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.
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.
Alongside our product launch. It started as a real internal need from one of our team.
If Revolte can reshape the AI-SDLC, building one more internal tool isn’t the story. The story is the shift: The recorder is just the first cut. The real proof is the system that built it — AI-SDLC, from intent to production-ready execution.
One of our teams needed a simple product/QA recording workflow. The usual answer would have been: approve another tool, add another subscription, and adjust our process around it.
But with Revolte, we asked a different question: why buy more when we can build the exact production gap ourselves?
The first cut already gave us that “wow” moment — tailored to our workflow, scalable, and ready to evolve with the team.
Revolte changes the AI-SDLC — from idea to production-ready software. A new way of thinking about software delivery.
Hunters, what would you build with Revolte?
P.S. I’m in a different TZ, will catch up soon.🙏
Congrats on the launch. Giving teams both Interactive Sessions and Autopilot under the same governance layer is a practical approach to handling different levels of risk and oversight.
Nice that Revolte does the delivery grunt work but leaves the big calls to engineers. What happens when one of its PRs needs a security fix after it's already merged?
Nice one. Having both modes makes sense - hands-on for the risky stuff, autopilot for the boring tickets. Good luck today!
Love that you made "you approve every step" a first-class feature instead of chasing full autopilot; that trust-through-control approach is exactly what engineering teams actually need.
Really like the idea of how Revolte can work with both new ideas and existing codebase. Feels much closer to how real engineering teams actually work.
Honestly i would be more interested in the failure cases than the happy path. Whats the most comman reason an agent run gets stopped?
I can see Interactive Sessions being useful for unfamiliar codebases. does the agent keep context across those sessions?
The audit trail caught my attention more than the code generation. are teams using it mainly for governance or debugging too?
For me the biggest question would be deployment confidence. what happens when an agent hits something unexpected mid deploy?
Cost caps + audit trails are underrated. agent autonomy gets much easier to sell when there is a clear paper trail.
The step by step approval model feels practical. i would trust autopilot more after seeing exactly where i can intervene.
No Jira required for Interactive sessions is a nice touch. Sometimes you just want to take an idea and start working on it without turning it into a ticket first.
The approval flow is probably the part that makes this easier to trust. having AI do the work is one thing, knowing exactly where a human can step in is another.
Looks exciting! My only question is when do I trust an AI agent enough to let it touch my codebase?
About Interactive Sessions on Product Hunt
“Drive the full SDLC with AI agents, step by step”
Interactive Sessions launched on Product Hunt on August 31st, 2026 and earned 273 upvotes and 86 comments, earning #3 Product of the Day. 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.
Interactive Sessions was featured in Software Engineering (42.9k followers), Developer Tools (518.5k followers) and Artificial Intelligence (477.4k followers) on Product Hunt. Together, these topics include over 206.8k products, making this a competitive space to launch in.
Who hunted Interactive Sessions?
Interactive Sessions was hunted by ISTIAK AHMAD. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.
Want to see how Interactive Sessions stacked up against nearby launches in real time? Check out the live launch dashboard for upvote speed charts, proximity comparisons, and more analytics.
ISTIAK AHMAD
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.