AI Agent Harness Research

A daily engineering digest for agent harness design, evaluation infrastructure, observability, replay, and production agent operations. Last updated 2026-05-29 UTC.

10 Recent Research Publications

2026-05

Automated Benchmark Auditing for AI Agents and Large Language Models

Modern AI benchmarks operate at a complexity that outpaces traditional verification methods. Tasks authored by domain experts often contain implicit assumptions, incomplete environ...

2026-05

Anticipate and Learn: Unleashing Idle-Time Compute in Proactive Agents

While AI agents demonstrate remarkable capabilities in reasoning and tool use, they remain fundamentally reactive: they compute responses only after explicit user prompts. This par...

2026-05

Behind EvoMap: Characterizing a Self-Evolving Agent-to-Agent Collaboration Network

Agent-to-Agent (A2A) networks enable autonomous AI agents to collaborate by sharing reusable problem-solving instructions. However, how these decentralized ecosystems operate in pr...

2026-05

Meta-Engineering Harnesses for AI-Native Software Production: A Contract-Driven Adversarial Verification Architecture with Early Deployment Report

AI-native software development is often evaluated at the level of individual models, prompts, or generated artifacts. This framing is insufficient for production environments where...

2026-05

Insuring Every Action: An Authority Frontier Framework for Runtime Actuarial Control of Autonomous AI Agents

Autonomous AI agents increasingly issue side-effect-bearing actions: database mutations, refunds, payments, external commitments. We propose the ...

Daily Harness Engineering Blogs (51 published)

2026-05-29

Replayable Agent Harnesses: 2026-05-26

how to design trace capture, deterministic replay, and failure triage for coding agents

2026-05-29

Evaluation Isolation for Agent Tools: 2026-05-26

how to separate model quality from harness bugs, flaky tools, and contaminated benchmarks

2026-05-29

Coding Agent Benchmark Design: 2026-05-29

how to design representative benchmarks that measure real engineering output, not just code completion

2026-05-29

Failure Taxonomy for Agent Systems: 2026-05-29

how to classify agent failures into contract violations, environment drift, model hallucination, and budget overflow

2026-05-29

Multi-Agent Communication Patterns: 2026-05-29

how to design worker delegation, team-mode review, and supervisor loops for multi-agent systems

2026-05-29

Model Selection for Coding Agents: 2026-05-29

how to evaluate LLM providers on pass rate, token cost, latency, and harness compatibility