:

• name: Vadim Rudakov email: rudakow.wadim@gmail.com date: 2026-04-01 description: Reasoning-Class models (high abstract synthesis) are required for Phase 0 to resolve requirements ambiguity before the aidx pipeline engages local hardware. tags:

• model

• workflow options: type: adr birth: 2026-01-24 version: 1.0.1 token_size: 1021 id: 26008 status: superseded superseded_by: ADR-26027

ADR-26008: Selection of Reasoning-Class Models for Abstract Synthesis (Phase 0)¶

Title¶

Mandating the use of General-Purpose “Reasoning-Class” LLMs for Phase 0 to ensure maximum logic depth and abstract synthesis.

Status¶

Superseded

Superseded by: ADR-26027

Supersession Rationale¶

This ADR bound the Reasoning-Class model requirement to Phase 0 of the aidx framework, coupling a general selection heuristic to a specific toolchain. Together with ADR-26006, it was superseded by ADR-26027, which defines the Reasoning-Class vs. Agentic-Class taxonomy as a tool-agnostic selection principle.

Date¶

2026-01-16

Context¶

As established in ADR-26006, the Phase 2 (Architect) role requires Agentic-Class models optimized for “Workflow Adherence” and rigid instruction following. However, Phase 0 (Intent Synthesis) ADR-26007 represents a different cognitive requirement:

• Abstract Synthesis: The model must synthesize vague human ideas into a cohesive, structured architectural plan.

• Reasoning Ceiling: High-level logic (e.g., GPQA Diamond benchmarks) is required to identify hidden technical debt or architectural contradictions before they reach the local editor.

• Conversational Nuance: Unlike the “Rigid Architect,” the Phase 0 model must be a “Thinking Partner” capable of multi-modal analysis and deep-dive logic.

Decision¶

We mandate the use of Reasoning-Class (Abstract Synthesis) models for the Phase 0 gateway.

1. Primary Criteria: Models must be selected based on their Reasoning Ceiling (GPQA/AIME scores) rather than instruction adherence alone.

2. Permitted Models: Only SOTA reasoning models are approved for this phase. The actual list of models is available in “General Purpose (Abstract Synthesis) vs Agentic (Instruction Adherence) Models” and should be considered the Single Source of Truth when choosing the model.

3. Role Separation: These models are strictly forbidden for the Phase 2 (Architect) role (unless configured in a high-adherence sub-mode) to prevent “Instruction Drift”.

Consequences¶

Positive¶

• High-Fidelity Planning: Leveraging the logic ceiling of the world’s most capable models ensures a robust foundation for the local stack.

• Ambiguity Resolution: These models excel at identifying what the Human Lead didn’t say, preventing downstream hallucinations.

Negative¶

• High Latency/Cost: Reasoning-class models are significantly slower and more expensive than the Agentic-class models (like Gemini 3 Flash) used in Phase 2. Mitigation: Since this is a one-time “Phase 0” gateway, the cost is offset by the reduction in token waste during Phase 2 and 3.

• Reduced Instruction Adherence: These models may attempt to “over-engineer” the plan. Mitigation: The Human Lead must strictly enforce the use of the aidx templates during the final mission synthesis.

Alternatives¶

• Using Agentic Models (Phase 2 Models) for Phase 0: Rejected. Models like Gemini 3 Flash (non-thinking mode) are optimized for speed and adherence but often lack the “Deep Thinking” necessary for complex problem elaboration.

References¶

• ADR-26005: Formalization of Aider as Primary Agentic Orchestrator

• ADR-26006: Requirement for Agentic-Class Models for the Architect Phase

• ADR-26007: Formalization of Phase 0: Intent Synthesis (Requirements Engineering)

• “General Purpose (Abstract Synthesis) vs Agentic (Instruction Adherence) Models”

Participants¶

1. Vadim Rudakov

2. Senior AI Systems Architect