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AI for Software Engineering. Revolte executes your complete software delivery lifecycle - code, tests, deployments, and operations.Engineers stay in control.

London
Joined March 2025
Photo by revolte.ai (@Revolte_ai)Photo by revolte.ai (@Revolte_ai)Photo by revolte.ai (@Revolte_ai)Photo by revolte.ai (@Revolte_ai)Photo by revolte.ai (@Revolte_ai)
The future of engineering isn't autonomous systems that replace judgment. It's systems that amplify judgment. Different thing entirely.
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If your CI/CD is still manual gates, deployments make you nervous, and teams can't ship in confidence... you're not using AI across the SDLC. You're using it in pockets. 🧵
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The gap: Most teams have one. They've added Copilot to dev workflows but haven't connected it to the rest of the lifecycle. Result: Faster code, same ship cycle.
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SDLC-level AI orchestrates from intent → production. Planning, code, tests, release, observe. That's how you actually move the needle on delivery metrics. Interested? Let's talk: revolte.ai
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"Developers just code" and "ops disappears" are comforting myths. The reality: both become more visible, more measured, more deliberate. That's actually better.
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When AI executes the SDLC, governance becomes essential. Code review gets stricter. Release gates get clearer. Observability becomes mandatory. Less "automation magic," more "intentional execution under control." Boring, maybe. Powerful, definitely.
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Where's your biggest delivery blocker right now? Testing (manual, slow) | Deployment gates (too many, too slow) | Production issues (discovery/fix lag) | Team coordination (alignment overhead) Reply with your answer if it's not listed 👇
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Your developers use AI to write code faster. Your releases are still every 2 weeks. Something's not connecting.
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Most teams measure: "How many devs use AI?" "Lines of code generated?" The right questions: "Did lead time drop?" "Is deployment frequency higher?" "Are we releasing with more confidence?" Those numbers are flat for most orgs using AI.
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The future isn't "AI makes devs faster." It's "AI executes the delivery lifecycle while teams stay in control." That's a different game entirely. Building for that shift right now.
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AI made developers faster🤞 Most engineering organizations are still shipping the same way. Revolte is AI for Software Engineering. Humans define intent. Humans govern outcomes. Revolte executes the SDLC. 8x faster releases. Full control over IP and cost. #AISDLC #Revolte
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Revolte got Featured at Top 5 on @ProductHunt 🚀 258+ upvotes and strong feedback from builders, founders, and engineering teams. A meaningful milestone for the #AI for Software Engineering. Thank you to everyone who supported, commented, challenged, and shared feedback.
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Engineering teams don’t need another AI demo. They need measurable outcomes: Faster release cycles. Faster testing and deployment. Fewer production incidents. Clearer visibility across stack. Revolte brings AI across the software delivery lifecycle, from intent to production.
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We're live on Product Hunt 🚀 Revolte is AI for the full software delivery lifecycle. Code, tests, deploys, runtime. Engineers approve every meaningful change, the agent handles the rest. Would love your supportRevolte: producthunt.com/products/rev…
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Software teams don’t just write code. They build new apps. Operate production. Evolve features. Migrate legacy systems. Revolte brings AI across these workflows — from intent to production. Every action stays visible, reviewable, and reversible. #AI #SDLC #AIEngineering
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AI has made developers faster. But delivery is still stuck in fragmented tools, reviews, handoffs, deployments, and production risk. @Revolte_ai is AI for Software Engineering — from Jira to production. AI does the heavy lifting. Engineers stay in control. #AI #SDLC
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