Recent Updates

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General Availability — Controlled AI Engineering

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Controlled AI Engineering Workflows & Grill Mode

Beta V2.1.1 introduces Revolte’s controlled AI engineering workflow. Bring engineering intent, repository context, and supporting information together to execute complex multi-file changes with complete developer visibility.

• Grill Mode intent clarification: Asks focused questions when requirements are ambiguous, or moves straight to planning when intent is clear.
• Interactive plan review: Inspect, update, and approve execution plans before code modifications begin.
• Live execution visibility: Follow step-by-step progress, inspect tools in real time, and view outputs as work happens.
• Human-in-the-loop controls: Pause execution, provide guidance mid-task, or stop work safely while retaining progress.

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Unified Workspace & Context

Connected project, application, and repository context across engineering sessions.

• Session tabs & history: Switch between active engineering tasks like tabs and resume past sessions seamlessly.
• Connected application context: Start tasks against specific applications instead of isolated chats.
• Multi-source context attachments: Attach specs, design docs, logs, and supporting files directly to tasks.
• Repository awareness: Connect GitHub repositories for full codebase structure and dependency understanding.

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Code Review & Pull Request Delivery

Ship reviewed AI-generated changes directly into your existing workflow.

• Direct GitHub commits: Push approved code changes directly to target branches.
• Pull Request creation: Convert completed AI tasks into review-ready pull requests for team inspection.
• Continued iteration: Refine and update code changes within the same task thread.

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Early Access Release — Core Platform Foundation

Over the last two weeks leading into delivery governance, engineering focus centered on benchmarking, task reliability, and project monitoring.

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Access & Organization

Simple, secure authentication and workspace access management.

• Simple & secure authentication: Email OTP login for frictionless access.
• Team invitations & organization onboarding: Onboard team members via invite links and manage organization workspaces.
• Smart post-login routing: Direct new users into onboarding flows or active workspaces.
• Workspace membership controls: Manage organization membership and workspace permissions.
• Authenticated session management: Maintain secure login sessions across workspaces.

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Engineering Workspace & Repository Management

Structure engineering work around projects, applications, and source control repositories.

• Project & application hierarchies: Group applications inside projects with connected repository links.
• Repository connectivity: Link GitHub repositories directly to applications.
• Persistent task resumption: Resume engineering tasks after repository connection without losing progress.
• Structured workspace organization: Keep related applications, repositories, and sessions logically grouped.

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Core AI Execution & Guided Workflows

Task-driven development from prompts or Jira tickets with live progress inspection.

• Jira ticket-led tasks: Start engineering tasks directly from Jira tickets using ticket details as the brief.
• Prompt-driven task execution: Run multi-file engineering tasks directly from natural language prompts.
• Requirement clarification workflow: Interactively refine requirements before execution begins.
• Execution plan review & approval: Review and approve step-by-step plans prior to file edits.
• Chat-to-workflow execution: Kick off AI execution directly via a “Run” action upon plan approval.
• Dual-tab workflow view: Open a dedicated Workflow tab alongside chat to inspect detailed execution steps.
• Live progress stepper: Track a live checklist showing completed, active, and upcoming steps.
• Output & artifact inspection: Review generated source code, diffs, and execution logs.

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Deployment & Project Monitoring

Full visibility from code commits to deployment health and project metrics.

• Facelifted deployment workflow: Configure environment variables and trigger deployments directly within Revolte.
• Project application dashboard: View all project applications with repository links and last run results.
• Recent workflow run history: Track the last 5 workflow runs with status, duration, and user attribution.
• One-click app workspace launch: Launch directly into the AI workspace pre-loaded with an application.
• Environment & status filtering: Filter applications by Production status or failed run states.
• Deployment health & DORA metrics: Track shipping frequency, failure rates, and recovery times for production environments.
• Project deletion safeguards: Require project name confirmation before deletion to prevent accidental removal.

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Product Roadmap

Revolte is evolving from AI-assisted development into an AI-native engineering platform for teams and enterprises.

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v1.0 — Controlled AI Engineering Foundation

Establishing the core experience where developers bring engineering intent, code context, and AI execution together.

• Unified AI workspace: Single place to start engineering tasks through chat and CLI.
• Code-aware understanding: AI works with repository context instead of isolated prompts.
• Jira-led engineering flow: Task-driven workflows directly from engineering tickets.
• Single-agent execution: Reliable execution foundation before moving into multi-agent experiences.

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v2.0 — Autonomous Engineering Workflows

Expanding Revolte with richer intent understanding, autonomous workflows, and enterprise-ready engineering experiences.

• Richer engineering intent: Capture requirements through voice and improved developer intent understanding.
• Background AI agents: Allow AI work to continue asynchronously while teams focus on other tasks.
• Improved maker-checker workflows: Strengthen validation, testing, and review before changes move forward.
• Workflow hub: Create reusable engineering workflows for repeatable delivery patterns.
• Demo-to-production workflows: Move from prototypes to production-ready applications faster.
• Enterprise engineering workflows: Support organization-wide delivery standards.
• Multiple engineering entry points: Enable workflows through tools teams already use.

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v3.0 — Enterprise AI Engineering Platform

Helping organisations confidently operate AI-driven software delivery with visibility and control.

• Step-level execution control: Review, pause, approve, or guide AI actions at important moments.
• Outcome intelligence: Connect engineering activity with delivery outcomes and DORA insights.
• Risk-based approvals: Apply different approval policies based on environment and business risk.
• Multi-agent collaboration: Enable multiple AI agents to work together on complex engineering tasks.
• Organization-level AI knowledge: Build shared engineering intelligence as a long-term enterprise advantage.
• Compliance and audit readiness: Provide visibility required for governed enterprise adoption.
• Marketplace ecosystem: Extend Revolte with reusable workflows, integrations, and capabilities.