PodMan — Idea

One-line value prop

PodMan is a real-time AI team coordination agent that watches consented work signals, maintains live project memory, and proactively coordinates collaborators when collisions, blockers, or handoffs emerge before anyone has to ask.

Problem

Teams working on the same project lose time because progress is fragmented across people, editors, terminals, and half-finished messages. Coordination gaps — a completed endpoint, a resolved blocker, two engineers duplicating work — are discovered too late, causing idle time, broken handoffs, and missed dependencies.

Slack doesn't help. Stand-ups are too slow. GitHub only knows pushed state.

Solution

PodMan is an ambient AI agent that:

Watches each engineer's consented LiveKit screen-share signal
Extracts structured context using Gemini Vision — current file, inferred task, terminal state
Maintains a shared live model in MongoDB Atlas — observations, collisions, interventions, outcomes, and graph memory
Detects coordination risks: same-file collision, blocker detected, duplicate work
Sends the least intrusive intervention first: card, Hermes message, and urgent voice only when needed

The AI's job is not to chat. It is to notice what teammates miss and say so, exactly when it matters.

Target user

Small software teams: hackathon squads, startup engineering teams, student dev teams collaborating in real time on a shared codebase.

Core AI job

Maintain per-person live context (file, task, terminal)
Infer shared project state (who owns what, what's blocked, what's ready)
Detect 3 coordination risk types:
- DEPENDENCY_READY — engineer A was waiting on work engineer B just completed
- BLOCKER_DETECTED — engineer appears stuck; another teammate can unblock
- DUPLICATE_WORK — 2+ engineers working on the same file simultaneously
Generate a short intervention message
Deliver it as a LiveKit data message, with Gemini TTS audio reserved for urgent escalation

How it fits the Continual Learning track

PodMan builds outcome-backed team memory in MongoDB that persists across sessions:

Session 1: PodMan observes work, predicts a collision, sends an intervention, and stores the outcome
Session 2+: PodMan recalls the exact signature and changes the graph or behavior

The system gets demonstrably more useful the more it is used, with no user configuration required. That is the track definition met exactly.

Architecture (one paragraph)

Each engineer opens a browser PWA on their laptop. The PWA shares live IDE context through LiveKit screen sharing, and the local git watcher writes dirty/unpushed state to MongoDB. The backend agent calls Gemini Vision to extract structured context, writes observations and collisions to MongoDB Atlas, recalls accepted or dismissed outcomes, and routes the smallest useful intervention. Cards and Hermes messages are default; Gemini TTS through LiveKit is reserved for urgent escalation. No Slack. No tab switching. No interruption to the editor flow.

Demo wow moment

Alice is building the auth endpoint. Carol is visibly blocked — her terminal shows connection refused. PodMan detects the blocker and says aloud: "Carol, looks like you're waiting on auth. Alice is actively building it — hang tight."

Two minutes later, Alice's server starts. PodMan says: "Carol, Bob — Alice just got the auth endpoint running. You're clear to integrate."

Nobody asked. Nobody pinged anyone on Slack. PodMan just knew.

What PodMan is NOT

Not a chat interface
Not a dashboard product
Not raw surveillance — engineers consent by joining the room and sharing their screen
Not a task manager
Not a GitHub integration (v1)

Prize alignment

Prize	How PodMan earns it
Best Gemini 3.5 / 2.5	Gemini Vision for screen understanding + Gemini TTS for urgent voice output
Best LiveKit	LiveKit is the real-time backbone for room presence and voice delivery — load-bearing, not decorative
Best DigitalOcean	Hermes deployed on DigitalOcean App Platform; MongoDB Atlas on DO-adjacent infrastructure

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