Systems & Infrastructure
Theinfrastructurebehind
everythingwebuild.
An agent runtime, an SDK to build on it, and AI coding configs. We run our whole business on this stack, and technical teams can build on it without starting from scratch.
The Stack
Three layers.
All production.
Most teams get stuck at the same point: they've seen what AI can do in a demo, but they don't have the infrastructure to make it run reliably in their actual workflow.
We built that infrastructure for ourselves first. Every client engagement runs on the same three layers.
Layer 01
AI Coding Configs
Your team’s AI is only as good as its configuration.
Out of the box, tools like Claude Code, Cursor, Amp, Codex, and OpenCode are powerful but generalized. They don’t know your codebase, your conventions, or the things your team cares about. When they produce bad output, the issue is usually configuration, not capability.
We build custom AI coding configurations for development teams. These are systems that enforce your standards in real time, get more intelligent as you use them, and are customizable at both the admin level and the individual developer level. They generalize across any set of supported coding agents.
- Hooks that enforce your standards before code gets committed
- Skills that encode your team’s actual patterns and workflows
- LSP integration so the model understands your types, your APIs, your architecture
- CLI tooling that wraps common operations into repeatable commands
- Forbidden patterns so the model never produces code your team has agreed to avoid
Every developer on your team works with the same AI configuration. You improve it together. The model gets better as your team uses it, not worse.
Layer 02
The Agent Runtime
An agent is only useful if you can run it from the places where work happens.
Your CRM, your inbox, your contracts, your Slack channels, and your schedules are all entry points where an agent can pick up a task. Each one needs the right prompt, the right skills, authentication, guardrails, and somewhere reliable to run.
We built a runtime that handles all of it. Agents run in isolated sandboxes, you can spawn one or a hundred, and your team reaches them through whichever interface fits the job.
- Sandboxed execution — every agent runs isolated, with exactly the permissions its config grants and nothing more
- Parallel by default — spawning a hundred agents is the same operation as spawning one
- Tenant isolation — your agents, your memory, your sessions. We can’t see in unless you let us
- Any interface — web app, MCP server, Chrome extension, or triggers from Slack, email, Linear, GitHub, and cron
- Configs are code — versioned, reviewed, and deployed from repositories you own
This is the layer everything else sits on. Tell us what you need, and a new agent is usually live the next day.
Layer 03
Always-On Cloud Agents
Agents that run without anyone asking them to.
Long-lived agent processes run on the runtime, with orchestration harnesses for parallel execution and pipelines for multi-step workflows. The code, the data, and the memory are yours.
What this looks like in practice:
- Bug triage — a Linear issue gets created, an agent reproduces it, opens a PR with a fix, and tags the right reviewer
- Code review — push to a branch, agents run security scans, pattern checks, and architectural review before a human looks at it
- Knowledge work — agents process incoming emails, update CRMs, generate reports, and flag anything that needs a human decision
Every one of these can be fixed, extended, or shut down from a Slack message or a Linear comment. You’re never waiting on us.
Start here.
We maintain a few open repos and config sets that show how these systems work. They're not marketing material. They're the actual starting points we use.
Open Source
Create Hooks
A Claude Code plugin for building, debugging, and managing hooks. Scaffolds hook files, validates config, and analyzes existing hooks for conflicts.
Learn moreOpen Source
Dodo VPS
One command to provision, secure, and launch an AI dev VPS. Swap, log limits, Tailscale, and systemd services — everything a cloud agent needs to run.
Learn moreOpen Source
Claw Monitor
Observability and self-healing for OpenClaw agents. Health checks, incident tracking, notifications, and CLI tools for debugging long-running deployments.
Learn moreThese aren't demos. They're production configs with the API keys removed.
For teams that already write code.
If you have developers, you don't need another AI platform. You need someone who's already built the infrastructure and can set it up for your team in weeks, not quarters.
01
Managed Agents
We run the infrastructure, you get the agents. Tell us the task, and we build the agent, wire it into your entry points, and keep it monitored in production. When you need a new capability, you ask, and it goes live in days rather than quarters.
A retainer, not a platform fee. Leave whenever you want and keep your code.
02
The SDK
If your team wants to build its own agents, the runtime is available as an SDK. You get the sandboxing, the tenancy, the memory layer, and the interfaces without building any of it from scratch. Your engineers write the agents, and the runtime handles everything underneath.
The same infrastructure we run our business on, as a foundation for yours.
03
Custom AI Coding Config
We audit how your team works. We read your codebase. We build a config that includes hooks, skills, forbidden patterns, and CLI tools specific to your stack and conventions. Every developer gets the same setup. You iterate on it together.
Most teams see the difference in the first week.
Questions
Common questions from technical teams.
Your team writes the code. We'll build the systems around it.
Tell us about your stack, your team, and where you want AI to actually do something useful. We'll tell you what's realistic and what it would take.
No sales process. First call is with the founder.