AI Coding Live News

OpenAI Agents API ships Auto Review, async compaction, experimental time awareness and mid-session tool updates

The OpenAI Developers account shared a post by Steve (@stevendcoffey), who works on the API at OpenAI, listing five Agents API updates this week: Codex-style Auto Review of commands before execution, compaction that runs in the background, an experimental time-awareness feature, updating a session's tools at any time, and automatic caching of system prompts across all sessions. As of writing, the official API changelog does not list these items yet.

Key Takeaways

  • Five updates: Auto Review, async compaction, time awareness (experimental), updating session tools at any time, and automatic cross-session system prompt caching
  • Auto Review mirrors the Codex mechanism and evaluates commands for potential bad behavior before they run
  • Time awareness lets the model act on time-boxed instructions such as "timebox CI fixes to 10 minutes"
  • The Agents API entered public beta on September 10, and this is another round of features within 7 weeks (after computer use on Sep 29, sandbox prewarming on Oct 9 and Ultrafast mode on Oct 16)
  • OpenAI has published no latency or cost-saving numbers, and the changelog has not listed these items yet
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humans& releases its first model, Ampersand v0.1: a group-collaboration model trained from GLM 5.3, now open via its Agents API

On Oct 20, AI startup humans& released its first model, Ampersand v0.1, pitched as a collaborator that helps groups reach individual and shared goals rather than an assistant that completes tasks alone. It is trained from Z.ai's GLM 5.3 (about 744B total, about 40B active parameters) with long-horizon multi-party RL against simulated users played by humans&'s own user model, Persimmon. It is available now, with no waitlist, through an API compatible with OpenAI's Agents API.

humans& releases its first model, Ampersand v0.1: a group-collaboration model trained from GLM 5.3, now open via its Agents API

Key Takeaways

  • Base: GLM 5.3 MoE with about 744B total and about 40B active parameters and a 1,048,576-token context (official model card)
  • Long-term collaboration simulation (vendor figures): 12.94 for Ampersand versus 9.89 for base GLM 5.3
  • Collaborative Intelligence teamwork 59.1% (GLM 5.3: 54.3%); CooperBench cooperative success 39.0% versus 17.3% for GLM 5.3
  • Trade-off: SWE-bench Pro v2 (Hard-51) 82.4%, slightly below the base model's 84.3%; humans& also admits it sometimes over-coaches
  • Access: model ID ampersand-v0.1, usable with the official OpenAI SDK pointed at the humans& base URL
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Open Managed Agents open-sources a self-hosted managed-agent platform for Node, Docker, or Cloudflare

@DanKornas highlighted Open Managed Agents (github.com/openma-ai/open-managed-agents), an Apache-2.0 self-hosted platform for builders who want managed-agent workflows without vendor lock-in: durable sessions, sandboxed tools, memory, encrypted credentials, and crash recovery on Node+Docker or Cloudflare Workers, with Claude Managed Agents API and OpenAI SDK paths via /openai/v1.

Key Takeaways

  • Self-host managed-agent workflows with durable sessions, memory, and crash recovery.
  • Supports sandboxed tools, private tools, and MCP; bring your own model keys.
  • Runs on Node/Docker or Cloudflare Workers; Claude Managed Agents API and OpenAI SDK compatible.
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OpenAI Agents API Adds Production Subagent Delegation & Parallel Workflow Orchestration

OpenAI upgraded its Agents API to generally support production-grade subagent delegation. A primary orchestrator agent can dynamically fork hundreds of lightweight, specialized child agents to execute asynchronous multi-file refactors and CI test repairs before synthesizing results back to main context.

Key Takeaways

  • Primary agent dynamically forks hundreds of dedicated child agents for parallel workloads
  • Native hierarchical context scoping and sandbox fencing eliminate single-thread bottlenecks
  • Radically simplifies enterprise-scale distributed agent workflow orchestration
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OpenAI launches Agents API: managed cloud agents on Codex harness with tools and sandboxes

OpenAI launched the Agents API—a managed cloud agent service powered by the Codex harness for orchestration, long-running sessions, and tool use. Bring connectors, attach any sandbox, and run agents with Astra.

Key Takeaways

  • Managed Agents API ships on the Codex harness.
  • Supports tools/connectors, arbitrary sandboxes, and long-running orchestration.
  • Aimed at builders running cloud agents with Astra; official blog live.
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