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Verifiedharnesshybridv0.1.0Recommended

Hybrid Runtime

Use rules for known packets, use synthesis only when ambiguity is real.

Agent Workspace LabsUnsignedVerified publisher·Updated 2026-04-15·~0 installs this month

Install

npx attrition-sh pack install hybrid-runtime
# Hybrid Runtime
# See: /packs/hybrid-runtime

Raw Markdown

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Telemetry

Not yet measured

Summary

A disciplined runtime pattern that reserves deterministic rendering for tightly scoped known cases and uses an LLM only for bounded synthesis, not as the default execution path for every question.

Fit and expected payoff

When this pack earns its extra structure, when to skip it, and what it should improve.

Situations where this pack earns its extra structure.

  • Many requests map to known issue packets or stable policies.
  • The team wants lower cost and more predictable answers for common cases.
  • The same answer shape needs to hold across both deterministic and synthesized runs.

Keeps the pack from becoming a default hammer.

  • The domain is highly unstructured and almost every request is novel.
  • The deterministic path is weak enough that it adds noise instead of reliability.

Expected outcomes if implemented well.

  • Routine questions become cheaper and more stable.
  • The model is reserved for where synthesis adds value.
  • The runtime has a cleaner boundary between retrieval, rendering, and reasoning.

Minimal instructions

Smallest useful starting point.

Route the request first.

If the request matches a known packet with explicit policy or action steps:
- answer deterministically

If the request spans multiple packets or requires ambiguity handling:
- run the bounded synthesis path

Do not default to a full agent run for every request.

Full instructions

Complete natural-language instruction set.

Build a hybrid runtime.

Path A: deterministic
- use canonical issue or entity packets
- render from rules and trusted fields
- cite exact identifiers and thresholds

Path B: bounded LLM synthesis
- only after routing decides deterministic coverage is insufficient
- limit the model to the validated evidence set
- preserve the same answer packet and quality gate shape

The value is not fewer models. The value is a cleaner decision boundary.

Evaluation checklist

These checks should pass before you consider the pattern production-ready.

  • Do known packets render without unnecessary model usage?
  • Does the LLM path only activate when the request exceeds deterministic coverage?
  • Do both paths emit the same answer packet shape and review metadata?

Common failure modes

Every check below traces back to a specific production failure. Read as: "I would think about X because in production Y can happen."

  • Mid

    Everything routes to the model because deterministic coverage is not well defined.

    Trigger
    (legacy — trigger not separated)
    Prevention
    (legacy — no explicit prevention)
  • Mid

    Deterministic answers are too brittle because packets are incomplete.

    Trigger
    (legacy — trigger not separated)
    Prevention
    (legacy — no explicit prevention)
  • Mid

    The two paths produce different output contracts and confuse the UI.

    Trigger
    (legacy — trigger not separated)
    Prevention
    (legacy — no explicit prevention)

Official docs and implementation references

Reference implementations