Waffle for product teams

How product teams use Waffle

Product and design teams chat, hop into voice, and work alongside Waffle AI, an AI teammate that reads research and specs, drafts PRDs and one pagers as real documents, summarizes long threads, and files Linear or Jira issues from a discussion. That matters because knowledge workers spend about a fifth of the workweek just searching for information (McKinsey Global Institute, 2012). Waffle keeps the decision and its context in one place.

Product work is really a stream of decisions, and the context behind each one tends to scatter across a chat app, a doc tool, and a tracker. Waffle folds that back together. You mention Waffle AI like any teammate, and its reply lands once, finished, with any files it made attached, right in the channel where the discussion happened.

What Waffle AI does for product teams

• Drafts PRDs, specs, and one pagers as real Word, PDF, or Markdown documents, attached to the reply.
• Summarizes a long thread or a research doc so you get the decision without rereading everything.
• Files Linear or Jira issues straight from a discussion through MCP connectors.
• Builds a simple spreadsheet, like a prioritization or a rollout tracker, as an Excel or CSV file.
• Catches you up on a channel with a private summary that never posts publicly.

Every one of these is a shipped capability, not a roadmap promise. Waffle AI reads attachments such as PDFs, spreadsheets, and text, and writes PDF, Word, PowerPoint, Excel, CSV, and Markdown files. An admin turns it on per channel and can set a per channel persona, so it speaks the way your team wants it to.

One place for the decision and its context

When the chat, the research the AI read, the PRD it wrote, and the issue it filed all live in the same thread, nobody has to reassemble the story later. That is real time back: workers toggle between apps roughly 1,200 times a day and lose nearly four hours a week reorienting themselves (Harvard Business Review, 2022). Fewer tabs, more decisions made.

Atlassian's 2025 State of Teams survey of 12,000 knowledge workers found teams waste about a quarter of their time just searching for answers (Atlassian, 2025). Waffle attacks that at the source: the answer, and the artifact, are produced in the conversation rather than in a tool you have to go find. And with 75 percent of knowledge workers already using AI at work (Microsoft and LinkedIn Work Trend Index, 2024), your team gets an AI teammate that is governed and in the shared space, instead of pasted in from a browser tab.

Voice and screen share for reviews

Any channel can become a one click voice channel with screen share, so a design critique or a spec walkthrough is one tap away, in the same place your team already chats. No scheduling, no separate call app, and no link to send around.

Share your screen to walk a prototype or a roadmap, talk it through, then drop back into the thread where the decision gets written down. Waffle voice is audio and screen share, tuned for quick working sessions rather than formal meetings.

Frequently asked questions

How do product teams use Waffle AI?

Product managers and designers mention Waffle AI in a channel or a private thread, and it does the work. It reads a research doc or a spreadsheet and answers with specifics, drafts a PRD or a one pager as a real document, summarizes a long thread, and files issues in Linear or Jira through MCP connectors. The reply lands once, finished, with any files attached.

Can Waffle AI draft a PRD or a one pager?

Yes. Waffle AI writes real files, not just chat text. It can produce a PRD, a spec, or a one pager as a Word, PDF, or Markdown document, and build a simple spreadsheet as an Excel or CSV file. It attaches the file to its reply in the channel, so the artifact lives right next to the discussion that produced it.

Does Waffle connect to Linear and Jira?

Yes, through MCP connectors. An admin connects Linear or Atlassian (Jira and Confluence), or any custom MCP server, and sets each connector read only or read and write. Admins also scope which connectors a given channel may use. Waffle AI can then file and read issues in the tracker your team already lives in, straight from the conversation.

How does Waffle keep a decision and its context together?

The discussion, the research the AI read, the document it wrote, and the issue it filed all live in the same channel and thread. There is no separate doc tool to sync or a decision log to maintain by hand. When someone joins late, they ask Waffle AI to catch them up and get a private summary that never posts publicly.

Sources

Statistics cited on this page, for reference:

• McKinsey Global Institute, The Social Economy (2012) on time spent searching for internal information.
• Harvard Business Review, How Much Time and Energy Do We Waste Toggling Between Applications? (2022)
• Atlassian, State of Teams (2025) on time spent searching for answers.
• Microsoft and LinkedIn, Work Trend Index (2024) on AI adoption among knowledge workers.