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Revolte
AI for Software Engineering
818 followers
AI for Software Engineering
818 followers
Revolte is for engineering teams to turn intent into production-ready software faster, safer, and with more control. Its agents plan changes, generate code, run quality and security checks, create PRs, support deployment, monitor runtime behavior, and surface risks early. Engineers approve the important decisions. Revolte handles the delivery heavy lifting. Built for higher delivery throughput across SDLC, stronger governance, and more value shipped per engineer.
This is the 2nd launch from Revolte. View more
Interactive Sessions
Launching today
Different work needs different AI oversight, and Revolte gives you both. Our Interactive Sessions let you drive the full lifecycle with the agents, step by step: architecture, code, tests, staging, deploy. You approve every step. Autopilot mode hands off a Jira ticket end-to-end, with agents planning, coding, opening the PR, and deploying. Same workspace, same governance: plan approval, inline diffs, cost caps, and audit trails, built in. Hands-on when you want control, hands-off when you don't.
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Launch Team / Built With
Revolte
Hey PH 👋 Raj here, co-founder & CEO of Revolte.
Every AI dev tool makes you pick a side. Cursor is hands-on: you're in the loop for every keystroke. Devin is hands-off: you hand it a task and check the result. Both are good, but neither is enough on its own for a real team. Because different work needs different oversight.
A tricky refactor in your payments service? You want hands-on. A backlog of dependency bumps? Hand it off. The real question isn't "do we adopt AI?" It's "how do we adopt it across different work with different risk profiles?" Nobody's answering that.
So we built Revolte to give you both, in one workspace.
Autopilot mode (from our previous launch) takes a Jira ticket and runs it end-to-end through PR and deploy, with engineers approving the meaningful steps.
Today we're adding Interactive Sessions: a tabbed workspace where you drive the full lifecycle with the agents directly, architecture, code, tests, staging, deploy. One session per task, you approve every step. No Jira required. Sign up and start in under a minute.
Same governance layer for both. Plan approval before code, inline diffs before merge, cost caps before deploy, audit trail on every action.
Hands-on when you want control, hands-off when you want throughput. Same platform, same procurement conversation.
Would love the hard feedback, especially from engineering leaders figuring out how to adopt AI across teams with different risk appetites. That's the problem we built this for.
@rajagopalanar signed up out of curiosity and had a session going in under a minute with non setup that low barrier to try is rare and it matters good work team.
Revolte
@priya_kushwaha1 We wanted to create ease of use and less barrier for users to start using product. Glad to know that it reflects. Thanks
@rajagopalanar congrats on the launch,best of luck you guys. i supported you guys
Looks exciting! My only question is when do I trust an AI agent enough to let it touch my codebase?
Revolte
@new_user___2432026393c9df85f17fd58 Great question. When you can control everything that AI does. If you just see AI as a junior engineer, who knows enough to do development but not enough to be trusted to ship to production, thats exactly the state AI is now. We have been following quality gates in SDLC all along. If you follow the gates and have control you could trust AI agents.
Revolte gives full control to you to see what AI agents does, and lets you to control approval flow.
Buffup.AI
For me the biggest question would be deployment confidence. what happens when an agent hits something unexpected mid deploy?
Revolte
@sansa_grey Thats a good question. We dont allow agents to directly deploy. There are clear quality gates. Agents first deploy in preview environment, developers validate the code & output and then approve the code to be pushed to main branch. Then the main branch is deployed in production. This helps to have good control over ai. Hope this answers your question.
I can see Interactive Sessions being useful for unfamiliar codebases. does the agent keep context across those sessions?
Revolte
@alira_salu Yes. Agent carries the context across sessions.
Honestly i would be more interested in the failure cases than the happy path. Whats the most comman reason an agent run gets stopped?
Revolte
@aatheeswaran Thanks, two modes is definitely what we are excited about. But it's slightly different than chat and cowork though in terms of switching interfaces. More like where do you need more control vs where it can be completely autonomous. Appreciate you taking your time to try 🙏
Revolte
@aatheeswaran thanks. Glad that you could feel the ease of use while using the product.
Revolte
@suraj_ss Haha, love this. This concept of taking an idea/intent to something functional and scalable is what we are trying to achieve with Revolte. We welcome your feedback after you try!
Revolte
@suraj_ss Thanks, would appreciate that. Please try as many ideas as possbile and scale them to production standard in revolte.