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Model Selection Playbook

Guidance for choosing models by phase and task type.

No model is required. These are recommendations, not requirements.


Selection by Phase

Planning & Architecture

Recommended capabilities:

  • Extended reasoning / thinking mode
  • Large context window (analyze multiple files)
  • Strong at structured output (specs, plans)

Why: Planning requires understanding full system context and making architectural decisions.

Examples: Models with "thinking" or "reasoning" modes, larger context variants.


Code Implementation

Recommended capabilities:

  • Fast iteration speed
  • Good at code completion
  • Tool/function calling (for verification commands)

Why: Implementation involves many small changes with frequent verification cycles.

Examples: Speed-tier models, code-specialized variants.


Refactoring

Recommended capabilities:

  • Large context window (see before/after)
  • Pattern recognition
  • Consistent style application

Why: Refactoring requires maintaining consistency across large code changes.

Examples: Standard or long-context variants.


Debugging

Recommended capabilities:

  • Extended reasoning (hypothesis generation)
  • Good at reading stack traces
  • Context for error patterns

Why: Debugging requires hypothesis testing and pattern matching.

Examples: Reasoning-focused models.


Code Review

Recommended capabilities:

  • Large context (review full PR diff)
  • Security pattern knowledge
  • Style consistency checking

Why: Review requires seeing both code and context together.

Examples: Long-context variants.


Capability Tiers

Tier Characteristics Best For
Fast Quick responses, lower cost Implementation, iteration
Standard Balanced speed/quality Most tasks
Reasoning Extended thinking, slower Planning, debugging, architecture
Long-context >100k tokens Review, refactoring

Anti-Patterns

Using reasoning models for simple edits — Overkill, slow, expensive

Using fast models for architecture — Insufficient depth for complex decisions

Ignoring context limits — Leads to quality degradation

Forcing a specific model — Breaks model-agnosticism


Model Switching Mid-Session

When to switch:

  • Context is getting polluted (approaching 50%)
  • Task type changes significantly (planning → implementation)
  • Current model struggling with task type

How to switch:

  1. Create state snapshot
  2. Update STATE.md with current position
  3. Start fresh session with appropriate model
  4. Load STATE.md to resume

GSD Model-Agnostic Principle

GSD works with any capable LLM. The methodology compensates for model differences through:

  1. Structured plans — Reduce ambiguity
  2. Explicit verification — Catch errors regardless of model
  3. State persistence — Enable model switching
  4. Fresh context — Prevent accumulation issues

Choose models based on task needs, not methodology requirements.


See PROJECT_RULES.md for canonical rules. See docs/runbook.md for operational procedures.