The Age of Async Agents — Cognition's Walden Yan & OpenInspect's Cole Murray
A Latent Space podcast episode featuring Cognition's Walden Yan and OpenInspect's Cole Murray discussing the current state of autonomous software engineering agents. Topics include Devin's reported 80% commit rate, spec-to-PR workflows, full VM environments for agents, agent memory, and the emerging pattern of product managers shipping code directly. The conversation covers practical deployment patterns and tooling for async agentic coding workflows.
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AINews: Agents for Everything Else — Codex for Knowledge Work, Claude for Creative Work
A Latent Space daily AI news digest reflecting on the expanding scope of coding agents beyond software development into knowledge work and creative work domains. The piece uses OpenAI Codex and Anthropic Claude as anchoring examples of agents 'breaking containment' from their original coding/assistant niches. Published as a quieter news day commentary, it surveys the broadening agent ecosystem landscape.
GitHub's plan for agentic coding — Kyle Daigle interview on Latent Space
Latent Space interviews Kyle Daigle of GitHub about the company's strategy for agentic coding workflows and the platform pressures created by the explosion in AI-assisted development following Copilot. The discussion covers how GitHub is adapting its infrastructure and product direction to support agents operating at scale. This is a strategic signal from one of the most central platforms in the developer AI ecosystem.
Claude Code, Codex and Agentic Coding #8
Zvi Mowshowitz's eighth installment in his ongoing series tracking the agentic coding landscape, covering developments around Claude Code and OpenAI Codex. As a tier-2 commentary source, the piece synthesizes recent progress and trends in coding agents. The series has been running since the initial wave of excitement around coding agents.
agent-teams-ai: multi-agent orchestration framework with kanban-style oversight
A TypeScript open-source project on GitHub implements a multi-agent system where autonomous agents handle tasks, communicate with each other, and review each other's work, while the user supervises via a kanban board. The framework supports 200+ models across 75+ LLM providers including Codex, Claude, and OpenCode. It has accumulated 1,189 stars with 56 added today, suggesting growing community interest.
Claude Code and What Comes Next
A commentary piece from One Useful Thing examining Claude Code and its implications for AI-assisted software development. The author reflects on what agentic coding tools can accomplish with the right scaffolding and considers near-term trajectories. Published in early January 2026, this represents a tier-2 analyst perspective on Anthropic's coding agent product.
Speeding up agentic workflows with WebSockets in the Responses API
OpenAI published a technical deep dive into the Codex agent loop, detailing how WebSockets and connection-scoped caching were used to reduce API overhead and improve model latency. The post focuses on infrastructure optimizations within the Responses API for agentic workflows. These changes are relevant to developers building multi-step agent pipelines that rely on repeated API calls.
Giving Agents Computers — Ivan Burazin, Daytona
Latent Space interviews Daytona CEO Ivan Burazin about the company's infrastructure for giving AI agents secure compute environments. The discussion covers Daytona's bare metal sandbox architecture, 850K daily runs, 74% month-over-month growth, and their approach to RL-based evaluations for agent workloads. The piece positions Daytona as part of an emerging 'agent cloud' category providing isolated execution environments for autonomous AI systems.
Real AI Agents and Real Work
A commentary piece from One Useful Thing examining the practical deployment of AI agents in real work contexts, framing the tension between human-centered work and AI-generated productivity outputs. The piece appears to analyze how autonomous AI agents are changing knowledge work workflows. Published by a Tier 2 source known for applied AI analysis aimed at practitioners and researchers.


