Lightsprint

Product managers, designers and ops people typically depend on engineers to implement even small changes, creating bottlenecks and handoff friction between teams. Meanwhile, AI coding agents today mostly run solo inside one developer's IDE, so the rest of the team falls out of sync and cannot see or steer the work. Feature requests arrive through tools like Linear, Jira and Slack but still require manual translation into engineering tasks, and feedback from customers or sales often gets stuck before it becomes a shipped feature. This leaves non-engineers unable to turn ideas into working software without waiting in an engineering queue.

Lightsprint lets anyone on a product team describe a change in plain English, then uses cloud AI agents to build it, spin up a live preview sandbox, and run automated QA and testing before engineers review and approve the final PR. It plugs into existing tools and workflows: tasks can start from Linear, Jira or Slack and ship as a PR to GitHub or Bitbucket, with no migration required. Teams can bring their own model or subscription (including Claude, Codex, GPT, Gemini and others via OpenRouter), save shared 'skills' like design.md or review.md so every teammate or agent follows the same conventions, and collaborate in shared agent sessions where multiple people can watch a build and weigh in live. A merge readiness score and checks like tests, design-token linting, accessibility contrast and dependency resolution are shown before engineers approve the PR.