Fast on one laptop, slow across the team
Agents speed up individual engineers while review queues grow and context gets lost at every handoff. The harness fixes the handoffs.
For engineering leaders
Make your team's coding agents ship work you can merge and maintain.
Your engineers already use coding agents. We work inside your engineering workflow to ship features, strengthen verification and improve how the team uses coding agents: repository context, permissions, verification gates and review flow.
What we solve
Where coding-agent speed gets lost.
Changes nobody can explain later
Every agent change arrives with its task, its evidence and the decision behind it, so the next engineer can maintain it.
A workflow that keeps up with the models
Models and tools change monthly. A retainer keeps your harness, permissions and gates current as they do.
Proof
Work we have already done.
We built the agent platform behind a product used by a unicorn startup and Fortune 500 companies. We bring that engineering practice to your team's harness. Our method is public, with a worked example you can run yourself.
AI-Native SaaS / selected work
Agent Platform Engineering for Enterprise AI
- The problem
- Give AI agents a way to find, create and update a content platform's structured information.
- What we built
- Backend AI with Anthropic, OpenAI and Google models, 50+ MCP tools, content APIs and semantic search.
- What it made possible
- Agents that find information, act on it and power interactive experiences inside compatible AI clients, for a unicorn startup and Fortune 500 companies.
- 50+
- MCP tools built
Backend AI, API and infrastructure engineering, from architecture through launch.
Read case studyAgent platform engineering
- Backend AIAnthropic, OpenAI and Google
- 50+ MCP tools builtDiscover, create and update content
- APIs and searchStructured content and semantic retrieval
- Platform infrastructureSupports agents and MCP Apps
How we engage
A forward-deployed team, on terms you can plan around.
Start with a harness review, ship real features through your harness with a forward-deployed team, then keep it current on a monthly retainer.
Architecture & Harness Review
Two to three weeks
An independent read of your AI system or your team's agentic engineering workflow, ending in a prioritized plan.
You get: System or workflow map, risk register, evaluation and release plan, harness gap list, and a decision brief with the next scope.
Explore this optionForward-deployed build
Initial three-month engagement
A forward-deployed team embeds with yours and builds the agent platform, AI product or the systems behind it. Scope, milestones and acceptance criteria are agreed before work starts.
You get: Working software, the harness your engineers keep using with coding agents, evaluation and release gates, runbooks, and a handoff your team runs with.
Explore this optionForward-deployed operations
Monthly retainer
After launch, we stay on to run the evaluations, keep the harness current as models change, respond to incidents and ship improvements.
You get: Evaluation and cost reporting, harness upkeep, incident response, ongoing improvements and a leadership readout.
How the retainer worksGo deeper
Read how we approach it.
Start a conversation
What are you building—or deciding?
Tell us where you are. We reply within one business day, and the first conversation ends with a recommended next step.