AI-native, not AI-wrapped
We don't bolt LLMs onto legacy code. Every system is designed agentic-first — reasoning, planning, and acting as a first-class architectural concern.
We build agentic workflows, LLM-powered products, and cloud-scale AI platforms — and advise the teams building their own. Everything we ship is AI-native from day one, whether we're delivering it or sitting next to your engineers.
Multi-agent systems · RAG pipelines · LLM orchestration · AI-native apps · Agentic workflows
Impressive demos, hallucinating agents, cloud bills that surprise the CFO. The gap between a GPT wrapper and a production-grade AI-native system is where most teams stall — and where we begin.
We don't bolt LLMs onto legacy code. Every system is designed agentic-first — reasoning, planning, and acting as a first-class architectural concern.
Prompt versioning, token budgets, eval suites, hallucination guards, and cost dashboards baked in — not bolted on after the first incident.
Every agentic system we deliver runs under real traffic with rollback, runbooks, and evals. Clean code, written docs — no lock-in to us.
Week engagements
From first prompt to production-grade agentic system. Not quarters — weeks.
Systems shipped
LLM-powered products, agentic pipelines, AI-native platforms — shipped.
Junior handoffs
Senior engineers ship the work. You always talk to the people building it.
Our team are AI-native developers — fluent in agentic workflows, model orchestration, and the full toolchain.
That's why we ship in weeks, not quarters.
Five scenes, real round-trips. From the moment a user sends a message until the citations land in their chat: rate limit, query expansion, hybrid retrieval, generation, attribution, claim grounding, atomic persist. The participants on stage change with each phase — this is what production agentic AI actually looks like.
Big agencies move slow. Freelancers vanish. In-house hires take a quarter to ramp. Here's what changes when a small senior team owns the problem end-to-end.
Code Origin
Competition
Multi-agent expertise
Time to first prod ship
Cloud architecture
Senior engineers only
Clean handover
Ongoing partnership
Convinced we're the right fit?
Book a 30-min introAgentic systems need more than a good model. They need a solid app underneath, the cloud to run it reliably, and senior engineering judgement throughout — we deliver all four, end-to-end or alongside your team.
Multi-agent workflows, LLM orchestration, and RAG pipelines — designed to reason, plan, use tools, and act autonomously at scale.
LLM-powered apps, APIs, and data pipelines built AI-first — not retrofitted. Production-grade from day one, owned by your team.
Scalable cloud platforms tuned for AI workloads — GPU pipelines, vector stores, inference APIs — observed and cost-controlled end-to-end.
Senior engineering judgement for teams building their own — software architecture, AI strategy, and code-level reviews. We sit next to your engineers when you don't need us to deliver.
Hands-on workshops and structured curricula that bring your engineers up to speed on AI coding tools — Claude Code, Cursor, GitHub Copilot, Codex, Gemini — and the production patterns around them.
Want this for your team?
Talk to an engineerWe package what we learn for clients into shipping products — from a flagship training platform to open-source developer tools.
Claude Code specialization courses
Hands-on, structured curricula for individuals and teams who want to ship faster with Claude Code. Built and maintained by the founder of Code Origin — always current with Anthropic's latest releases.
Open-source Claude Code plugin · Full-lifecycle workflow
A unified Claude Code plugin that orchestrates the entire software lifecycle — from planning and design through implementation, testing, security audits and deployment. Built and battle-tested on our own client work.
Every project is staffed by named people you can talk to from day one. No bench shuffle, no junior offshore swap mid-sprint.
Founder · Principal Engineer
Creator of masterclaude.dev. Builds AI-native systems for production and trains engineering teams to ship with Claude Code.
Most engagements land between $30k and $250k depending on scope. Discovery is typically $8–15k for a one-week diagnostic with a written architecture and budget. We share a fixed fee before any build starts — no T&M surprises.
Agentic reasoning is a first-class architectural concern, not an LLM bolted onto a CRUD app. Prompt versioning, eval suites, traces, cost guardrails and hallucination grounding live alongside your application code from day one.
You do. Code, prompts, evals, infra-as-code, runbooks, and recorded walkthroughs are delivered to your repos under a standard work-for-hire clause. No lock-in to us, no third-party platform you cannot leave.
Anthropic Claude, OpenAI, and open-weights (Llama, Qwen, Mistral) on AWS, GCP, or Vercel. Vector stores: pgvector, Pinecone, Qdrant. Application stack: Next.js / TypeScript / Python. We pick what fits your team, not what we already know.
Yes to both. We sign standard mutual NDAs before discovery and DPAs before contract. EU data residency on AWS Frankfurt / GCP eu-west is supported on every engagement; SOC 2 Type II workflows on request.
Optional retainer ($8–20k/month) covers LLMOps, model upgrades, eval maintenance, cost tuning, and on-call for the first 90 days post-launch. Or you take it over completely — your team has the runbooks and we are one Slack message away.
We will not pitch you. We will ask sharp questions, sanity-check your architecture, and tell you whether we are a fit. If we are not, we will point you to who is.
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Tell us a little about what you're building. We reply within one business day — typically with a few sharp questions and a proposed next step.
A senior engineer's launch gate for RAG features — chunking, hybrid retrieval, grounding, evals, observability, cost control, and the boring compliance bits everyone skips.