Connected
Planning
Jira
Turn tickets into tracked work items that agents can claim and complete.
VibeFlow
Ship Quality & Secure code while you sleep.
A full AI engineering team — developer, architect, PM, QA, security, and DevOps — that shares context, remembers decisions, and ships code autonomously. This isn't autocomplete. It's an AI team that knows your codebase.
The VibeFlow Difference
Velocity, security, and quality — in one platform
How governed AI agent teams compare with traditional coding and unmanaged vibecoding across the three dimensions that matter most.
Visual 1 · Velocity
Ship rate vs traditional coding
Traditional coding
1X
Human-written baseline
Vanilla vibecoding
5–8X
AI-assisted, ad-hoc
VibeFlow vibecoding
60X
Governed agent teams
Visual 2 · Security
Security issues caught during development
0%
Traditional coding
Caught post-release, in production
0%
Vanilla vibecoding
No security review in the loop
100%
VibeFlow vibecoding
Every change scanned before merge
Visual 3 · Quality
Built-in quality gates
QA run on every code change
TraditionalNot supported
Vanilla vibecodingNot supported
VibeFlowBuilt-in
Automated unit tests
TraditionalNot supported
Vanilla vibecodingNot supported
VibeFlowBuilt-in
Automated post-commit QA
TraditionalNot supported
Vanilla vibecodingNot supported
VibeFlowBuilt-in
AI code review before merge
TraditionalNot supported
Vanilla vibecodingNot supported
VibeFlowBuilt-in
Shared context memory
TraditionalNot supported
Vanilla vibecodingNot supported
VibeFlowBuilt-in
Dimension
Traditional
Vanilla vibecoding
VibeFlow
QA run on every code change
Automated unit tests
Automated post-commit QA
AI code review before merge
Shared context memory
Built-in Not supported
Stop vibe coding. Start shipping with confidence.
One governed pipeline. Every feature flows through planning, implementation, testing, security review, and QA — all autonomous, all auditable.
Real Codebases, Real Gains
Real projects. Real AI teams. Production code shipped autonomously.
Customer StoryVibeFlow has fundamentally changed how I build software. It allows me to code from anywhere, even directly from my mobile phone, which makes it incredibly convenient to capture ideas and implement changes on the go.
57×
37/38
Features
296/296
Todos
362/362
Issues
2d 23h
Work Time
+65,341
-17,310
Lines
169d 14h
Human Est.
Integrations
Connect VibeFlow to the tools already driving the work
Bring planning, documentation, source control, and design into one governed delivery loop. VibeFlow works from the systems your team already trusts instead of forcing copy-paste handoffs between tabs.
Requirements in syncDesign-ready implementationRepo-native delivery
Keep Jira, Confluence, Bitbucket, GitHub, and Figma connected to the same autonomous workflow instead of treating them as isolated reference points.
Planning, knowledge, repos, and design
Connected
Knowledge
Confluence
Pull in specs, requirements, and architectural decisions before execution starts.
Connected
Source Control
Bitbucket
Keep branch workflows, pull requests, and delivery history visible inside the loop.
Connected
Engineering
GitHub
Link issues, PRs, and commit trails so every change stays auditable.
Connected
Design
Figma
Ground implementation in real designs instead of letting agents guess the UI.
AI agents are powerful.
Without structure, they're unreliable.
Every session starts from scratch. Agents forget what they learned, step on each other's work, and burn tokens re-discovering context that should have been persisted.
Context Loss
Agents start fresh every session. Architecture decisions, file conventions, and past failures are gone — forcing you to re-explain everything.
No Coordination
Multiple agents step on each other's work. No locking, no claiming, no awareness of what other sessions are doing.
No Work Queue
You manually tell agents what to do every time. There is no structured backlog, no priority ordering, and no autonomous task discovery.
Design Drift
Agents ignore your design system, invent their own conventions, and produce inconsistent code because specs live outside their context window.
No Audit Trail
No trace from requirement to implementation. You cannot see which agent changed what, when, or why — making debugging a guessing game.
Wasted Tokens
40-50% of tokens are spent on repeated context. Every session re-reads the same files, re-discovers the same patterns, and re-learns the same conventions.
The difference VibeFlow makes
Go from manual, session-by-session AI coding to fully autonomous, context-aware development with persistent memory.
Before VibeFlow
Re-explain project architecture every session
Agents forget conventions and repeat mistakes
No structured work queue — manual instructions only
Design specs pasted into chat, lost when session ends
Agent finishes one task, then waits for you
No audit trail from requirement to code change
With
VibeFlow
Agents load full project context automatically
Persistent memory captures conventions and gotchas
Structured work queue with priority-based polling
Design docs attached to features, loaded on demand
Continuous autonomous operation — zero idle time
Every task traced to a git commit with line counts
Agent TeamsStop coding alone.
Stop coding alone.
Build with an AI team.
VibeFlow gives you a full team of AI specialists — a developer, architect, product manager, QA engineer, security lead, and DevOps engineer — all sharing context and working together on your project.
Alex
Senior Software EngineerYour workhorse. Give Alex a feature spec, a bug report, or a todo — and get back working code with tests, committed to a clean branch.
- Implements features end-to-end
- Follows your project conventions automatically
- Commits with meaningful messages and clean diffs
Aria
Senior Product ManagerThinks about the why before the what. Creates PRDs, writes strategies, defines requirements, and ensures the team builds the right thing.
- Drafts PRDs, strategy docs, and feature specs
- Defines acceptance criteria and success metrics
- Reviews output from a product perspective
Morgan
Senior ArchitectLooks at the big picture. Designs systems, data models, API contracts, and catches design flaws before they become expensive refactors.
- Designs system architecture and data models
- Reviews code for scalability and maintainability
- Documents architectural decisions (ADRs)
Quinn
Senior QA LeadThinks about everything that can go wrong — and writes tests to prove it won't. Ensures the code your team ships actually works.
- Writes comprehensive test suites
- Identifies edge cases and failure modes
- Validates against acceptance criteria
Sophie
Security LeadScans every change for security issues — injection vulnerabilities, auth gaps, data exposure risks, and compliance violations.
- Identifies OWASP Top 10 vulnerabilities
- Validates authentication and authorization flows
- Ensures SOC 2, HIPAA, ISO 27001 compliance
Casey
Customer AdvocateThe voice of the customer inside every sprint. Casey maps user needs to product decisions and ensures every feature delivers real customer value.
- Translates user feedback into actionable requirements
- Validates features against customer success metrics
- Ensures UX consistency and customer journey alignment
Parker
DevOps EngineerHandles the last mile — getting code from a branch to production safely. Deployment configs, CI/CD pipelines, and operational monitoring.
- Configures deployment pipelines and GitOps
- Sets up monitoring, alerting, and logging
- Orchestrates canary deployments and rollbacks
Dana
UX DesignerDesigns the user experience before code is written. Dana creates wireframes, defines interaction patterns, and ensures every interface is intuitive and accessible.
- Creates wireframes and interaction specifications
- Enforces design system and accessibility standards
- Reviews UI implementations for UX consistency
Kai
Principal EngineerThe technical strategist. Kai reviews architecture decisions, mentors the AI team, resolves complex cross-cutting concerns, and ensures technical excellence across the codebase.
- Reviews architecture and cross-cutting concerns
- Resolves complex technical decisions and trade-offs
- Ensures code quality, performance, and maintainability
Precision context. Every level.
Not a giant context dump. VibeFlow organizes knowledge at four levels — project, feature, todo, and issue — so agents load only what's relevant to the task at hand. The result: faster execution, fewer tokens, zero hallucination from stale context.
L1
Entire projectProject Context
Architecture & stack decisions
Cross-feature conventions & patterns
Session history & commit log
Key files & directory map
L2
Per featureFeature Context
Feature-specific gotchas & decisions
Implementation checklists
Component architecture & file map
Design docs & style guides
L3
Per work itemTodo & Issue Context
Attached PRDs & acceptance criteria
Wireframes & visual references
Linked documents & assets
Execution logs & progress history
L4
Every commitGit-Backed Truth
Full commit attribution per agent
Line counts added & deleted
Traceable from requirement to code
Version-controlled & auditable
When Alex works on Todo #247, VibeFlow loads the project architecture, the parent feature's gotchas, and the todo's attached design doc — nothing more. Precision retrieval means fewer tokens, faster execution, and zero noise from unrelated context.
"It's like having a team that's been working on your project for a year, from day one. They know the codebase, they know the patterns, and they never forget a lesson learned."
Everything agents need to ship autonomously
Seven integrated capabilities that turn AI coding agents from powerful-but-chaotic into reliable, autonomous implementers.
Visual Project Management
A drag-and-drop swimlane board that gives humans full visibility into project status. Features flow through a defined lifecycle — from planning to done — with real-time status updates and progress tracking.
- Nested hierarchy: Projects, Features, Todos, and Issues
- Auto-refresh dashboard with real-time status updates
- Status cascade — completing all todos marks features done
- Progress tracking with completion percentages and counts
Ready to replace isolated coding sessions with a governed AI engineering team?
Get Started for FREEFrom plan to shipped code
Five steps from a feature request to a verified git commit. Humans plan, agents execute, VibeFlow orchestrates.
Step 1
Plan the work
Define features, write specs, attach design docs and context files in the visual dashboard.
Step 2
Agent initializes
Agent calls session_init, loads project context, design docs, and discovers the work queue.
Step 3
Autonomous execution
Agent polls for work, implements features, runs tests, and commits to git with tracked line counts.
Step 4
Context captured
Agent updates context files with what it learned — gotchas, decisions, and implementation notes.
Step 5
Review & repeat
Check the kanban, verify QA, approve or reject. Agent polls for the next item automatically.
Cut token costs by 45-65%
Structured context loading eliminates redundant token consumption. Agents spend tokens on implementation, not re-discovering your codebase.
Vanilla Vibe Coding
Tokens per task~50K
Context overhead40-50%
Work discoveryManual
Session continuityNone
Agent idle timeHigh
With VibeFlow
Tokens per task~25K
Context overheadStructured loading
Work discoveryAutonomous polling
Session continuityPersistent memory
Agent idle timeZero
Terminal UI for all your agents.
A terminal-native session manager that lets you launch, switch between, and supervise multiple AI coding agents from a single interface. Whether you're running Claude Code, OpenAI Codex, or Google Gemini — VibeFlow CLI keeps them all organized, isolated, and productive.
Open source on GitHub
Multi-Session Management
Launch multiple AI coding sessions in isolated tmux sessions. Switch between them with a single keypress — every session's provider, branch, and status visible at a glance.
Any AI Coding Agent
Built-in support for Claude Code, OpenAI Codex CLI, and Google Gemini CLI. Add any custom agent binary through YAML configuration.
Persona-Based Teams
Assign specialized personas — Developer, Architect, QA, Security, PM — to each session. Multiple personas work concurrently without conflict.
Git Worktree Isolation
Every session runs in its own git worktree on its own branch. No merge conflicts between concurrent agents. Automatic cleanup when sessions end.
Autonomous Execution
Connect to a VibeFlow server and agents become fully autonomous — polling tasks, implementing, committing, and reporting back while you supervise.
Single Go Binary
Zero external dependencies beyond tmux. Everything embedded — agent configs, provider definitions, full TUI. Works on macOS and Linux out of the box.