The 825 resource library

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Research and repositories worth inspecting. Evidence guides attention; a listing is not an endorsement or proof of effectiveness.

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Reviewed source snapshot imported 2026-10-20. This is not a live feed. Source and contributions.

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Choose a question to explore. These are editorial reading paths, not quality scores or endorsements.

Will AI actually help with this work?

Start with comparisons and tradeoffs before adding more automation.

When combinations of humans and AI are useful: A systematic review and meta-analysis

Tests the assumption that combining people and AI beats the stronger baseline.

Finding: On average, human-AI combinations performed worse than the better human-only or AI-only baseline. Effects varied: decision-making tasks showed losses, content-creation tasks showed gains, and augmentation depended on which side initially performed better.

Limits: The reviewed evidence is experimental and heterogeneous, with possible publication bias and differing study designs. Next: which coordination mechanisms improve the best-baseline comparison in sustained, privacy-constrained work?

What was reviewed: Structure and relevance screened; not a full evaluation

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Shifting Work Patterns with Generative AI

Separates changes in individual work from changes in coordination.

Finding: Access to AI changed work that individuals could change independently, including less time spent on email and moderately faster document completion. It did not significantly change time spent in meetings, a coordination-dependent activity.

Limits: The report describes access and work-pattern effects, not the quality, safety, or persistence of cross-repository coordination. Next: which repeated-use measures observe handoff quality, correction, and ownership changes rather than only time use?

What was reviewed: Structure and relevance screened; not a full evaluation

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Help people check the work and stay in control

Understand where explanations and automation can mislead.

Does the Whole Exceed its Parts? The Effect of AI Explanations on Complementary Team Performance

Shows why an explanation alone is not evidence of better decisions.

Finding: AI assistance produced some complementary performance, but explanations did not increase it. Explanations increased acceptance of recommendations whether they were right or wrong.

Limits: The tasks were bounded classification and reasoning tasks. Next: which outcome set captures quality, effort, reversibility, and accountability in open-ended work?

What was reviewed: Structure and relevance screened; not a full evaluation

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Human Performance Consequences of Stages and Levels of Automation: An Integrated Meta-Analysis

Connects routine automation benefits with recovery and awareness tradeoffs.

Finding: Higher automation improved routine performance and workload but reduced situation awareness and failure performance, especially across the analysis-to-action-selection boundary.

Limits: The studies vary and mostly predate LLM systems. Next: do the same tradeoffs appear when generative agents move from analysis to consequential action?

What was reviewed: Structure and relevance screened; not a full evaluation

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Recover interrupted work

Inspect recovery mechanisms without assuming they make every action safe.

temporalio/sdk-python

An established durable-workflow example for inspecting recovery design.

Finding: Deterministic workflows, activities and replay expose resumable state.

Limits: Requires a Temporal service and replay discipline. External effects still need idempotency. README inspected; no runtime test or adoption.

What was reviewed: README reviewed only; no runtime test recorded

Original evidence note

Deterministic workflows, activities, replay and sandboxing expose resumable state. Requires a Temporal service and replay discipline; external effects still need idempotency. Pinned README screen only; no runtime test or adoption.

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hatchet-dev/hatchet

A second recovery design with a recorded version-specific counterexample to consider.

Finding: Durable tasks, execution history and pause/resume expose a recovery design.

Limits: Old retry work advancing after replacement was reported on an earlier release. Current-head behavior was not tested. Requires server and data-retention review; no collaboration benefit established.

What was reviewed: README reviewed only; no runtime test recorded

Original evidence note

Pinned README describes durable tasks, Postgres-backed execution history, retries, pause/resume and worker routing. These expose recovery mechanisms, not safe supersession or agent collaboration benefit. Open issue 4900 reports old retry work advancing after replacement on an earlier release; current-head behavior was not tested. Requires a server and data-retention review before any operational use.

Recorded counterevidence: Publicly reported behavior on an earlier release; not reproduced or verified on this snapshot.

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Reading guide recorded October 24, 2026. Selected from existing appraisals; no new reproduction or adoption claim. Profiles retain their separately dated catalog evidence.

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