Agor's spatial canvas, cards, and zones

Summary 
In this episode Max Beauchemin explores how multiplayer, multi‑agent engineering is reshaping individual and team velocity for building data and AI systems. Max shares his journey from Airflow and Superset to going all‑in on AI coding agents, describing a pragmatic “AI‑first reflex” for nearly every task and the emerging role of humans as orchestrators of agents. He digs into shifting bottlenecks — code review, QA, async coordination — and how better DevX/AIX, just‑in‑time context via tools, and structured "context as code" can keep pace with agent‑accelerated execution. He then dives deep into Agor, a new open‑source agent‑orchestration platform: a spatial, multiplayer canvas that manages git worktrees and shared dev environments, enables templated prompts and zone‑based workflows, and exposes an internal MCP so agents can operate the system — and each other. Max discusses session forking, sub‑session trees, scheduling, and safety considerations, and how these capabilities enable parallelization, handoffs across roles, and richer visibility into prompting and cost/usage—pointing to a near future where software engineering centers on orchestrating teams of agents and collaborators. Resources: agor.live (docs, one‑click Codespaces, npm install), Apache Superset, and related MCP/CLI tooling referenced for agent workflows. 

Announcements 

• Hello and welcome to the AI Engineering Podcast, your guide to the fast-moving world of building scalable and maintainable AI systems
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• Your host is Tobias Macey and today I'm interviewing Maxime Beauchemin about the impact of multi-player multi-agent engineering on individual and team velocity for building better data systems

Interview

• Introduction
• How did you get involved in the area of data management?
• Can you start by giving an overview of the types of work that you are relying on AI development agents for?
• As you bring agents into the mix for software engineering, what are the bottlenecks that start to show up?
• In my own experience there are a finite number of agents that I can manage in parallel. How does Agor help to increase that limit?
• How does making multi-agent management a multi-player experience change the dynamics of how you apply agentic engineering workflows?

Contact Info

• LinkedIn

Links

• Agor
• Apache Airflow
• Apache Superset
• Preset
• Claude Code
• Codex
• Playwright MCP
• Tmux
• Git Worktrees
• Opencode.ai
• GitHub Codespaces
• Ona

The intro and outro music is from Hitman's Lovesong feat. Paola Graziano by The Freak Fandango Orchestra/CC BY-SA 3.0