Early access now open for product and platform teams

Turn every engineer into the lead of an AI delivery fleet.

FleetLead.dev deploys task-focused engineering agents that understand your stack, run your tools, and ship code through your real workflow. Less prompt theater, more merged work.

Book a DemoWatch a live run

Assign work from Slack, Teams, email, or CLI in plain language.

team@fleetlead-cli:~
>fleetlead run "stabilize flaky auth tests in user-service"
[Context] Loading schemas and historical incidents via MCP connectors...
[Env] Provisioning isolated MicroVM with service-level credentials...
[Git] Cloned repo and checked out fix/auth-test-flake branch
[Run] Patch applied. Hooks passed. 142 tests green.
PR #1042 opened: "Fix race condition in JWT validation"

More output per developer

Each engineer manages parallel execution instead of working one request at a time.

Faster path to pull request

Ideas move from message to tested branch in minutes, with less context switching.

Less tribal knowledge

Your conventions, architecture, and team patterns become part of every run.

Safer automation

Agents pass through hooks, tests, and review gates before code reaches production.

Stop pasting generic model output. Start orchestrating a fleet.

A chatbot can help you think. FleetLead.dev helps your team deliver: real context, real execution, and real pull requests under enterprise controls.

Generic AI Chatbots

  • Context

    You paste fragments and hope the context window holds.

  • Execution

    Output is plain text you still have to copy, test, and wire in.

  • Safety

    No guaranteed respect for repo policy, checks, or branch rules.

FleetLead Agents

  • Progressive Retrieval

    Fetches exact code paths, schemas, and logs using MCP tools.

  • Isolated Execution

    Clones repos, runs tests, and opens clean pull requests.

  • Hardened Gates

    Enforces hooks, linting, CI, and branch protections by default.

Progressive Context

Right context. Right moment. Right scope.

FleetLead.dev does not dump your whole codebase into one giant prompt. Agents earn context progressively through structured access.

  • 1
    Start with task boundaries and target service.
  • 2
    Retrieve internal docs, patterns, and historical pull requests.
  • 3
    Expand only where needed into dependencies, traces, and logs.

Better decisions, fewer hallucinations, lower token waste.

auth_service.ts
Loaded
schema.prisma
Fetched via MCP
incident_logs.json
Fetched via MCP

Environment Sandboxed

MicroVM provisioned with scoped secrets.

Execution and Linting

Agent writes code and resolves strict typing issues.

Tests Passing

Unit and integration suites pass before handoff.

Human Review

Pull request opens with full context for final approval.

Hardened Execution

Autonomy without control is only a demo.

Agents run in isolated environments that mirror how your engineers work today, with governance built in.

FleetLead.dev hardens every run with the checks that make automation trustworthy:

Pre-commit hooks
Typed interfaces
CI and policy checks
Branch protections

RequestContext LoadsIsolated ExecutionTests RunClean PR

That is the product.

Meet your team where they already work.

Start a FleetLead run from the tools your team already uses. Same execution engine, multiple entry points.

Slack

Engineering requests

Teams

Cross-functional delivery

CLI

Deep local execution

WhatsApp

Business workflows

For scaling startups

Increase engineering throughput without increasing headcount at the same pace.

For larger engineering orgs

Standardize delivery patterns and reduce dependency on individual team memory.

For platform teams

Encode internal tooling and governance so quality scales with every release.

Build your company's AI delivery workforce.

Your best engineers should spend time on architecture and product direction, not repetitive implementation. FleetLead.dev handles the repetitive work safely and consistently.

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