Agent Evals Become a Discipline Separate from Model Evals
Reliable agents require evaluation of trajectories, tools, state, recovery, and outcomes rather than grading only the final answer.
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Dated, source-linked observations imported from the QWG AI archive.
These are evidence records, not finished editorial conclusions.
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.
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.
Reliable agents require evaluation of trajectories, tools, state, recovery, and outcomes rather than grading only the final answer.
The archive captures Asteroid as a dated public record from Asteroid. It documents model output moving from plain answers into generated task interfaces and actions and is retained as supporting evidence for the task-specific AI interfaces trend.
The archive captures Walkinglabs / Learn Harness Engineering as a dated public record from Walkinglabs / Learn Harness Engineering. It documents evaluation, review, and observability becoming the bottleneck after generation accelerates and is retained as pressure-testing evidence for the verification bandwidth trend.
Browser guidance, inspection, interaction, and screenshots make frontend work observable enough for agents to test rather than merely generate.
Anthropic's legal repository expresses domain knowledge, procedures, and tools as installable modules for repeatable professional work.
The archive captures Google / Gemini Models as a dated public record from Google / Gemini Models. It documents software exposing explicit capabilities, permissions, and machine-readable actions and is retained as supporting evidence for the agent-ready software trend.
Search is extending from retrieval and answers into tasks, tool use, and guided execution inside a familiar high-traffic interface.
Stitch combines editable UI, design instructions, reusable skills, and handoff context instead of stopping at attractive screenshots.
A common memory layer reduces the cost of switching coding clients and moves context ownership outside any one model interface.
A public X post from Gemini CLI as a public source in its own right flags Transitioning Gemini CLI users to Antigravity CLI We are unifying our efforts around a single harness and platform, Google Antigravity with four distinct surfaces: • Antigravity 2...
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