Launched this week
Revolte
AI for Software Engineering
396 followers
AI for Software Engineering
396 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.
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The 'engineers approve the important decisions' angle is smart — too many AI coding tools skip the governance layer entirely. Curious how Revolte handles merge conflicts when multiple agents touch the same file?
Revolte
@xiaosong001
Thanks! Really glad that resonates — the governance layer is something we’ve been intentional about from the start.
On merge conflicts — Revolte uses a sequencing mechanism so agents don’t touch the same file at the same time. If a conflict does come up, it gets flagged to the human reviewer to resolve rather than the agent guessing its way through it.
how are you guys actually indexing the codebase for the planning and PR agents? are you running an upstream embedding sync on your cloud servers or does revolte run a local daemon process that evaluates repo context directly through a gateway connection?
extending the agentic context to the full lifecycle outside the IDE is the absolute logical next step for engineering teams. outstanding work on this Raj...
Revolte
@priya_kushwaha1
Thank you, really appreciate that!
To answer directly — Revolte runs on cloud, and yes, we use embeddings to index and understand the codebase. Each App or Service maintains its own context through this embedding layer, which is what the planning, coding, and PR agents draw from when executing workflows. It’s not a local daemon — it’s a cloud-based sync that keeps context current and available across all agents and workflows, including Revolte Code for human review.
And you’ve framed it well — extending agentic context across the full SDLC rather than keeping it locked inside the IDE is exactly the problem we set out to solve.
Lancepilot
Congratulations to Raj and the Revolte team on the launch 🚀
I hunted Revolte because it’s one of the few AI engineering platforms I’ve seen that looks beyond code generation and focuses on the real bottleneck: getting software safely from intent to production.
A lot of AI dev tools make engineers faster inside the IDE. That matters, but it doesn’t solve the full delivery problem. The hard part is everything around the code, planning the change, understanding the existing codebase, running the right checks, creating the PR, supporting deployment, watching what happens at runtime, and knowing what to do when something breaks.
That’s where Revolte feels different to me.
Their bet is not that AI should blindly replace engineering judgment. It’s that agents can take on more of the SDLC heavy lifting if the trust model is designed properly, with the right approval gates, visibility into the diff and reasoning, quality and security checks, and rollback paths where they matter.
That’s the version of AI for software engineering I can actually see moving into real production codebases.
Two things I’d encourage people here to look at closely: the per-service pricing model, which is very different from the usual per-seat AI tooling model, and the CLI/workflow experience, because engineering teams don’t want another SaaS dashboard unless it genuinely removes work.
Excited to see how the Product Hunt community responds to this.
Raj and team have clearly thought deeply about where AI belongs in the software delivery lifecycle. Looking forward to the discussion.
Revolte
Thanks you,@istiakahmad this means a lot.
You captured the heart of it perfectly: the bottleneck was never code generation, it's everything around the code, getting a change safely from intent to production. That's the whole thing we obsess over, and the trust model is exactly where we've spent the most time, approval gates, visibility into the diff and reasoning, the checks and rollback paths.
And appreciate you flagging the per-service pricing and the CLI experience for people to dig into. Grateful to have you hunting us today. 🙂
does it mean this will work starting from the idea with a small title - "like create AI note pad" to autonomous implementation?
@maksym_shcherbakov1 Yes, that is the direction, but we don’t think of it as blind autonomy from a vague title.
Something like “create an AI notepad” can definitely be the starting point. Revolte would help turn that into a clearer spec, break it down into implementation steps, generate the code, create tests, open PRs, and keep humans involved at the right review points.
The goal is to take an idea and move it through planning, implementation, validation, and approval with enough context and control around the workflow.
Revolte
@maksym_shcherbakov1
Great question! Almost — but not quite from a single title alone.
Revolte runs on spec-driven development, so the starting point is a spec rather than a loose idea. Think of it less like "create AI notepad" and more like a defined set of requirements for what that notepad should do, how it should behave, and what the acceptance criteria are.
Once that spec exists, yes — Revolte takes it from there autonomously. Planning, coding, testing, security checks, PR — all the way through without hand-holding.
The spec is the foundation that makes autonomous execution reliable. Without it, agents are guessing — and that’s where things go wrong.
Revolte
Greetings Product Hunt 👋 this is Watson from @Revolte
One thing we kept hearing from engineering teams was this:
AI helps teams write more code. But WHY shipping software to production still feels painfully operational — and WHY no serious engineering team fully trusts AI near production yet.
The hardest balance in AI software delivery today :
Too much approval, and the product becomes another workflow layer engineers have to babysit.
Too much autonomy, and no serious team will trust it near production.
Automation should handle the repeated delivery work
environment setup, test runs, build management, deployment support, runtime monitoring, and coordination.
Human judgment should stay where it matters: code merges, production changes, infra-sensitive decisions, security-sensitive changes, and rollback paths.
This balance is the product. We went through many versions before landing on the current model.
And honestly, that’s where a lot of AI ROI still gets stuck inside real engineering organizations.
We believe the future isn’t just AI generating code — or engineers manually coordinating every step around software delivery forever.
It’s intelligent execution systems continuously carrying delivery work forward while engineers stay focused on architecture, reliability, product thinking, and technical judgment.
That’s the balance we’ve thought deeply about while building Revolte — and where the compounding value really starts.
Would genuinely love feedback from the PH community ❤️
this is actually a really cool application. howd you come up wih the idea? I make AI plugins for premiere pro and adobe, do you think I could use it?
Revolte
@devinhuynh Thank you, really appreciate that!
The idea came from a simple frustration — most AI coding tools are built for individual productivity, making one developer faster. But the real bottleneck in software delivery is team collaboration and managing the entire SDLC together. That’s what Revolte is built to solve — not speeding up one person, but making the whole team and process more effective.
And yes, absolutely — if you’re building AI plugins for Premiere Pro and Adobe, Revolte can work for you. As long as there’s a development and delivery process involved, Revolte can manage it. Creative tooling is still software — it still needs planning, coding, testing, and review. Revolte handles all of that, whatever you’re building.
Lancepilot
Excited to share that we’re launching Revolte today.
Revolte around a simple belief: software teams should spend more time building great products and less time dealing with delivery complexity.
Today, engineering teams jump across multiple tools for planning, coding, testing, deployment, and production monitoring. A lot of valuable time gets lost in handoffs, repetitive workflows, and operational overhead.
That’s why created Revolte.
Revolte is AI for software engineering, helping teams move faster from intent to code, testing, deployment, and production, while keeping engineers in control throughout the process.
With Revolte, teams can:
⚡ Build faster
🧪 Automate testing and release workflows
🚀 Ship with less operational overhead
🔍 Monitor production with greater visibility and confidence
Building this for developers, engineering leaders, and teams that want to ship faster without adding more complexity to their workflow.
Would love to hear your thoughts, if AI could take over one painful part of your software delivery workflow, what would you want it to handle?
Thanks so much for checking out Revolte 🙌