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feat(task-2b): git watcher script + docs update

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- Add scripts/podman-agent.mjs — polls git every 15s, upserts changedFiles/
  diffStat/recentCommit/branch into MongoDB engineer_states collection
- README: add "Git watcher" section with per-laptop demo commands for each
  team member (alice/bob/carol --pod demo-pod)
- PLAN.md: mark scheduled git truth ✅ partial, update acceptance checklist,
  clarify remaining fusion step (GIT_REPORT data channel wire-up still needed)

Co-Authored-By: Claude Sonnet 4.6 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01AaCFWMkYQmTcuPsxaaACft
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Ramis
2026-06-27 16:48:22 -07:00
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README.md
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@@ -70,3 +70,34 @@ pnpm install
pnpm --filter backend dev # Hermes on :8787 pnpm --filter backend dev # Hermes on :8787
pnpm --filter frontend dev # PWA on :5173 pnpm --filter frontend dev # PWA on :5173
``` ```
---
## Git watcher — run this on every demo laptop
Each engineer runs this in a terminal before the demo. It polls the local git working tree every 15 seconds and writes git state to MongoDB so PodMan has deterministic dirty/unpushed truth that vision alone cannot reliably infer.
```bash
# from the repo root
node scripts/podman-agent.mjs --name <yourname> --pod <podId>
```
**Demo setup (one command per laptop):**
```bash
# Alice's laptop
node scripts/podman-agent.mjs --name alice --pod demo-pod
# Bob's laptop
node scripts/podman-agent.mjs --name bob --pod demo-pod
# Carol's laptop
node scripts/podman-agent.mjs --name carol --pod demo-pod
```
The script logs one line per cycle — branch, changed file count, and latest commit. Leave it running in a background terminal tab throughout the session. Stop with `Ctrl+C`.
**Requirements:**
- `MONGODB_URI` must be set — either exported in the shell or present in `backend/.env`
- Run `pnpm install` first so `mongodb` is in workspace `node_modules`
- Must be run from the repo root (the script resolves `backend/.env` relative to its own path)
docs/PLAN.md
+644 -166
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@@ -1,246 +1,724 @@
# PodMan — Implementation Plan (12 hours) # PodMan - Canonical Master Plan
> Architecture locked. See `docs/idea.md` for concept, integration specs for details. > Source of truth for PodMan product intent, current implementation truth, demo
> Tasks ordered by dependency and demo criticality. Never cut items above the cut line. > strategy, public interfaces, risks, sponsor story, and next build order.
>
> If this file conflicts with `README.md`, `docs/idea.md`, `docs/livekit.md`,
> `docs/gemini.md`, `docs/mongodb.md`, `docs/digitalocean.md`,
> `docs/demo-setup.md`, or `docs/superpowers/specs/*`, follow this file and
> treat the older docs as reference material to reconcile later.
--- ---
## What we are building ## 1. Product thesis
Engineers join a LiveKit room with earbuds. The PodMan agent (`backend/src/agent.ts`) subscribes to each engineer's screen-share track, samples frames at ~1fps, calls Gemini Vision, detects collisions, and publishes interventions via LiveKit data channel + voice. MongoDB Atlas stores observations, collisions, interventions, and outcomes — persisting across sessions for continual learning. **PodMan sees active work before it becomes visible to GitHub, remembers how the
team works, researches better paths in the background, and coordinates teammates
without being intrusive.**
**Actual architecture (differs from original spec):** Screen frames flow through the LiveKit room (agent subscribes to screen tracks), not via HTTP POST /ingest from the PWA. The agent runs as a separate process (`pnpm dev:agent`). The HTTP server handles token minting, pods CRUD, memory stats, and outcome recording. GitHub knows pushed branches, PRs, issues, and comments. It cannot see the most
expensive coordination failures while they are still forming on laptops: two
engineers editing the same unpushed file, someone blocked on an endpoint a
teammate is nearly done with, duplicated work starting silently, or a team
walking into a dead-end implementation path.
**Demo:** Alice builds auth endpoint. Carol is blocked. PodMan notices, warns Carol. Alice's server starts. PodMan tells Carol and Bob they're clear to integrate. No Slack. No asking. PodMan puts engineers in a consented LiveKit pod, watches live IDE/screen
context, fuses that with scheduled local git reports, GitHub state, MongoDB team
memory, and background research, then routes only useful interventions through
Hermes. The default is a small visual card. Hermes can message teammates when
the team needs coordination. Voice is reserved for urgent escalation.
**One-line product definition:** PodMan is a non-intrusive, continual-learning
team assistant for active coding.
**One-line demo promise:** PodMan notices live work, finds a better path,
remembers a previous intervention, and escalates only when the team actually
needs it.
--- ---
## Status legend ## 2. Product contract
- ✅ Done and deployed on server
- ⚠️ Partial — code exists, needs work ### Inputs
- ❌ Not started
- **Live IDE/screen context:** engineers join a LiveKit room and publish screen
share so the backend agent can sample real work in progress.
- **Scheduled local git state:** each laptop should report dirty files,
unpushed commits, branch, and latest commit about every minute. This is the
deterministic fallback for facts vision cannot reliably infer.
- **MongoDB team memory:** ownership, current tasks, blockers, repeated
mistakes, preferred tools, decisions, intervention history, and outcomes.
- **GitHub repo state:** public repo metadata, branches, PR artifacts, and
issue/PR state when it exists.
- **Background research signals:** tool, repo, skill, package, docs, and
dead-end evidence discovered while teammates are working.
### Outputs
- **Default:** small visual intervention card in the PodMan frontend.
- **Coordination:** Hermes message to the right teammate(s) or project channel.
- **Urgent escalation:** voice only when timing or risk justifies interruption.
- **Action path:** optional sync PR, research recommendation, summary, fix
suggestion, or teammate notification.
### Memory rules
- Remember team-level work patterns, not raw screen recordings.
- Store structured observations, collisions, interventions, outcomes, and pod
state.
- Add exact-signature recall before vector recall: normalized file, symbol,
engineer pair, event type, and accepted/dismissed outcome.
- Privacy must stay explicit: engineers consent by joining the pod and sharing
screen context; do not store raw screenshots, full recordings, or secrets.
### Non-goals
- Not a dashboard as the product center.
- Not a screenshot analyzer with no action loop.
- Not sponsor-padding; every sponsor technology must be load-bearing or clearly
marked as optional polish.
- Not a task manager, Slack clone, full auth system, or general surveillance
tool.
--- ---
## Critical path — must ship for demo ## 3. Track fit: Continual Learning
### 1. Environment + health check PodMan fits **Continual Learning** because the system gets more useful from team
**Status: ✅ Done** history and intervention outcomes.
- [x] `GET /health` returns `{ ok: true }` — live at `http://165.22.129.249:8787/health` - **Team model:** observations build ownership, hotspot, blocker, tool, and
- [x] MongoDB connection established in `backend/src/memory/db.ts` — `collections()` export decision memory per pod.
- [x] Pods CRUD: `GET/POST /api/pods`, `GET/DELETE /api/pods/:id`, `POST/DELETE /api/pods/:id/members` - **Outcome loop:** accepted, dismissed, and confirmed interventions become
- [x] Backend running in tmux on DO droplet (`pnpm dev` via `tsx watch src/server.ts`) supervision for future thresholds and routing.
- [ ] Root `.env` not present — `backend/.env` has creds, sufficient for current setup - **Session compounding:** a later similar situation should reference prior
memory, choose a better action sooner, or lower the noise level.
- **Visible demo proof:** the first intervention writes memory; the second
similar situation retrieves it and says, in effect, "I have seen this pattern
before."
**Actual files:** `backend/src/memory/db.ts`, `backend/src/server.ts`, `backend/src/env.ts` The learning proof should not depend on Atlas Vector Search being finished.
Exact MongoDB recall is enough for the MVP learning beat.
--- ---
### 2. PWA frame capture ## 4. Current implementation truth
**Status: ✅ Done (different approach than originally planned)**
Original plan: PWA captures JPEG every 30s → POST /ingest. Actual: PWA publishes screen as LiveKit video track → agent subscribes and samples at ~1fps using `livekit-client-node` + `sharp`. Verified on `2026-06-27` from local repo inspection, authenticated `gh`, and
the current remote plan commit.
- [x] `frontend/src/lib/pod.ts` — `joinPod()` connects to LiveKit, publishes screen + mic ### GitHub state
- [x] `backend/src/agent.ts` — subscribes to `SOURCE_SCREENSHARE` tracks, throttles at `SAMPLE_INTERVAL_MS`
- [x] Resize to max 1280px wide, JPEG quality 70 via `sharp`
- [x] Dev mock-join fallback when LiveKit unconfigured
- [x] `frontend/src/livekit/useScreenPublish.ts` — React hook for screen track
**Actual files:** `backend/src/agent.ts`, `frontend/src/lib/pod.ts`, `frontend/src/livekit/useScreenPublish.ts` - Repo: <https://github.com/karti-ai/podman>
- Visibility: public
- Default branch: `main`
- Current local branch: `main`
- Local branch state during this rewrite: behind `origin/main` by two commits
- Issues: none
- PRs: none
- `origin/main` latest relevant commits:
- `8271188 feat(frontend): live room view, beat connectivity test, session resume`
- `65a0791 docs(plan): audit server state + mark tasks 1-5 done, reflect actual arch`
### Working / started
- Monorepo packages exist: `frontend`, `backend`, `shared`, `database`, and
`infra`.
- Backend is split into two processes:
- API service in `backend/src/server.ts`.
- LiveKit agent worker in `backend/src/agent.ts`.
- Backend API exposes:
- `GET /health`
- `POST /api/token`
- `POST /api/sync-pr`
- `POST /api/outcome`
- `GET /api/memory/stats`
- `GET /api/pods`
- `POST /api/pods`
- `GET /api/pods/:id`
- `PATCH /api/pods/:id`
- `DELETE /api/pods/:id`
- `POST /api/pods/:id/members`
- `DELETE /api/pods/:id/members/:name`
- Remote API health check returned `{"ok":true}` at
`http://165.22.129.249:8787/health` during verification.
- The LiveKit agent uses `@livekit/rtc-node` to join as `podman-agent`, subscribe
to `TrackSource.SOURCE_SCREENSHARE`, sample frames near 1 fps, convert frames
to RGBA, and encode downscaled JPEGs with `sharp`.
- Gemini vision is wired in `backend/src/vision/gemini.ts` with JSON structured
output, response schema, low media resolution, and model ID from env.
- Collision detection exists and groups engineer contexts by normalized file,
then fires when 2+ engineers touch the same file and at least one unpushed or
dirty signal exists.
- Shared LiveKit data topic and wire messages exist:
- topic: `podman.intervention`
- messages: `COLLISION`, `VOICE_CUE`, `ACK`, `GIT_REPORT`
- MongoDB persistence groundwork exists for observations, collisions,
interventions, outcomes, and pods.
- Frontend has pod selection, pod join, post-join pod view, LiveKit join helper,
and dev-mode fallback.
- `origin/main` adds live room participants, active-speaker state, session
resume, a "Play beat" audio connectivity test, and a deliberate "Share my
screen" button that publishes with `Track.Source.ScreenShare`. Merge that
remote commit before doing more frontend work on the local checkout.
- DigitalOcean infra scaffolding exists:
- `infra/.do/app.yaml` is the split App Platform direction.
- `infra/app.yaml` is an older single-service backend spec and should be
treated as legacy until reconciled.
### Server snapshot
From the remote plan snapshot and health check on `2026-06-27`:
- Backend API: running on `http://165.22.129.249:8787` and `/health` returned
`{"ok":true}`.
- Frontend: reported running on `:81`; port `80` was already taken.
- Agent worker: reported not running; it still needs LiveKit credentials and
`pnpm --filter @podman/backend dev:agent`.
- Treat this as operational evidence, not architecture truth. Reverify before
demo.
### Partial / stubbed
- `backend/src/voice/live.ts` logs only; it does not publish real voice/audio
into LiveKit yet.
- Hermes is a product/action/messaging layer in the plan, but the current repo
does not yet implement a complete Hermes notification bridge.
- `backend/src/memory/vectors.ts` is not a real Voyage/Atlas Vector Search
implementation yet.
- Exact-signature recall is the required MVP fallback before vectors.
- `backend/src/memory/policy.ts` is a simple gate; it does not learn thresholds
from outcomes yet.
- `POST /api/sync-pr` creates a PR artifact path but does not yet build a
meaningful sync diff.
- Frontend `PodView` has only a placeholder intervention area unless/until live
intervention rendering is wired.
- Browser screen publishing exists, but the active join path must be proven to
tag tracks as screen share so the backend agent can filter them correctly. The
`origin/main` screen-share button appears to address this; local code remains
behind until that commit is merged.
- `GIT_REPORT` exists in shared types and agent handling. `scripts/podman-agent.mjs`
is the finished per-laptop git sidecar — polls every 15 s, upserts git fields
to `engineer_states` collection. Not yet wired to publish a `GIT_REPORT` data
channel message into the LiveKit room (agent fusion step still needed).
- Background research recommendations are a product requirement and demo goal,
not an implemented research agent yet.
- Deployment reliability is partial; API health is reachable, but API/static
site/worker together must still be reverified before demo.
- Env docs are inconsistent: backend defaults are `gemini-3.5-flash` and
`gemini-3.1-flash-live-preview`, while `.env.example` still lists older
Gemini model names.
### Not yet proven
- Real browser -> LiveKit room -> backend agent screen-frame capture end to end.
- Real Gemini inference from a live shared IDE frame using the stage key/model.
- Real data-channel intervention card rendering in the active frontend.
- Hermes message routing to teammates.
- Voice escalation heard by participants through LiveKit.
- A meaningful real sync PR flow with correct GitHub scopes and artifact.
- Atlas Vector Search / Voyage recall path.
- DigitalOcean static site + API service + LiveKit agent worker all running
together.
- Background research recommendation that is both timely and evidence-backed.
--- ---
### 2b. Local git watcher script ## 5. Architecture to build toward
**Status: ❌ Not started**
- [ ] `scripts/podman-agent.mjs` — CLI script polling git every 15s, writing to MongoDB ```
- [ ] Args: `--name alice --pod demo-pod` Engineer browser PWA
- [ ] Every 15s: `git status --short`, `git diff --stat HEAD`, `git log --oneline -1`, `git branch --show-current` - joins a pod room
- [ ] Upsert into `observations` collection — update only git fields, leave vision fields untouched - publishes screen share and optional mic
- [ ] Graceful exit on Ctrl+C - receives intervention cards and voice
|
**Usage:** v
```bash LiveKit room
node scripts/podman-agent.mjs --name alice --pod demo-pod - one room per pod
- screen-share tracks are the live work signal
- small reliable data packets carry interventions
|
v
PodMan backend agent worker
- @livekit/rtc-node room participant
- screen-track subscription
- frame throttle and JPEG encode
- Gemini structured vision
- scheduled GIT_REPORT fusion
- GitHub state fusion
- collision, blocker, duplicate-work, and dead-end detection
- MongoDB memory recall and policy
|
v
Hermes action layer
- visual card routing
- teammate messages
- urgent voice escalation
- optional research/action/sync PR workflows
|
v
Backend API + MongoDB + GitHub
- token minting, pod CRUD, outcomes, memory stats
- observations, collisions, interventions, outcomes, pod memory
- public repo state and PR artifacts
``` ```
**Files:** `scripts/podman-agent.mjs` (new) The backend must remain split:
- **API service:** routable HTTP process with `/api/*` endpoints and health
checks.
- **Agent worker:** outbound LiveKit participant with no HTTP health-check port
requirement.
This split matters for DigitalOcean App Platform: the LiveKit agent should be a
worker, not a web service that App Platform expects to health-check over HTTP.
--- ---
### 3. MongoDB state layer ## 6. Public interfaces to preserve
**Status: ✅ Done (different collection names than originally planned)**
- [x] `observations` — `recordObservation(ctx: EngineerContext)` Do not rename or reshape these without updating frontend, backend, docs, and demo
- [x] `collisions` — `recordCollision(collision: Collision)` scripts together.
- [x] `interventions` — `recordIntervention(intervention: Intervention)`
- [x] `outcomes` — `recordOutcome(outcome: InterventionOutcome)`
- [x] `memoryStats()` — count per collection, exposed via `GET /api/memory/stats`
- [x] Vector recall: `recallSimilar(collision)` in `backend/src/memory/vectors.ts`
- [x] Policy gate: `shouldIntervene(collision, prior)` in `backend/src/memory/policy.ts`
**Actual files:** `backend/src/memory/db.ts`, `backend/src/memory/store.ts`, `backend/src/memory/policy.ts`, `backend/src/memory/vectors.ts` ### Backend HTTP
- `GET /health`
- `POST /api/token`
- `POST /api/sync-pr`
- `POST /api/outcome`
- `GET /api/memory/stats`
- `GET /api/pods`
- `POST /api/pods`
- `GET /api/pods/:id`
- `PATCH /api/pods/:id`
- `DELETE /api/pods/:id`
- `POST /api/pods/:id/members`
- `DELETE /api/pods/:id/members/:name`
### LiveKit data channel
- Topic: `podman.intervention`
- Core messages:
- `COLLISION`: agent -> PWA; contains `collision` and `intervention`.
- `ACK`: PWA -> agent/API; intervention response.
- `GIT_REPORT`: local git sidecar -> agent; dirty/unpushed ground truth.
- `VOICE_CUE`: text cue/fallback for voice escalation.
### Required environment
```bash
LIVEKIT_URL=
LIVEKIT_API_KEY=
LIVEKIT_API_SECRET=
GEMINI_API_KEY=
GEMINI_VISION_MODEL=
GEMINI_LIVE_MODEL=
GITHUB_TOKEN=
GITHUB_REPO=karti-ai/podman
MONGODB_URI=
VOYAGE_API_KEY=
POD_ROOM=demo-pod
PORT=8787
VITE_BACKEND_URL=http://localhost:8787
VITE_LIVEKIT_URL=
```
Keep all non-`VITE_` secrets server-side.
--- ---
### 4. Gemini Vision pipeline ## 7. Critical implementation callouts
**Status: ✅ Done**
- [x] `analyzeFrame(engineerId, podId, jpeg)` calls `gemini-2.0-flash` with structured JSON schema ### LiveKit
- [x] Extracts: `currentFile`, `currentSymbol`, `activity`, `hasUnpushedChanges`, `confidence`
- [x] Low media resolution for speed, zero thinking budget
- [x] Called from `agent.ts` → `podman.onScreenFrame()` → `analyzeFrame()` → `recordObservation()`
- [x] Collision detection runs after every frame: `detectCollisions([...contexts], github)`
**Actual files:** `backend/src/vision/gemini.ts`, `backend/src/agent/podman.ts` - Screen share is a video track. The backend agent should consume raw screen
frames through `@livekit/rtc-node`.
- The agent must filter screen share, not webcam:
`pub.source === TrackSource.SOURCE_SCREENSHARE`.
- Frontend publishing must tag the track as screen share; otherwise the agent can
miss it.
- Throttle aggressively. Screens can arrive near video frame rate; Gemini should
receive sampled frames only.
- Keep reliable data packets small. Use them for intervention metadata, not
screenshots, large diffs, or research dumps. Treat reliable payloads as
roughly 15 KiB max.
- A historical closed `livekit/node-sdks` issue reported high memory use when
consuming video; run memory checks during agent frame tests and stop if the
loop leaks.
### Gemini
- Use structured output for vision: JSON mime type plus response schema.
- Use low media resolution for ambient screen watching; reserve higher
resolution for debugging or targeted inspection.
- Never expose `GEMINI_API_KEY` to the browser.
- Gemini Live API is still a risk for the first demo path. Use card + Hermes
message first; add browser TTS or pre-generated voice fallback before relying
on Gemini Live for stage audio.
- Keep model IDs in env so preview/availability changes do not require code
changes.
### MongoDB
- Local MongoDB is fine for dev CRUD and memory counts.
- Atlas or Atlas Local is needed for the sponsor-grade Vector Search story.
- Build exact-signature recall first:
normalized file + symbol + engineer pair + event type + outcome.
- Writes from the agent should be best-effort. Mongo hiccups should degrade
memory, not kill live detection.
- Do not store raw screenshots or recordings.
### GitHub
- The repo is public and currently has no issue/PR backlog, so do not make the
plan issue-driven yet.
- GitHub cannot see local dirty files or unpushed commits. That is still a core
product moat.
- Sync PRs should use deterministic GitHub REST/Octokit flows, not browser
automation.
- Verify token scopes and demo repo permissions before stage time.
### DigitalOcean
- Use App Platform as:
- static site for frontend,
- HTTP service for API,
- worker for the LiveKit agent.
- Do not model the agent worker as a health-checked HTTP service.
- Keep a local and recorded fallback even if deployment works; venue network is a
stage risk.
### Hermes
- Treat Hermes as the action and messaging layer, not as a replacement for the
current implemented backend agent until code changes make that real.
- Hermes should choose the least intrusive channel:
card -> message -> voice.
- Hermes can own research summaries, teammate notification, sync PR initiation,
and urgent escalation once those workflows exist.
--- ---
### 5. Event detector + nudge generator ## 8. Build ladder
**Status: ✅ Done (collision-based, not Gemini-event-detection-based)**
- [x] `detectCollisions()` — groups engineers by normalized file path, flags when 2+ editing same file with unpushed changes Do not mark a rung done until it is proven in logs, UI, or a visible external
- [x] `shouldIntervene()` + `preferredAction()` policy gate (prevents spam) artifact.
- [x] `recallSimilar()` — vector recall elevates severity if prior collision on same file
- [x] Generates intervention message string (inline, not via Gemini call)
- [x] Publishes `{ type: 'COLLISION', collision, intervention }` via data channel
- [x] Calls `speak(room, message)` (currently stub — just logs)
- [ ] Cooldown per pod not yet implemented (policy gate provides some protection)
**Actual files:** `backend/src/collision/detector.ts`, `backend/src/agent/podman.ts`, `backend/src/memory/policy.ts` ### P0 - make the live loop undeniable
1. **Preserve and reconcile the plan**
- Merge local `docs/PLAN.md` with `origin/main:docs/PLAN.md`.
- Keep both the broad product thesis and concrete server/current-state facts.
- After the docs are safe, merge or rebase the two newer `origin/main` commits
before implementing frontend work.
2. **Browser publish proof**
- Start backend API and frontend.
- Join a real LiveKit room from the browser.
- Confirm the browser publishes a screen-share track with the correct source.
3. **Agent frame proof**
- Start `pnpm --filter @podman/backend dev:agent`.
- Confirm room join, screen-track subscription, frame sampling, and JPEG
encode logs.
- Watch process memory while consuming frames.
4. **Gemini vision proof**
- Send one live sampled IDE frame to Gemini.
- Log parsed JSON with `currentFile`, `currentSymbol`, `activity`,
`hasUnpushedChanges`, and `confidence`.
- Add a confidence/logging gate if noisy frames cause bad reads.
5. **Scheduled git truth** ✅ partial
- `scripts/podman-agent.mjs` polls every 15 s: `git status --short`,
`git diff --stat HEAD`, `git log --oneline -1`, `git branch --show-current`.
- Upserts `changedFiles`, `diffStat`, `recentCommit`, `branch`, `gitUpdatedAt`
to `engineer_states` collection in MongoDB (upsert by `podId::name` key).
- **Still needed:** fuse `engineer_states` git fields into the collision
detector, and/or publish `GIT_REPORT` data channel messages so the agent
worker can incorporate git truth into vision-based decisions.
6. **Intervention card + Hermes notification**
- Publish a real intervention on `podman.intervention`.
- Render it as a small card in the frontend.
- Route a Hermes message to the affected teammate(s) or project channel once
the bridge exists.
7. **Background research recommendation**
- When the team is heading into a poor tool/repo/skill choice or dead end,
produce a recommendation card with short evidence.
- Minimum evidence: why it matters, what to use instead, and who should act.
8. **Learning proof**
- First intervention writes observation/collision/recommendation/outcome
memory.
- Second similar situation retrieves exact prior memory and changes the
message: "I have seen this pattern before."
9. **Urgency routing**
- Default to card.
- Escalate to Hermes message when coordination involves other teammates.
- Escalate to voice only when urgent.
10. **Action artifact**
- If demo uses same-file collision, click the card to open a real draft sync
PR or visible GitHub artifact.
- If demo uses research recommendation, show the accepted recommendation and
memory outcome instead.
11. **Deployment or fallback proof**
- Prove API/static/worker deployment together, or explicitly run local with a
recorded backup.
- Keep backup video on a separate device.
### P1 - polish the money moment
- Add visible live inference captions in the PWA.
- Add a small memory stats panel backed by `/api/memory/stats`.
- Add browser-side TTS or pre-generated voice fallback for urgent interventions.
- Add Hermes notification bridge once the target channel is chosen.
- Improve research cards with compatibility, install effort, docs quality, repo
health, and security/trust signals.
### P2 - sponsor and scale polish
- Implement Voyage embedding + Atlas Vector Search recall.
- Improve policy learning from outcomes.
- Deploy DigitalOcean static site + API service + worker as the submission path.
- Add optional GitHub issue/PR backlog integration after issues/PRs actually
exist.
### Cut if behind
- Webcam grid.
- Mic transcription.
- Full auth/accounts.
- Slack/Linear/Jira integrations unless Hermes requires one immediately.
- Complex dashboards.
- Server-published audio if browser/pre-generated voice proves escalation.
- Vector Search if exact Mongo recall demonstrates the learning beat.
--- ---
### 6. Voice via LiveKit ## 9. Critical 3-minute demo script
**Status: ⚠️ Partial — agent structure done, voice is a stub**
- [x] `backend/src/agent.ts` — full LiveKit agent: joins room, subscribes to screen tracks, 1fps sampling **Rule:** open on one active IDE, not a grid. PodMan is an agent, not a
- [x] `backend/src/voice/live.ts` — `speak(room, message)` function wired into pipeline dashboard.
- [x] `room.localParticipant.publishData()` — data channel publish working
- [ ] `speak()` is a stub — logs message but does NOT produce audio
- [ ] Gemini Live 2.5 audio streaming not implemented
- [ ] **Agent not started on server** — `start-podman.sh` has it commented out; needs `pnpm dev:agent` + real LiveKit creds
**To unblock:** Implement real TTS in `speak()` (Gemini TTS → WAV → publish audio track), then uncomment agent window in `start-podman.sh`. 1. **0:00 - Set the scene**
- One engineer is actively coding in the IDE.
- The presenter says: "This work is not pushed yet. GitHub cannot see it."
**Actual files:** `backend/src/voice/live.ts`, `backend/src/agent.ts`, `backend/src/agent/podman.ts` 2. **0:20 - Show the live signal**
- Show a compact caption: current file, inferred task, git dirty/unpushed
state.
- Show that PodMan is watching consented screen context, not stored
recordings.
3. **0:40 - Introduce the better-tool moment**
- A teammate starts down a weak path: wrong package, dead repo, bad API,
duplicated effort, or risky implementation.
- PodMan has been researching in the background.
4. **1:05 - Money moment**
- PodMan shows a small card:
"This path is likely a dead end. Use X instead; it matches our stack and is
actively maintained."
- The card names the affected teammate and the suggested action.
5. **1:25 - Hermes coordination**
- Hermes notifies the right teammate(s), not the whole room.
- No voice yet unless the situation is urgent.
6. **1:50 - Learning beat**
- A similar issue appears.
- PodMan references memory:
"I have seen this pattern before. Last time the team accepted the X
recommendation."
- Show `/api/memory/stats` or the visible memory indicator.
7. **2:20 - Urgency escalation**
- Raise the severity with a same-file collision, blocking dependency, failing
test, or imminent bad push.
- Hermes escalates to voice only now.
8. **2:40 - Close**
- Show the public repo, deployed/local URL, and memory stats.
- Closing line: "PodMan coordinates work while it is still happening."
### Reliable fallback demo
If the research recommendation is not reliable by stage time, use the same-file
collision fallback:
1. Two engineers open the same visible file.
2. `GIT_REPORT` or vision marks one as dirty/unpushed.
3. Agent publishes `COLLISION` on `podman.intervention`.
4. Frontend renders the card.
5. The card opens a sync PR artifact.
6. A second similar collision retrieves prior memory.
--- ---
### 7. PWA active session UI ## 10. Sponsor strategy
**Status: ❌ Not started**
- [ ] `frontend/src/components/SessionView.tsx` — active session screen post-join ### Gemini
- [ ] Teammate status cards (name, inferred file, inferred task)
- [ ] `RoomEvent.DataReceived` listener for collision/intervention messages from agent
- [ ] Nudge feed: last 5 interventions, timestamped
- [ ] "PodMan is watching" indicator
**Depends on:** Task 6 (agent producing data channel messages — working even without voice) Gemini must be load-bearing for the vision loop:
**Files:** `frontend/src/components/SessionView.tsx` (new), `frontend/src/App.tsx` (wire post-join) - live IDE/screen frame -> structured work context,
- optional message/recommendation generation,
- optional Live voice only after card/Hermes routing is stable.
Do not overclaim voice if it is using browser/pre-generated TTS. Say plainly that
it is the reliability fallback.
### LiveKit
LiveKit is the real-time spine:
- engineers join one pod room,
- screen-share tracks carry active work context,
- PodMan joins as a participant,
- data packets carry interventions,
- voice can be added as urgent escalation.
Pitch line: "Unpushed work is invisible to GitHub, so real-time presence is the
only way to coordinate before the push."
### MongoDB + Voyage
MongoDB is the learning proof:
- observations, collisions, recommendations, interventions, and outcomes persist,
- prior memory changes a later intervention,
- exact recall is the MVP,
- Voyage + Atlas Vector Search is the stronger sponsor-grade version after exact
recall works.
### DigitalOcean
DigitalOcean earns its place when:
- frontend runs as a static site,
- API runs as an HTTP service,
- LiveKit agent runs as a worker,
- public URL is shown in submission or demo.
Local fallback is acceptable for stage reliability, but the submission should
include the deployment URL if possible.
--- ---
## Cut line — below here only if tasks 1–7 done before hour 10 ## 11. Risks and mitigations
### 8. Ownership warm-start demo | Risk | Mitigation |
**Status: ⚠️ Partial — memory persists, no warm-start logging** | -------------------------------------- | -------------------------------------------------------------------------------------------------------------------------------- |
- [ ] On agent startup: log "Loading session memory for pod X — N collisions known" | Looks like a dashboard | Keep the UI quiet. Hero is card/message/action, not a grid. |
- [ ] Demo: session 1 cold, session 2 faster — visible in logs | Looks like a screenshot analyzer | Always show screen signal + git truth + memory + action. |
| Interrupts too much | Default to cards, escalate to Hermes messages, reserve voice for urgency. |
| Overclaims implemented features | Mark voice, Hermes bridge, vectors, adaptive policy, research agent, real sync PR, and DO worker deploy incomplete until proven. |
| Vision misses unpushed state | Use scheduled `GIT_REPORT` for deterministic dirty/unpushed truth. |
| Research recommendation lacks evidence | Show only concise evidence: stack fit, repo/tool health, install effort, docs/trust signal. |
| No visible learning | Build exact Mongo recall before vector search. |
| LiveKit frame loop leaks memory | Monitor agent memory during video consumption; throttle hard. |
| GitHub issue/PR backlog absent | Do not invent issue-driven backlog; repo currently has no issues or PRs. |
| Venue network failure | Rehearse on hotspot and keep recorded backup. |
| DO worker deploy hangs | Deploy agent as worker, not health-checked service. |
--- ---
### 9. GitHub-enriched collision detection ## 12. Documentation reconciliation tasks
**Status: ⚠️ Exists but may not be needed for demo**
- `backend/src/github/client.ts` exists — fetches PR state as `GithubStateSnapshot` After this plan is accepted, update the supporting docs so they stop conflicting
- Not required for the demo since screen-based `hasUnpushedChanges` is sufficient with this file:
- `README.md`: replace POST-screenshot-first language with LiveKit screen-track
agent architecture and Hermes action-layer wording.
- `docs/idea.md`: broaden from blocker/dependency voice demo to card/message/
urgent-voice coordination plus research and memory.
- `docs/livekit.md`: remove "Hermes does NOT subscribe to engineer screen
tracks"; current architecture uses backend agent screen subscription.
- `docs/gemini.md`: keep structured vision, but mark Gemini Live as P1 and avoid
claiming voice is implemented.
- `docs/mongodb.md`: align collection names with current code
(`observations`, `collisions`, `interventions`, `outcomes`, `pods`) and add
exact-signature recall.
- `docs/digitalocean.md`: split API service and agent worker; do not deploy the
worker as a health-checked HTTP service; mark `infra/app.yaml` legacy or
reconcile it with `infra/.do/app.yaml`.
- `docs/demo-setup.md`: update the script to include better-tool research,
learning recall, Hermes notification, and urgency-based voice.
--- ---
### 10. Backend state endpoint ## 13. Acceptance checklist
**Status: ✅ Done (as pods API)**
- `GET /api/pods` — returns all pods Before saying PodMan is demo-ready:
- `GET /api/pods/:id` — returns pod with members
- No per-engineer state endpoint yet (frontend uses data channel instead) - [ ] `pnpm format:check` passes or all failures are documented as unrelated.
- [ ] `pnpm typecheck` passes.
- [ ] Browser joins a real LiveKit room.
- [ ] Browser publishes a screen-share track with the correct source.
- [ ] Backend agent subscribes to the screen-share track.
- [ ] Agent logs at least one parsed Gemini context from a real IDE screen.
- [x] Local git report supplies dirty/unpushed truth on a schedule (`scripts/podman-agent.mjs` — 15 s poll → MongoDB `engineer_states`). Agent fusion still needed.
- [ ] Frontend renders a real intervention card.
- [ ] Hermes notification path works for teammate messages.
- [ ] Voice is heard only for urgent escalation or a fallback is declared.
- [ ] Outcome ACK writes to MongoDB.
- [ ] `/api/memory/stats` shows counts increasing.
- [ ] Second similar situation uses prior memory in the message.
- [ ] Research recommendation card is evidence-backed, or fallback collision demo
is used.
- [ ] Sync PR action creates a visible GitHub artifact if used in demo.
- [ ] DigitalOcean deployment or local fallback is rehearsed.
- [ ] Backup recording is ready on a separate device.
--- ---
## What needs to happen next (priority order) ## 14. Evidence appendix
1. **Voice (Task 6)** — implement real `speak()` with Gemini TTS → WAV → LiveKit audio track ### Repo and GitHub state
2. **Session UI (Task 7)** — `SessionView.tsx` with data channel listener + nudge feed
3. **Start agent on server** — uncomment agent window in `start-podman.sh`, ensure LiveKit creds in `backend/.env`
4. **Git watcher (Task 2b)** — `scripts/podman-agent.mjs` for demo terminals
--- - Public repo: <https://github.com/karti-ai/podman>
- Verified with authenticated `gh` on `2026-06-27`.
- Default branch: `main`.
- No GitHub issues or PRs existed at verification time.
## Server state (165.22.129.249) ### Hackathon / event
- Backend: ✅ running on `:8787` (tmux `podman:backend`) - AI Engineer World's Fair: <https://www.ai.engineer/worldsfair/2026>
- Frontend: ✅ running on `:81` (tmux `podman:prod`, port 80 taken) - Cerebral Valley hackathon page:
- Agent: ❌ NOT running — needs LiveKit creds + `pnpm dev:agent` <https://cerebralvalley.ai/e/aiewf-hackathon-2026>
- To start agent: `tmux new-window -t podman -n agent && tmux send-keys -t podman:agent 'cd /root/podman && pnpm --filter @podman/backend dev:agent' C-m`
- To attach: `ssh root@165.22.129.249` → `tmux attach -t podman`
--- ### LiveKit
## Cut immediately - Screen share docs: <https://docs.livekit.io/transport/media/screenshare/>
- Data packets docs: <https://docs.livekit.io/transport/data/packets/>
- Node SDK reference: <https://docs.livekit.io/reference/client-sdk-node/>
- Node SDK releases: <https://github.com/livekit/node-sdks/releases>
- Node SDK issue risk: <https://github.com/livekit/node-sdks/issues/444>
- Mic transcription or voice input from engineers ### Gemini
- Manual task input fields on PWA
- Multilingual voice
- Slack / Linear / Jira integrations
- Webcam tracks
- Always-on raw screen surveillance (1fps sampling is by design)
- Full task management features
- User auth / accounts
--- - Structured output:
<https://ai.google.dev/gemini-api/docs/structured-output>
- Media resolution: <https://ai.google.dev/gemini-api/docs/media-resolution>
- Live API: <https://ai.google.dev/gemini-api/docs/live-api>
## Risk table ### DigitalOcean
| Risk | Mitigation | - App Platform app spec:
|---|---| <https://docs.digitalocean.com/products/app-platform/reference/app-spec/>
| Gemini Vision accuracy on screens | Large font (18pt+), single editor window, file tab fully visible. |
| Gemini Live TTS not implemented | Fallback: `@google/genai` TTS → WAV buffer → publish as audio track manually. |
| Agent needs HTTPS for screen capture | Demo from localhost or ngrok. PWA has dev mock-join fallback. |
| Event detection false positives | Policy gate in `shouldIntervene()`. Demo is pre-staged so collisions fire cleanly. |
| DO deploy: frontend on :81 not :80 | Port 80 taken — either kill the process or update DNS/proxy to :81. |
| Multiple collisions fire at once | Policy gate prevents spam; same-collision dedup via file+engineers key. |
--- ### MongoDB
## Demo script (3 min) - Vector Search index type:
<https://www.mongodb.com/docs/vector-search/index/vector-search-type/>
**(0:00)** Three laptops visible. Alice, Bob, Carol join `demo-pod` via PWA. Agent logs `[agent] PodMan joined room demo-pod`. - Node driver Atlas Vector Search:
<https://www.mongodb.com/docs/drivers/node/current/atlas-vector-search/>
**(0:20)** Alice opens `auth/middleware.ts` (18pt font, clearly visible). First frame processed. `[vision] currentFile: auth/middleware.ts`.
**(0:45)** Bob opens `auth/middleware.ts` too. Carol runs `curl http://localhost:3001/auth` → `connection refused`.
**(1:20) MONEY MOMENT 1 — COLLISION_DETECTED:**
PodMan data channel message fires: *"alice and bob are both editing auth/middleware.ts and one has unpushed changes."*
Voice says it aloud in the room.
**(1:50)** Alice pushes. Bob pulls. Carol's integration unblocks.
**(2:20)** Show `GET /api/memory/stats` → `{ observations: 47, collisions: 1, interventions: 1, outcomes: 0 }`. Session 2 warm-start: collision detected in 12s vs 3min cold.
**(2:45)** Close: *"PodMan — the teammate that sees what Slack can't."*
---
## Pre-demo checklist (day of)
See `docs/demo-setup.md` for full laptop setup. Key items:
- [ ] All laptops: font 18pt+, single editor window, file tab visible
- [ ] `demo-pod` created in LiveKit Cloud, creds in `backend/.env`
- [ ] Agent running: `tmux attach -t podman` → check `agent` window
- [ ] `GET /health` returns OK on deployed URL
- [ ] Earbuds tested — voice audible through browser
- [ ] Backup video recorded and on separate device
- [ ] Demo rehearsed 3×
scripts/podman-agent.mjs
+152
View File
@@ -0,0 +1,152 @@
#!/usr/bin/env node
/**
* Local git watcher — polls working tree every 15s and upserts into MongoDB.
* Usage: node scripts/podman-agent.mjs --name alice --pod demo-pod
*/
import { execSync } from 'node:child_process';
import { MongoClient } from 'mongodb';
// ── CLI args ──────────────────────────────────────────────────────────────────
function parseArgs() {
const args = process.argv.slice(2);
const get = (flag) => {
const i = args.indexOf(flag);
return i !== -1 ? args[i + 1] : null;
};
const name = get('--name');
const pod = get('--pod');
if (!name || !pod) {
console.error('Usage: node scripts/podman-agent.mjs --name <name> --pod <podId>');
process.exit(1);
}
return { name, podId: pod };
}
// ── Environment ───────────────────────────────────────────────────────────────
async function loadEnv() {
if (!process.env.MONGODB_URI) {
try {
const dotenv = await import('dotenv');
dotenv.config({ path: new URL('../backend/.env', import.meta.url).pathname });
} catch {
// dotenv not available — rely on process.env
}
}
const uri = process.env.MONGODB_URI;
if (!uri) {
console.error('Error: MONGODB_URI not set. Export it or add it to backend/.env');
process.exit(1);
}
return uri;
}
// ── Git helpers ───────────────────────────────────────────────────────────────
function git(cmd) {
try {
return execSync(cmd, { encoding: 'utf8', stdio: ['pipe', 'pipe', 'pipe'] });
} catch {
return '';
}
}
function collectGitState() {
const statusRaw = git('git status --short');
const changedFiles = statusRaw
.split('\n')
.map((l) => l.trim())
.filter(Boolean);
const diffRaw = git('git diff --stat HEAD').trim();
const diffStat = diffRaw || null;
const logRaw = git('git log --oneline -1').trim();
const recentCommit = logRaw || null;
const branchRaw = git('git branch --show-current').trim();
const branch = branchRaw || null;
return { changedFiles, diffStat, recentCommit, branch };
}
// ── Poll ──────────────────────────────────────────────────────────────────────
async function poll(col, engineerId, podId, name) {
const { changedFiles, diffStat, recentCommit, branch } = collectGitState();
const now = new Date();
try {
await col.updateOne(
{ _id: engineerId },
{
$set: {
changedFiles,
diffStat,
recentCommit,
branch,
gitUpdatedAt: now,
updatedAt: now,
},
$setOnInsert: {
podId,
name,
confidence: 0,
},
},
{ upsert: true },
);
const ts = now.toISOString().slice(11, 19);
const files = changedFiles.length;
const br = branch ?? '(detached)';
const commit = recentCommit ? recentCommit.slice(0, 50) : '(no commits)';
console.log(`[${ts}] ${name}@${podId} | branch=${br} files=${files} commit="${commit}"`);
} catch (err) {
console.error(`[poll error] ${err.message}`);
}
}
// ── Main ──────────────────────────────────────────────────────────────────────
async function main() {
const { name, podId } = parseArgs();
const engineerId = `${podId}::${name}`;
const uri = await loadEnv();
const client = new MongoClient(uri, { serverSelectionTimeoutMS: 8_000 });
await client.connect();
const col = client.db().collection('engineer_states');
await col.createIndex({ podId: 1, updatedAt: -1 }, { background: true });
console.log(`podman-agent started | id=${engineerId} | polling every 15s`);
console.log('Press Ctrl+C to stop.\n');
let running = true;
const shutdown = async () => {
running = false;
console.log('\nShutting down...');
await client.close();
process.exit(0);
};
process.on('SIGINT', shutdown);
process.on('SIGTERM', shutdown);
// Run immediately, then loop
await poll(col, engineerId, podId, name);
while (running) {
await new Promise((r) => setTimeout(r, 15_000));
if (running) await poll(col, engineerId, podId, name);
}
}
main().catch((err) => {
console.error('Fatal:', err.message);
process.exit(1);
});