Atono vs. Linear

Frequently asked questions

• Can Atono replace Linear?

  

  Yes, it can. Linear and Atono handle the core objects similarly: issues become Stories, cycles become Timeboxes, roadmaps become Timelines, and so on. What Atono adds is Product Knowledge – your product's terminology, decisions, and definitions captured in one place.

  The key difference: Linear gives AI access to your issues. Atono gives AI access to what those issues mean – the context behind them. This is what AI agents actually need to build correctly.

  You can replace Linear entirely, or run Atono alongside it during migration.

• What does Atono offer that Linear doesn't?

  

  A Product Glossary and AI Context served to AI tools through a native MCP server, plus feature flags tied to stories, product analytics, design-decision and research capture, and at-risk/staleness warnings. Linear keeps these outside its scope.

• Is Atono as fast as Linear?

  

  Yes. Atono is built around instant, in-context access – getting to your work without navigation detours – so planning and board views stay fast. The bigger difference is the shared product-context layer Atono adds around that speed.

• Is Atono more complex than Linear?

  

  No. Linear is built for speed. Atono is built for clarity. You get a similarly minimal interface, with the option to build a Glossary from your existing documentation or import one using a TSV file. That gives your team shared product context without adding heavy configuration.

• Why would a fast-moving team need product context?

  

  Speed without context gets you shipped fast – but almost right is worse than wrong. When humans and AI agents build together, agents need to understand what "right" means for your product. Linear gives you velocity; Atono gives velocity with alignment.

• Can Atono and Linear work together?

  

  Yes. You can keep Linear for execution and use Atono as the product context layer that grounds your AI tools in what your product means, then migrate when you're ready.

• Which works with AI dev tools like Cursor and Claude Code?

  

  Atono is MCP-native and tool-agnostic, connecting to Cursor, Claude Code, Copilot, and Windsurf with real-time access to stories, bugs, and AI Context, plus a Glossary TSV export. Linear's AI features help manage work inside Linear; Atono helps AI tools understand your product.

• Does Atono import from Linear?

  

  Yes – Atono includes a Linear import tool, so your existing issues and structure come across when you move or run the two in parallel.

• Why does AI need structured product context?

  

  When Atono ran its own Glossary against its own AI-generated stories, 60% needed changes to match the product. That's direct evidence that AI output drifts from the product without structured context. The Context Gap Report points to the same gap in the field – AI helps manage work, but it struggles without understanding your product's terminology and decisions.