Launching today
FlyDocs
Team alignment. Real-time visibility. Built for AI speed.
4 followers
Team alignment. Real-time visibility. Built for AI speed.
4 followers
AI made your developers fast, FlyDocs brings the rest of your team up to speed. FlyDocs isn't a coding agent or a PM tool, it's the bridge that connects Cursor, Claude Code, Windsurf and Codex to Linear and Jira, enforcing standards your agents can’t skip. Every AI session follows your team's rules, your tickets auto-update as you go, and leads always know what's shipping. When your team is aligned and your leads have real visibility, the speed your AI tools unlocked actually goes somewhere.
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Over the last two years as AI adoption really started to ramp up, we kept noticing the same pattern across the tooling we use internally and every AI-assisted team we work with. Code was moving fast. Everything around it was not. Docs were weeks behind. Tickets were stale or missing. Leadership was asking what was shipping and getting answers that depended on someone remembering to update a board. Handoffs that worked fine at human speed were quietly breaking at AI speed.
I'm Matt, co-founder of FlyDocs. I've spent 20 years in product and consulting. Our team has spent the last two years deep in agentic engineering work, for ourselves and for clients. I watched this pattern destroy velocity across teams, repeatedly, before I built anything.
At first we blamed AI for creating the problem. It hadn’t. It just exposed how misaligned things already were. Stale docs and lagging tickets were always there; they just didn't hurt as much when everything moved slower. Speed up one layer of the system and every gap compounds fast: the more code ships, the less of that speed survives, because everyone downstream is catching up.
FlyDocs realigns those gaps. It runs as a layer inside your existing AI coding workflow, connecting your editor to Linear or Jira without changing how your developers work. You define your team's standards once, and every AI session inherits them, so work ships consistently instead of however each dev happened to prompt that day. When an agent does the work, it opens the issue, moves it through your workflow, and updates Linear or Jira on its own. The project lead watches the card cross the board in real time while the dev is still in the editor. Leadership gets a straight answer on what's shipping, how fast, and whether it's working. Everyone operates on the same signal.
Ten teams are running FlyDocs in production today. Most of what we've shipped so far has come directly from the people using it. We built it in the open on purpose: we want FlyDocs to fit the way teams actually work, not force them into a workflow we designed in isolation.
Cost forecasting and token analytics are next on the roadmap so you can see exactly where your AI spend is going and get ahead of it before the bill lands. It's part of a bigger push to keep the framework as token- and cost-efficient as we can, so teams don't have to think about it. For anyone watching what AI actually costs them, that changes the picture.
I'll be in the comments all day to answer any questions. One question I'd love to hear more on: if your team is already shipping with AI-assisted development, where does it break down first? Docs falling behind, tickets not reflecting reality, or leadership losing the picture of what's actually shipping?
The sync between Cursor sessions and Linear tickets sounds great. One thing I'd love to see is a way to comment back into Jira from the FlyDocs dashboard without needing to switch tools, so non-engineering folks can leave context directly on the work being shipped.