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| schema: foundry-doc-v1 | schema: foundry-doc-v1 |
| title: "Model tier discipline" | title: "Model tier discipline" |
| slug: model-tier-discipline | slug: model-tier-discipline |
| category: patterns | category: patterns |
| type: topic | type: topic |
| quality: complete | quality: complete |
| short_description: The discipline for routing work to the appropriate AI model tier — deep-think, implementation, or mechanical — to match model capability to work shape and control inference cost. | short_description: The discipline for routing work to the appropriate AI model tier — deep-think, implementation, or mechanical — to match model capability to work shape and control inference cost. |
| status: active | status: active |
| bcsc_class: public-disclosure-safe | bcsc_class: public-disclosure-safe |
| last_edited: 2026-05-01 | last_edited: 2026-05-01 |
| editor: pointsav-engineering | editor: pointsav-engineering |
| cites: [] | cites: [] |
| paired_with: model-tier-discipline.es.md | paired_with: model-tier-discipline.es.md |
| --- | --- |
| A platform that routes all inference work through the highest-capability model available regardless of work shape spends significantly more per output than necessary. A platform with no guidance on model selection leaves each contributor to make independent choices that may be inconsistent, cost-inefficient, or both. Model tier discipline is the structured approach that matches work shape to model capability, routes appropriate work to lower-cost tiers, and makes the routing decision explicit and reviewable. | A platform that routes all inference work through the highest-capability model available regardless of work shape spends significantly more per output than necessary. A platform with no guidance on model selection leaves each contributor to make independent choices that may be inconsistent, cost-inefficient, or both. Model tier discipline is the structured approach that matches work shape to model capability, routes appropriate work to lower-cost tiers, and makes the routing decision explicit and reviewable. |
| ## Three abstract tiers | ## Three abstract tiers |
| Work shapes fall into three categories that map to three model tiers: | Work shapes fall into three categories that map to three model tiers: |
| **Deep-think.** Architectural decisions, doctrine authoring, cross-cutting analysis, novel problem framing, multi-source synthesis. These are the tasks where a more capable model's additional reasoning ability produces materially better outputs. Examples: authoring a new convention, debugging a problem whose root cause is not yet identified, coordinating decisions across multiple workstreams. | **Deep-think.** Architectural decisions, doctrine authoring, cross-cutting analysis, novel problem framing, multi-source synthesis. These are the tasks where a more capable model's additional reasoning ability produces materially better outputs. Examples: authoring a new convention, debugging a problem whose root cause is not yet identified, coordinating decisions across multiple workstreams. |
| **Implementation.** Following an established plan, single-component scoped work, well-specified feature implementation, code review against ratified conventions. A model at this tier can produce correct output on an established specification without needing the full reasoning capacity required for deep-think work. Examples: scaffolding a new module from a documented spec, drafting a runbook from a known template, writing unit tests for a defined interface. | **Implementation.** Following an established plan, single-component scoped work, well-specified feature implementation, code review against ratified conventions. A model at this tier can produce correct output on an established specification without needing the full reasoning capacity required for deep-think work. Examples: scaffolding a new module from a documented spec, drafting a runbook from a known template, writing unit tests for a defined interface. |
| **Mechanical.** Pattern-matching work with clear inputs and outputs, no architectural judgment, repeatable structure. The work is correct or incorrect in an unambiguous way. Examples: file moves, version number bumps, registry row updates, formatting normalization. | **Mechanical.** Pattern-matching work with clear inputs and outputs, no architectural judgment, repeatable structure. The work is correct or incorrect in an unambiguous way. Examples: file moves, version number bumps, registry row updates, formatting normalization. |
| ## The preferred in-seat routing mechanism | ## The preferred in-seat routing mechanism |
| When a work session reaches a natural pause and the next bounded chunk of work fits a lower tier, the session dispatches a foreground sub-agent at the appropriate tier rather than continuing to perform that work at the current tier. The parent session retains its context and waits for the sub-agent to complete, then reviews the result and either commits it or queues the next chunk. | When a work session reaches a natural pause and the next bounded chunk of work fits a lower tier, the session dispatches a foreground sub-agent at the appropriate tier rather than continuing to perform that work at the current tier. The parent session retains its context and waits for the sub-agent to complete, then reviews the result and either commits it or queues the next chunk. |
| This approach preserves session context while routing volume work through lower-cost tiers. The parent pays parent-tier rates only for orchestration — reviewing results, authoring commit messages, making the next structural decision. The sub-agent does the volume work at a lower rate. | This approach preserves session context while routing volume work through lower-cost tiers. The parent pays parent-tier rates only for orchestration — reviewing results, authoring commit messages, making the next structural decision. The sub-agent does the volume work at a lower rate. |
| Four properties govern how sub-agent dispatch works in practice: | Four properties govern how sub-agent dispatch works in practice: |
| **Bounded brief.** One task, one result, self-contained. The brief includes file paths, names the desired output shape, and caps response length. Open-ended exploration is not a sub-agent task. | **Bounded brief.** One task, one result, self-contained. The brief includes file paths, names the desired output shape, and caps response length. Open-ended exploration is not a sub-agent task. |
| **Foreground and serial when writing.** A sub-agent writing to files runs to completion before the next one starts. Parallel dispatch is appropriate for read-only work — research, scanning, triage — but not for write operations that share a file index. | **Foreground and serial when writing.** A sub-agent writing to files runs to completion before the next one starts. Parallel dispatch is appropriate for read-only work — research, scanning, triage — but not for write operations that share a file index. |
| **Confidence gate.** Dispatch only when there is high confidence the sub-agent will produce output matching or exceeding what the current tier would produce on the same bounded task. Mechanical edits, well-specified implementations, read-only research, and scoped refactors against a clear spec pass this gate. Architectural decisions, doctrine drafting, cross-layer coordination, and anything requiring novel framing do not. | **Confidence gate.** Dispatch only when there is high confidence the sub-agent will produce output matching or exceeding what the current tier would produce on the same bounded task. Mechanical edits, well-specified implementations, read-only research, and scoped refactors against a clear spec pass this gate. Architectural decisions, doctrine drafting, cross-layer coordination, and anything requiring novel framing do not. |
| **Layer scope preserved.** A sub-agent dispatched from one layer operates within that layer's scope. Cross-layer work travels through the established coordination mechanism rather than through sub-agent dispatch. | **Layer scope preserved.** A sub-agent dispatched from one layer operates within that layer's scope. Cross-layer work travels through the established coordination mechanism rather than through sub-agent dispatch. |
| ## The cost framing | ## The cost framing |
| The three-tier structure produces a significant effective multiplier at fixed daily token budgets. Using the same daily token cap, running mechanical work at the mechanical tier instead of the deep-think tier extends the budget by approximately a factor of fifteen. A contributor pool operating at tier discipline can sustain a substantially larger volume of committed output within the same infrastructure cost as a smaller pool operating without tier discipline. | The three-tier structure produces a significant effective multiplier at fixed daily token budgets. Using the same daily token cap, running mechanical work at the mechanical tier instead of the deep-think tier extends the budget by approximately a factor of fifteen. A contributor pool operating at tier discipline can sustain a substantially larger volume of committed output within the same infrastructure cost as a smaller pool operating without tier discipline. |
| This multiplier is the structural reason why a contributor model that includes a larger pool of paid contributors is operationally viable. Without tier discipline, that model is expensive enough to be impractical. With it, the cost structure works. | This multiplier is the structural reason why a contributor model that includes a larger pool of paid contributors is operationally viable. Without tier discipline, that model is expensive enough to be impractical. With it, the cost structure works. |
| ## What the discipline is not | ## What the discipline is not |
| Model tier discipline does not refuse work at the current tier. Sessions write a dispatch recommendation or proposal; a human principal decides whether to act on it. The discipline is a cost-optimization recommendation mechanism, not a gate. | Model tier discipline does not refuse work at the current tier. Sessions write a dispatch recommendation or proposal; a human principal decides whether to act on it. The discipline is a cost-optimization recommendation mechanism, not a gate. |
| It is also not a constant check. Recommendations fire only at substantive work-shape pivots. Constant suggestions create overhead that erodes the cost savings they are intended to produce. The trigger is a genuine pivot, not a micro-pause. | It is also not a constant check. Recommendations fire only at substantive work-shape pivots. Constant suggestions create overhead that erodes the cost savings they are intended to produce. The trigger is a genuine pivot, not a micro-pause. |
| Tier discipline and model version progression are orthogonal axes. A new model version earning a role through a supervised period of demonstrated correctness is a different question from which tier of the current model family to use for a specific bounded task. Both apply simultaneously. | Tier discipline and model version progression are orthogonal axes. A new model version earning a role through a supervised period of demonstrated correctness is a different question from which tier of the current model family to use for a specific bounded task. Both apply simultaneously. |
| ## See also | ## See also |
| - [[compounding-substrate]] — the contributor model this discipline makes economically viable | - [[compounding-substrate]] — the contributor model this discipline makes economically viable |