The layer above AI coding agents
Claude Code runs one task.
Maxwell runs your entire team.
You already know how to use AI coding agents. Maxwell takes that same setup and distributes it — running dozens of tasks in parallel on your machines, tracking every one in real time, managing context automatically. You keep building. Maxwell keeps shipping.
Built in production, not in a lab
We used Maxwell to outship companies 20x our size.
3.3x
Engineering output
100
Items shipped in 3 weeks
3
Engineers, doing the work of 10
The Problem
AI coding agents are everywhere. An orchestration layer doesn't exist.
Tickets are written for humans
Your backlog lives in Jira or Linear — too vague for machines, too disconnected from your codebase.
Agents run in ad-hoc terminals
No guardrails. No audit trail. No way to know what an agent did, why, or what it cost.
Approvals happen in Slack threads
Human governance is an afterthought. Someone reviews a diff in chat and prays nothing slipped through.
No system connects the pieces
No single platform routes work to agents, sequences execution, monitors output, and enforces human review.
Why it's different
Claude Code is a brilliant individual contributor.
Maxwell coordinates dozens of them simultaneously.
Same agents you already use. Same models. Same tools. Maxwell adds the layer that distributes work, tracks progress, and manages context — so you never babysit a terminal again.
10X your dev output
Stop waiting on terminals. Distributed AI orchestration means you kick off a task and keep moving — Maxwell handles the rest.
Your agents, your environments — your way
Maxwell calls AI agents the exact same way you do. It just distributes the work and orchestrates it across your existing setup.
Deterministic, not hopeful
No more crossing your fingers. Define exactly where tasks go, what happens at each stage, and what triggers human review.
100 tasks in parallel, all in real time
Launch an entire sprint worth of work at once and watch every task progress live — not buried in a terminal you have to check.
A water-wheel of quality
Pair with self-validating agents and preview environments for a constant, self-sustaining flow of high-quality engineering work.
Context management built in
You don't need to become a context management expert. Maxwell handles it as a core part of the system — automatically, every time.
Complete Observability
Every work item. Fully tracked.
From spec to deployment — every decision, artifact, and review captured in a single place.
Agents & Teams
Build your team once, run it on every work item
Agents are reusable workers you define once at the org level. Assemble them into a Team for each project — a named group that handles every work item end-to-end, with a human reviewer in the loop.
Product Manager
Writes the spec and acceptance criteria
Architect
Designs the technical approach
Human Reviewer
You approve before code is written
Developer
Implements the feature and opens a PR
Code Reviewer
Checks standards, security, and clarity
UI/UX Reviewer
Validates visual consistency
QA Engineer
Writes and runs tests against the spec
Deploy Agent
Deploys to preview and runs smoke tests
Mix AI agents and human reviewers. Use a template or build your team from scratch.
Full Agent Control
Your prompts. Your agent team. Your rules.
We send your runner the task state and context. Everything else — the prompts, the models, the tools, the execution environment — is entirely yours.
Maxwell Cloud
Work Queue
Orchestrator
State Store
task state + context
↓
status updates
↑
Your Runner — Your Machine
Any model (Claude, GPT, Gemini…)
Your system prompts
Custom tooling
Your environment vars
connects to anything on your network
⚙
MCP Servers
🔗
Internal APIs
📁
Local Repos
🗄
Private DBs
Own your prompts
Write the system prompts that define how every agent thinks. Tune, version, and iterate them without touching Maxwell's infrastructure.
Connect to anything on your network
Your runner runs where your tools live. Hook up MCP servers, internal APIs, private repos, local databases — anything accessible from your environment, with zero exposure to us.
Any model, any runtime
Claude Code, GPT, Gemini, a local Llama — your runner, your choice. Swap models per agent, per task, per environment. No lock-in, ever.
We only see what you send us
Maxwell receives task context and status updates — nothing more. Your source code, secrets, and tool configs never touch our servers.
How Maxwell Is Different
Maxwell isn't the AI. It's the factory floor where the AI works.
Cursor, Lovable, and Windsurf are incredible coding agents — but they're the workers, not the assembly line. Maxwell routes work to those agents, sequences their execution, manages their context, and brings humans in when it matters.
Capability
Cursor / Lovable / Windsurf
DIY Scripts
Maxwell
Multi-agent orchestration
Single agent, single task
Fragile hand-wired chains
Autonomous agent pipelines with handoffs
Crash recovery
Start over from scratch
Start over from scratch
Resumes from last checkpoint automatically
Context management
One massive context window
Manual, error-prone
Fresh context per agent stage — no "AI dementia"
Human approval gates
None — you review after the fact
None
Configurable pause points before any stage
Visibility & audit trail
Terminal output
Logs if you built them
Full DVR — reasoning, cost, duration, every decision
Model lock-in
Locked to one model
Locked to whatever you scripted
Swap any model, any tool, any time
Project management
Separate tool (Jira, Linear)
Separate tool
Built-in — AI-native work items, boards, cycles
Connects to everything you already use
Native SCM integration with GitHub, GitLab, and Bitbucket. Bring any AI model — Claude, GPT, Gemini, or your own.
GitHub
GitLab
Bitbucket
Claude
GPT
Gemini
The future of software is built by teams of humans and agents, together.
Stop copy-pasting between Jira, Slack, and terminals. Give your work a system that understands it, routes it, executes it, and brings you in only when it matters.
MXWL
AI agent orchestration for software teams
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