Your team grew. Your velocity didn't.

Frequently asked questions

• How does Atono help maintain engineering velocity as teams scale?

  

  Velocity decays at scale when the reasoning behind decisions stops travelling with the work. New engineers re-investigate what was already solved. AI agents start every session from zero. Atono keeps decisions, design rationale and implementation history on every story – so every person and every agent builds on what came before instead of starting over. The context compounds as the team grows rather than resetting with every hire or reorg.

• How does Atono speed up engineer onboarding?

  

  Atono captures decisions, trade-offs and implementation context on the story as work happens – not as a documentation project that never gets completed. When a new engineer picks up a story, the reasoning behind every decision is already there. They don't need to find the veteran who made the call three months ago. Onboarding time shortens because the institutional knowledge is on the work, not in someone's head.

• What engineering metrics does Atono track for planning?

  

  Atono tracks cycle time per story size – calculated as cumulative time spent in active workflow steps (Design, Development, Test, Review) on a configurable rolling window, with outliers excludable manually. That data powers estimated completion dates that update automatically as the backlog reorders, sprint capacity projections on the calendar, and staleness indicators that flag stories spending more than three standard deviations above the team's average time-in-step. All metrics are team-specific and adapt to customized workflows.

• How does Atono replace Jira, LaunchDarkly and Amplitude?

  

  Atono consolidates project management, feature flags and engagement analytics into one workspace. Stories carry feature flags linked directly to the work that defined them. Engagement data appears on the originating story the moment a flag goes live. Planning, shipping and measuring all happen in the same place – no reconciling between tools, no separate contracts, for less than the per-user cost of any one of them.

• How do AI agents use context in Atono across sessions?

  

  Every story in Atono carries three persistent context tabs – Design decisions, Technical investigation, Technical changes – written and updated by AI agents via MCP as work progresses. When an agent opens a story in a new session, it reads all three tabs automatically before acting. Context is versioned and attributed, so engineering leaders can see what each agent decided and when. Multiple agents can work on the same story across a sprint without losing or duplicating context.

• Is Atono free?

  

  Atono is free for teams up to 25 users – no credit card required and no expiration. Paid plans add AI functionality and scale to any team size.