I built my last application across 200+ separate Cursor chats. Every feature was a new conversation. Every agent had no idea what the last one did. I was the only thread connecting everything — in my head, across browser tabs, in a Notion doc nobody else could read. This isn't a unique story. It's the default experience for anyone building a real product with AI agents in 2026. And the tooling hasn't caught up. The AI development ecosystem has poured enormous energy into making agents faster, smarter, and more autonomous. Multi-agent orchestration is a hot topic — new frameworks appear weekly on r/ArtificialIntelligence and r/AI_Agents. But almost all of them solve orchestration at the task level: run this agent on this task, run that agent on that task, merge the outputs. Nobody's asking the product-level question: how do all these pieces fit into a coherent whole? A developer in r/copilotstudio recently posted about multi-agent orchestration problems — multi-turn conversations breaking down, context getting lost between agents, connected systems failing to share state. The thread was full of people hitting the same wall. Not because the individual agents were bad, but because there was no shared product context connecting them. Meanwhile, even sophisticated builders are coordinating manually. A CTO I spoke with described his workflow: open a Claude Code session, tell it to work on an issue, have a conversation to clarify requirements, review the plan, then repeat for the next feature. It works, he said — but every session starts from scratch. There's no persistent understanding of the product across sessions. Tools like Vibe-Kanban (5.9K GitHub stars) prove there's real demand for agent orchestration. But they operate at the task level: one card equals one task equals one agent execution. The interface is a kanban board. The mental model is a task manager with agents. This solves the execution problem. It does not solve the coordination problem. When you're building something with dozens of interconnected features, knowing that Agent #3 finished Task #7 doesn't tell you whether the authentication flow still makes sense, whether the data model supports the reporting feature you haven't built yet, or whether two agents just made contradictory assumptions about how users navigate between screens. The coordination problem is a product-level problem. It requires product-level visibility. Dossier exists because I got tired of being the human coordination layer. It models your product as a user story map — not a task list, but a hierarchical view of what users do and how the system supports them. Product → Workflows → Functionalities, with structured context at every node. When you build feature by feature from this map, agents work from scoped context that knows where it sits in the larger product. When something changes, the map reflects it. You can see the whole product forming in near-real time instead of stitching together a mental model from terminal output across a dozen sessions. The tagline that keeps resonating: see the forest while agents build the trees. That's the coordination problem in six words — and why task-level orchestration, no matter how sophisticated, can't solve it alone. The tools will catch up eventually. For now, Dossier is free and open source.