IST: Running AI Coding Sessions as a Team

Most of us use AI to write code the same way: one chat window, one agent, one task at a time. It is a good default — until the work outgrows a single conversation, and that one thread becomes the bottleneck.

IST takes a different approach. Instead of a single agent, it runs multiple sessions that coordinate like a team: a manager that plans and delegates, and workers that carry out tasks in parallel. The manager rarely touches the code itself. It decomposes the work, hands each piece to a worker, reviews what comes back, and keeps everything moving toward the goal.

Here is what that looks like when several sessions run at once:

A team, not a chatbot

A single agent is a capable individual contributor. But an individual has limits: one context window, one train of thought, one thing in flight. Scale the ambition — a migration across dozens of files, a feature that spans several services, a batch of independent tasks — and you feel those limits fast.

IST reframes the unit of work from a conversation into a team:

• Sessions are independent agents, each with its own context and workspace. You start and manage them with a single command.
• Messaging lets sessions talk to one another — a manager assigns a task, a worker reports back — so coordination is explicit rather than improvised.
• Monitoring watches every session at once, surfacing the moment one needs a decision or finishes its work, so nothing stalls in silence.

On top of these primitives sits a simple pattern we call TDA (Top-Down Agent): the manager owns the plan and the delegation; workers own the execution. The manager stays at altitude — deciding what and who — while workers handle the how.

Why it matters

Parallelism is the obvious win: several workers can move on several fronts while the manager holds the thread. But the quieter benefit is separation of concerns. The manager is never buried in diffs, so it stays free to plan, sequence, and verify. Workers are never distracted by the big picture, so each one focuses on a single well-scoped task and returns a clean result. The structure itself makes the work more legible — and, in our experience, more correct.

Try it yourself

The best way to understand IST is to run it. Our getting-started guide takes you from zero to your first manager-and-worker setup in a few minutes:

→ Getting Started with IST

If you build something with it — or break something interesting — we would love to hear about it. Follow along as we build MicrowiseAI in the open.