Describe a feature. Runstream ships it.

AI agents execute across multiple parallel streams — frontend, backend, integrations, tests — all at once. Dependencies are handled automatically. You step in only when your judgment actually matters.

5 AI agents executing in parallel
Stream Master:@you
Token validation service
Merged
2
Magic link API endpoint
Creating PR...
3
Login form component
Running tests...
4
Email delivery service
Implementing...
5
Dashboard redirect logic
Waiting on dependency [Task 2]...

How Execution Works

01

Takes the execution plan

The plan (from the Planning module or your own spec) includes tasks, dependencies, streams, and acceptance criteria. Runstream knows what to build, in what order, and what can happen simultaneously.

02

Spins up parallel agent streams

Independent work starts immediately across multiple streams. Each agent has full codebase context, understands its task's acceptance criteria, and knows which dependencies it's waiting on. Frontend doesn't wait for backend to finish.

03

Manages dependencies in real-time

When Stream 1 finishes a task that Stream 2 was waiting on, Stream 2 picks up immediately. No Slack message. No standup update. No ticket transition. It just happens. If a dependency reveals a conflict, execution pauses and escalates to you.

04

Escalates only when it matters

You're pulled in for decisions that genuinely affect outcomes: architecture choices, breaking API changes, conflicting implementations, actions that touch production. Everything else? Agents handle it.

05

Creates PRs with full context

Every PR Runstream creates includes: link back to the original task and execution plan, link to the feature definition and opportunity, clear description of what changed and why, test results and coverage, related PRs from other streams.

Safe by design. You always stay in control.

Nothing ships without approval

Every PR requires review. Every production action requires sign-off. Runstream doesn't push to main while you're sleeping — it queues for your approval and moves on to the next task while it waits.

Reject, change, or cancel — anytime

Don't like what an agent did? Reject the PR, ask for changes, or cancel the stream entirely. Execution runs in controlled environments. Worst case: you say "no" and try again. Zero risk.

Escalation with full context

When Runstream asks for your input, it shows you: what the agent is trying to do, why it needs your decision, the original customer evidence behind the feature, and what happens if you approve or reject. Informed decisions, not blind ones.

Not another coding assistant. The execution layer above them.

Cursor, Claude Code, and Copilot make individual developers faster. Each person runs their own fast loop.

Runstream doesn't replace any of that. It sits above — connecting the work into parallel streams that actually converge into shipped features.

You keep your tools. You keep your flow. Runstream makes that individual speed compound into team output.

Works with

CursorClaude CodeCopilotVS CodeGitHubGitLabCI/CD

Measure what matters.

Parallel Efficiency

How many streams are running simultaneously vs. sequentially? Higher parallelism = faster delivery.

Human Intervention Rate

What % of tasks required human input? 5-15% = healthy governance. 30%+ = you're just supervising bots.

Blocked Time

Total minutes work is stalled waiting for a human decision. Runstream keeps this near zero by continuing other streams while you review.

Error Rate

% of agent actions that needed correction. Runstream targets <5% — healthy autonomy without reckless automation.

Stop babysitting execution. Start shipping.