The TPM Meeting Assistant Is Here (Beta): Agency Starts Where the Meeting Starts

There is a thing the industry keeps dancing around, and we should just say it plainly.

If your company is going to become AI-native, it has to start with the meetings.

Not the documents. Not the dashboards. Not a chatbot sitting in the corner of your intranet. The meetings. The daily standups, the sprint planning sessions, the retros, the syncs that your remote team runs every morning at 9:15. Those are the source of truth. That is where decisions happen, commitments are made, and work gets assigned.

And right now, most AI meeting tools record that conversation, transcribe it, summarize it, and hand you a document that — let's be honest — you probably won't read.

That is not agency. That is a fancier version of meeting minutes.

Why Meetings Are the Top of the Funnel

Here is the frame that matters: meetings sit at the top of the execution funnel for every team that works remotely.

Every decision, every commitment, every "I'll have that done by Thursday" — it starts in a meeting. And if AI is going to be useful to your organization beyond a novelty, it needs to be present where those commitments are made. Not downstream. Not after the fact. In the room.

When AI has a seat at the table during the conversation, that context can filter down to everything else. Downstream agents, project tracking, knowledge systems — they all benefit from a source of truth that was captured at the point of origin, not reconstructed after the fact from someone's notes.

What the TPM Assistant Actually Does

The TPM Meeting Assistant is a voice-enabled AI participant. You talk to it the way you talk to any other person in the meeting. It listens, it responds, it acts.

Here is how it works:

The PM Tool Ecosystem

The reason the TPM assistant works is that it is not isolated. It has authenticated access to the ecosystem of project management software your team already uses.

That means:

• Jira, Linear, Asana, Monday — ticketing, sprint boards, backlog
• Confluence, Notion, Google Docs — wikis, specs, prior decisions
• GitHub — PR status, branch activity, deployment state
• Slack, Microsoft Teams — follow-ups, handoffs, async coordination
• Google Calendar — schedule awareness, meeting history

The assistant does not just listen to the meeting and produce a document. It reaches into these systems during the conversation. When someone says "I'm blocked on the auth service migration," the assistant checks the ticket, checks the PR, and tells the room what the actual status is — before the conversation moves on.

This is what separates a TPM from a notetaker. A notetaker records that someone said they were blocked. A TPM checks the data and tells the room what is actually going on.

Real Workflows

Here are a few things that happen naturally when you run your standup with the TPM assistant:

Enterprise Knowledge: Glean and Notion

Two platforms are worth calling out specifically because they change what the assistant can do at inference time.

When the TPM assistant has Glean connected, it is not working from a blank slate. It has semantic access to your org's collective knowledge. It knows who Jesse is, what his role covers, which projects he owns, and which Slack channel to reach him in — not because someone configured a rigid workflow, but because that context already exists in the knowledge graph.

When the assistant has Notion connected, meeting context flows directly into the workspace. Action items become tasks. Decisions become documented records. The meeting is not an isolated event — it is a node in the team's knowledge system.

How We Think About Cost and Performance

Here is something the industry is learning, and we think it is worth saying directly: model intelligence is not the only factor in agent performance.

There is a common assumption that better outcomes require the most expensive model available. In practice, that is not what we see. Our harness — the orchestration layer that manages memory, context, tool access, and execution — allows us to get reliable, high-quality performance from models that are considered less expensive but still highly capable.

The result is meaningful cost savings for our users without sacrificing the quality of the assistant's work. When you pair strong orchestration with disciplined context management, you do not need to brute-force every interaction with the largest model on the market.

A few specifics on what makes this work:

• Memory and context management. The assistant maintains continuity across sessions without dumping entire conversation histories into every prompt. Prior decisions, open tickets, and team dynamics are retrieved selectively — what is relevant to this meeting, right now.
• Code execution. The assistant can run code during the meeting to process data, transform outputs, and interact with APIs. This is not prompt-and-pray. It is structured execution with real compute.
• Thousands of APIs without context rot. We connect external services through an architecture that keeps tool access clean and current. The assistant does not hallucinate API schemas or guess at endpoints. It has live, authenticated access to the systems it needs.

A Note on Where the Industry Is

We are at an inflection point. The hype cycle around AI has produced a lot of tools that demonstrate capability without delivering outcomes. The gap between "look what AI can do" and "here is what AI did for your team today" is still wide.

The TPM Meeting Assistant is a direct attempt to close that gap. It is not a demo. It is not a summary layer. It is a working technical project manager that joins your meetings, does the work, and ships deliverables into your pipeline.

AI note takers — Fireflies, Otter, Fathom, and the rest — are not bad tools. They solved a real problem. But a transcript is not an outcome. A summary is not a sprint. And a list of action items that nobody acts on is not project management.

The standard we are building toward is simple: the meeting should produce the work, not a document about the work.

Try It (Beta — Free Access)

The TPM Meeting Assistant is in beta. Sessions are limited to 15 minutes during this period, and access is free.

FAQ

What is the TPM Meeting Assistant?

It is a voice-enabled AI technical project manager that joins your engineering meetings as a live participant. It retrieves context from your PM tools, responds to questions in real time, tracks action items, and creates tickets with assignments before the call ends.

How do I invite it to a meeting?

Send it a calendar invite, the same way you would invite any other participant. It supports Zoom, Google Meet, and Microsoft Teams.

What tools does it connect to?

Jira, Linear, Asana, Monday, Confluence, Notion, Google Docs, Google Sheets, GitHub, Slack, Microsoft Teams, Google Calendar, and more. The platform supports thousands of API integrations.

Is it a notetaker?

No. It takes notes as a side effect of doing real work. The primary output is deliverables — tickets, follow-ups, status checks — not a summary document.

How much does it cost?

It is free during the beta period. Sessions are limited to 15 minutes. Pricing will be determined based on beta feedback.

Can I talk to it during the meeting?

Yes. It is voice-enabled. You talk to it the same way you talk to any other meeting participant. You can ask it questions, give it instructions, or just let it listen and act on ambient conversation.

What happens after the meeting?

The transcript and recording are shared with meeting attendees. Any tickets or action items created during the session are already in your project management tool.