Tag

Harness

All content about Harness, organized for fast scanning.

6 itemsUpdated Jun 10, 2026
In Brief

Recent developments in autonomous coding agents highlight a shift towards goal-driven loops that enhance their efficiency and effectiveness. Innovations include open-source tools for vulnerability patching and improved architectural frameworks that significantly increase developer productivity. Additionally, there is a growing focus on creating long-running agents capable of maintaining context and memory across sessions, addressing current limitations in agent performance.

Timeline

  1. Insight

    Addy Osmani’s “Loop Engineering” hints at autonomous coding agents

    Addy Osmani says coding agents may be shifting from prompt-by-prompt use to goal-driven loops that plan, split work, verify results, and repeat. His thread maps the core building blocks—and the token, security, and “exit condition” pitfalls. [https://x.com/addyosmani/status/2064127981161959567](htt…

  2. News

    How to build AI agents from first principles, not frameworks

    Anshuman Mishra lays out a bottom-up recipe for agent training using a tiny text-to-diagram task. The key: start with a strict environment and reward loop, use SFT to learn valid actions, then apply RL to optimize behavior—and watch for reward hacking.

  3. News

    AI’s next leap: long-running agents that persist beyond chat

    A recent article by Addy Osmani explores “long-running agents” that can keep working across sessions without losing state. It outlines the key architectural patterns and why today’s agents still stall when context, memory, and verification break down.

  4. Insight

    New paper says agentic coding scaling needs smarter reuse

    Joongwon Kim and coauthors argue test-time scaling for long-horizon coding agents depends less on more sampling and more on carrying forward useful rollout information. Their summary-based RTV and PDR methods boost results on SWE-Bench Verified and Terminal-Bench v2.0.