Murmell is a browser canvas where real coding agents run on cloud machines and share one project directory, each reserving a file before it writes. Agents like Claude Code and Codex run in isolated terminals on remote machines, collaborating through file-locking to prevent overwrites. The canvas shows live terminal output from each agent in separate windows, with cursors labeled by agent name. Users can share read-only links (unlimited) or edit links (plan-limited) to collaborate in real-time. Work is automatically committed to a private Git repository per project, and agents run on persistent cloud sandboxes that survive tab closure. Murmell solves the chaos of multiple AI agents editing the same file simultaneously by enforcing reservation-based file access, making multi-agent coding practical and safe.
codemap is an MIT-licensed project brain for AI coding tools that gives LLMs instant architectural context from your codebase without burning tokens. It generates a fast tree/context view, dependency flow, dependency blast-radius analysis, and a layered handoff format for cross-agent continuation, then exposes everything through a JSON context bundle and an MCP server compatible with Claude Code and Codex. A built-in Codex plugin and community skill registry make it easy to install and share. Developers use codemap to onboard agents to large repos in seconds, keep session continuity across handoffs, and scope the impact of a change before running it.
Type.com is a multiplayer AI workspace where teams collaborate with Claude, Codex and other models in a shared company context. It brings conversations, files, skills, integrations and automations into collaborative Spaces instead of leaving useful work trapped in individual chat windows. Marketing, sales, support and operations teams can tag Type from Slack or email, share access through role-based permissions, and build custom dashboards or internal apps grounded in company knowledge. Type also supports OAuth, MCP and API connections, with granular controls for users and spaces. It is notable now because its Product Hunt launch presents a practical answer to the coordination problem emerging as teams adopt multiple coding and general-purpose agents. The official site confirms a shipped cloud workspace with desktop and mobile access, not merely an agent concept.
Ollama is a local AI platform for running, managing, and sharing open models on your own machine or private infrastructure. It makes it easy to pull models, serve them through an API, and integrate local inference into developer workflows without relying on a fully managed cloud stack. Teams use Ollama for privacy-sensitive assistants, internal tools, offline experimentation, and rapid testing of open-weight models across laptops, workstations, and servers. It is especially useful for developers, operators, and AI builders who want quick setup with less operational overhead. What makes Ollama distinctive is how approachable it is: it packages model runtime, distribution, and deployment into a streamlined experience that helps people get productive with local AI in minutes instead of spending days on configuration.
Ahmad Al-Dahle, the former Meta AI lead now CTO of Airbnb, shares how the company turned 60% of its code over to AI and shipped 80% more features. The real story is how Airbnb collapsed handoffs, built a queryable context graph, and restructured teams around outcomes.
Four days after OpenAI's DevDay, ecosystem signals reveal the real shift: decision models becoming standard infrastructure, platforms tightening permissions, and governance hardifying across the industry.
OpenAI's DevDay 2026 introduced persistent agents (Dots) and GPT-6.1 Sol, signaling a shift from token-based to compute-based pricing. What it means for startups and enterprises.