Interactive Sessions by Revolte - Drive the full SDLC with AI agents, step by step
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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.
Replies
HarnessRouter
Revolte
@kuanzema Thanks. Great to hear your feedback. You could use our CLI for greater control(human in the loop) for factory model.
Lancepilot
Revolte
@priyankamandal Thanks for rightly pointing the governance angle. That is exactly the gap we are looking to close.
Revolte
@The @priyankamandal Great that you have noticed it. Yes, governance makes all the difference for enterprises and startups who wanted to have absolute control of their tech stack and customer data. @Revolte we are not just want AI to code but to use AI to automate entire SDLC where governance and security becomes the most important layers.
Appreciate this,a lot of it makes sense. Especially chat-flow for the most of the SDLC
Revolte
Appreciate it, lot of work has gone into it.
Happy launch day team. Proud of this one. The interesting thing I found here is the CLI factory model
Revolte
@suvetha_devi_r yes, we believe CLI factory model is so powerful in having autonomy and greater control
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.
Revolte
@gideon_henry Yes. Glad that you like this. We are also planning some feature that integrate with Jira for ticket grooming.
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.
Buffup.AI
@rajagopalanar That clears it up. I like the preview-first approach, especially having developers validate both the code and the output before anything reaches production. It feels like a good balance between automation and control.
Revolte
@sansa_grey Thanks thats great question. We don't allow any agent directly to deploy rather, we allow agents/workflows only to plan, architect, code/write test cases. All of these are artefacts which are saved as text or code in your repo. Code output will be always raised as PR from agent or workflow. On approval, rest of the deployment steps works. For all the deployment steps, we have automated with engineering logics in the product rather than using AI. This assures certainty.
I can see Interactive Sessions being useful for unfamiliar codebases. does the agent keep context across those 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
@manjesh_yadav1 Agents dont get stopped but the output that are provided by agents are not what we anticipate. This is usual expected scenario. The way to go about this is having to tweak prompt, ground the agent and have clear context. If any one if this is not good, the results will not be good. The way to improve output is to improve these. The way to measure these is confidence score. So you could look at confidence score in Revolte to see if you would be assured results
@rajagopalanar That makes sense. I think having a confidence score would be useful when the output looks right but you still arent sure how reliable it is
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.
Revolte
@harini_govind That's what we are trying to achieve, glad it landed.
Revolte
@harini_govind yes thats the idea. Glad that like the product.
Cluing
Interesting approach, saving this for later.
Revolte
@ralic thanks. appreciate if you could trial and give feedback.