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token-optimization — Reusable Retrieval "Experience Edges" for Cache-Memory
Paper: VikingRAG: Accurate and Token-efficient Retrieval-augmented Generation over Structured Documents Authors: Peiyuan Gao, Gaoyuan Zhang, Haojie Qin Published: 2026-09-10 Effort: medium Rationale: VikingRAG materializes multi-round agentic retrieval traces as "experience edges" reused for similar future queries, avoiding repeated multi-round exploration and cutting token overhead. gh-aw's cache-memory/repo-memory could store these traces across workflow runs so similar future queries in DataOps pre-steps or sub-agent research tasks skip redundant multi-round retrieval, directly reducing per-run token cost.
workflow-compilation — Principled Failure Diagnosis Before Harness Auto-Revision
Paper: Ecdysis: Efficient and Effective Training of Runtime Harnesses for LLM Agents Authors: Ruiqing Yue, Yu Cui, Zhuoyu Sun Published: 2026-09-10 Effort: medium Rationale: Ecdysis identifies the lack of principled failure diagnosis — distinguishing model-specific deficiencies from systematic harness issues — as the key bottleneck limiting harness-evolution generalization. Applied to gh-aw, this suggests adding a diagnosis step before the compiler or gh aw fix-style codemods auto-revise workflow frontmatter/config, preventing overfitting compiled-workflow changes to noisy, task-specific failure patterns.
safe-outputs — Interaction Contracts for Mid-Flight Goal Changes
Paper: Agent-Integrated Software: Interaction Contracts and Continuous Assurance Authors: Shengcheng Yu, Chunrong Fang, Zhenyu Chen Published: 2026-09-10 Effort: high Rationale: The paper's Interaction Contracts formalize task bindings, role-specific authority, control transitions, and outcome evidence to keep delegated agent execution correct when users revise goals mid-task. gh-aw's safe-outputs could adopt a similar schema layer so in-flight writes (issue/PR/discussion creation) are validated against the original triggering context, preventing stale or unauthorized outputs when a workflow's triggering issue/PR state changes during a run.
Investigate: Reusable retrieval "experience edges" for cache-memory (effort: medium)
Investigate: Principled failure diagnosis before harness auto-revision (effort: medium)
Investigate: Interaction contracts for safe-outputs mid-flight goal changes (effort: high)
Quick-Win Agentic Prompts
Paste one of these as a new issue or comment to kick off implementation with @copilot
(one prompt per opportunity, in the same order as above):
@copilot Implement: Materialize agentic multi-round retrieval traces as reusable "experience edges" in cache-memory/repo-memory so similar future workflow queries skip repeated multi-round exploration, cutting token cost in gh-aw's token-optimization component. Rationale: VikingRAG materializes multi-round agentic retrieval traces as "experience edges" reused for similar future queries, avoiding repeated multi-round exploration and cutting token overhead. gh-aw's cache-memory/repo-memory could store these traces across workflow runs so similar future queries in DataOps pre-steps or sub-agent research tasks skip redundant multi-round retrieval, directly reducing per-run token cost. Source: VikingRAG: Accurate and Token-efficient Retrieval-augmented Generation over Structured Documents.
@copilot Implement: Add principled failure diagnosis (model-deficiency vs. harness-issue classification) before auto-revising workflow/agent configs in gh-aw's workflow-compilation component. Rationale: Ecdysis identifies the lack of principled failure diagnosis — distinguishing model-specific deficiencies from systematic harness issues — as the key bottleneck limiting harness-evolution generalization. Applied to gh-aw, this suggests adding a diagnosis step before the compiler or gh aw fix-style codemods auto-revise workflow frontmatter/config, preventing overfitting compiled-workflow changes to noisy, task-specific failure patterns. Source: Ecdysis: Efficient and Effective Training of Runtime Harnesses for LLM Agents.
@copilot Implement: Formalize interaction contracts (task bindings, role-specific authority, control transitions, outcome evidence) as explicit schema constraints on safe-outputs writes in gh-aw's safe-outputs component. Rationale: The paper's Interaction Contracts formalize task bindings, role-specific authority, control transitions, and outcome evidence to keep delegated agent execution correct when users revise goals mid-task. gh-aw's safe-outputs could adopt a similar schema layer so in-flight writes (issue/PR/discussion creation) are validated against the original triggering context, preventing stale or unauthorized outputs when a workflow's triggering issue/PR state changes during a run. Source: Agent-Integrated Software: Interaction Contracts and Continuous Assurance.
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Summary
25 papers screened, 12 relevant, 3 actionable opportunities identified.
Actionable Opportunities
token-optimization — Reusable Retrieval "Experience Edges" for Cache-Memory
Paper: VikingRAG: Accurate and Token-efficient Retrieval-augmented Generation over Structured Documents
Authors: Peiyuan Gao, Gaoyuan Zhang, Haojie Qin
Published: 2026-09-10
Effort: medium
Rationale: VikingRAG materializes multi-round agentic retrieval traces as "experience edges" reused for similar future queries, avoiding repeated multi-round exploration and cutting token overhead. gh-aw's cache-memory/repo-memory could store these traces across workflow runs so similar future queries in DataOps pre-steps or sub-agent research tasks skip redundant multi-round retrieval, directly reducing per-run token cost.
workflow-compilation — Principled Failure Diagnosis Before Harness Auto-Revision
Paper: Ecdysis: Efficient and Effective Training of Runtime Harnesses for LLM Agents
Authors: Ruiqing Yue, Yu Cui, Zhuoyu Sun
Published: 2026-09-10
Effort: medium
Rationale: Ecdysis identifies the lack of principled failure diagnosis — distinguishing model-specific deficiencies from systematic harness issues — as the key bottleneck limiting harness-evolution generalization. Applied to gh-aw, this suggests adding a diagnosis step before the compiler or
gh aw fix-style codemods auto-revise workflow frontmatter/config, preventing overfitting compiled-workflow changes to noisy, task-specific failure patterns.safe-outputs — Interaction Contracts for Mid-Flight Goal Changes
Paper: Agent-Integrated Software: Interaction Contracts and Continuous Assurance
Authors: Shengcheng Yu, Chunrong Fang, Zhenyu Chen
Published: 2026-09-10
Effort: high
Rationale: The paper's Interaction Contracts formalize task bindings, role-specific authority, control transitions, and outcome evidence to keep delegated agent execution correct when users revise goals mid-task. gh-aw's safe-outputs could adopt a similar schema layer so in-flight writes (issue/PR/discussion creation) are validated against the original triggering context, preventing stale or unauthorized outputs when a workflow's triggering issue/PR state changes during a run.
Papers Analyzed
Next Steps
Quick-Win Agentic Prompts
Paste one of these as a new issue or comment to kick off implementation with
@copilot(one prompt per opportunity, in the same order as above):
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