Raw Signals

Dated, source-linked observations imported from the QWG AI archive.
These are evidence records, not finished editorial conclusions.

1332 public records15 reviewed patternsOpen JSON index

Key takeaway

Across 1332 observations, most signals relate to model behavior, evaluation discipline, and real-world agent operations. Strong evidence clusters around tooling, memory, routing, and productized agent execution.

agentscoding agentsagent harnessagent runtimemodelsagent protocols

What this means

Teams are moving from experiments to systems. The emphasis is on verifiable behavior, operational safety, and measurable outcomes—especially in agent memory, evaluation rigor, and forward-deployed engineering.

Filters (current page)

1-10 of 10 matching raw signals on this page
  1. lusters-91fb66

    Impactful scheduling for GPU clusters

    Ai2 says it replaced a priority-based GPU scheduler with a system combining GPU-time budgets, hierarchical fair-share allocation and a workload minimum-runtime contract.

    notableresearch
    source-linked
    1
  2. -claude-72da39

    The Gauntlet Loop: The Prompting Method Behind Claude of Duty

    Matt Shumer’s article describes the Gauntlet Loop, a method for repeated agent improvement: give a lead agent a goal and a concrete quality reference, split the work into parts, and have separate critics compare results against that reference.

    notableupdate
    source-linked
    1
  3. t-using-810711

    A new feature for my blog, built using my voice

    Simon Willison shipped a newsletters archive for his blog after building most of it through Codex voice mode in the ChatGPT desktop app, connected to a local development environment.

    notableannouncement
    source-linked
    1

Source & exports

Primary indexes and programmatic access to this dataset.

Archive contractEnglish normalized copy, Telegram provenance, public sources only
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