Building an AI Agent to Eliminate Workplace Information Overload

✳The problem they went after

Teams burn two to three hours a day just keeping up. Project managers lose the thread across fifteen-plus channels, a developer going on unplanned leave leaves the team stuck without context, and engineering managers watch important files vanish under notification floods. Add the constant hop between Slack, Google Meet, Calendar and Docs, and the cost is real working time.

✳What they actually did

Four capabilities sit on one architecture: a Daily Catch-Up that summarises missed messages with prioritised action items, a Smart Finder for natural language search across messages and files, an Intelligent Scheduler that books meetings inside Slack, and a Proxy Assistant that attends meetings and answers on the user's behalf. Underneath, a RAG pipeline routes queries through intent classification into a vector database of messages, files, meetings and tasks. The business case models twenty to twenty-five million dollars of Year 1 revenue and a three-phase launch priced at free, ten, and twenty dollars per user per month.

✳What you can take from it

The transferable bitThe feature list is paired with the plumbing that makes it possible. These are not four disconnected AI ideas; everything reads off the same vector index, which is why an assistant that sits in meetings for you is even plausible. Worth studying for how pricing tiers and a phased rollout get tied back to the capabilities themselves.

✳Everything else they shared