Hey PH 👋 Raj here, co-founder and CEO of Revolte. We started Revolte because engineering teams spend most of their time on work that sits around the code, not on the code itself. Setting up environments. Running tests. Managing deploys. Triaging incidents. Updating tickets after the fact. Hiring more engineers takes months. Building an internal platform takes a year and a dedicated team. Coding copilots like Cursor and Copilot help engineers write code faster, but the bottleneck stopped being the writing a long time ago. So we made a different bet with Revolte: the AI should run the lifecycle, not the IDE. The agents pick up the ticket, write the code, run the tests, open the PR, deploy the build, watch the runtime, and triage incidents when things go wrong. Every change passes through an engineer before it merges. You see the diff, the reasoning, and the rollback path, the agent never ships anything you didn't approve. This is the part most AI coding tools get wrong, and it's the reason teams quietly stop using them after their first bad merge. The surprising part is what this unlocks. Once shipping a feature no longer requires an engineer at every step, the work changes shape. Your senior engineers stop spending their week on tickets that don't need them. The team starts shipping ideas they used to shelve because no one had the capacity. Roadmaps stop being constrained by how many people you can hire and start being constrained by how many decisions you can make. We built Revolte for engineering teams that want to ship more without growing the team to do it. If that's you, try it at revolte.ai. And if you're an engineering leader thinking about deploying agents into a real codebase but want to talk through the governance side first, DM me, happy to walk through how it works on your stack. Would love your feedback.

Revolte

AI for Software Engineering

AI for Software Engineering