Jindo AI builds Pawsly to fix coordination failures in parallel coding agents

Developers running multiple AI coding agents simultaneously often face a hidden problem: each agent works in isolation, causing conflicts, stale context, and broken merges when their work is combined. Jindo AI founder identified three core failure points — branch conflicts, decision drift across sessions, and faulty handoffs between agents. To address this, the company built Pawsly, a coordination layer that gives all agents a shared live plan, explicit roles, real-time context updates, and tracked handoffs. Internal benchmarks showed that with four agents, standard shared Git produced consistent, non-conflicting work only 3 out of 10 times, while Pawsly achieved 9 out of 10. The company has published its full benchmark methodology and results, including unflattering data, at jindoai.net/engineering.