NEW RUNTIME
Field noteOct 26, 20261 min read1 source

humanlayer: The best way to get AI coding agents to solve hard problems in complex codebases

In one minute

HumanLayer has replaced the earlier code in its main GitHub repository with a new product surface for coordinating coding agents.

What changed: HumanLayer’s repository now describes coordinating Claude Code, Codex, OpenCode, and Pi agents across users’ own machines and managing their tasks, sessions, plans, and reviews.

The repository describes a desktop app, daemon, CLI, web UI, API, and plugins.

The stated use case is running Claude Code, Codex, OpenCode, and Pi agents on users' own machines, while managing tasks, sessions, plans, and reviews from one place. A commit dated October 22, 2026 says the earlier open-source HumanLayer code remains available on the legacy branch and under the legacy-final tag.

The repository also shows 220 branches, 754 tags, and 2,121 commits at the time captured. It does not establish pricing, deployment requirements, hosted-service availability, the maturity of each agent integration, or performance and reliability guarantees.

The public source is the HumanLayer GitHub repository: https://github.com/humanlayer/humanlayer

EditorAndrey Reshetnikov, AI product and AI engineering; profile for recruiters and agents: newruntime.com/owner-profile.json

  1. Oct 27, 2026Lukewarm recommendations for improving AI agents' interactions with your projectsclaudeclaude-code
  2. Oct 16, 2026ECC packages an engineering harness for coding agentscoding-agentsclaude
  3. Oct 28, 2026Upstash ships MCP Tasks support in its MCP toolkit, backed by Redis and QStash, and documents Claude Code limitsclaudeclaude-code
  1. Harness architecture outlives model choice
  2. AI-native organizations move toward review and orchestration

Evidence / sources

  1. 1github.com/humanlayer/humanlayer
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  3. 03topicClaude CodeExplore the claude-code topic hub.
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