I run a 24/7 AI orchestration system managing 15+ real projects — live SaaS products, tax APIs covering 4,246 jurisdictions, multi-agent pipelines. I come in, assess how your team uses AI, set up a proper orchestration system with the right knowledge structure and agent roles, then teach your team how to run it.
The Problem
Most teams jump straight to prompting. The 10% that set up real structure see 10x the output.
Devs using Claude or ChatGPT for isolated tasks — no shared context, no memory, no methodology. Every conversation starts from zero.
AI outputs look good in a proof-of-concept but fail when real data, edge cases, and scale enter the picture. No validation gates, no fallback logic.
Every agent starts from scratch. Decisions made on Monday are forgotten by Friday. No planning gates, no verification, no shared memory structure.
The Difference
Most people teaching AI orchestration have read the papers. I've been running it in production.
A 24/7 AI orchestration system that manages 15+ real projects — with persistent memory, multi-agent coordination, planning gates, and automated verification. It's not a demo. It runs every day.
HostReply (live SaaS for vacation rental AI messaging), a Payroll Tax API covering 4,246 jurisdictions, a skill marketplace for Claude Code agents. These are running in production, not slides.
Hooks, agents, skills, MCP servers — I understand how Claude Code works at the architecture level, not just how to prompt it. I've built extensions for it and written about the internals.
I designed and hardened the architecture: context management, knowledge distillation, planning gates, worker methodology, verification-before-completion, escalation protocols. It works because I stress-tested it.
How It Works
Not a training course. Not a playbook PDF. I come in, set it up, and teach your team how to run it themselves.
I assess how your team currently uses AI — where knowledge lives, what's breaking, how much AI is in your workflows. Usually a 60–90 min deep dive.
Install the orchestration system. Connect your existing tools (Notion, Linear, Slack, GitHub). Set up knowledge structure, agent roles, and validation gates tailored to your workflows.
Hands-on sessions with your team: context management, planning gates, worker methodology, verification-before-completion. They learn by running it, not by watching slides.
Your team is running it independently. I'm available for support and iteration. Optional monthly retainer if you want ongoing access as you scale.
"I come in, assess how your team is using AI, set up a proper orchestration system with the right knowledge structure, agent roles, and validation — then teach your team how to run it."
— The engagement in one sentence
Pricing
Simple model. Setup fee gets your system installed and your team trained. Optional retainer if you want ongoing support as you scale.
Discovery → Setup → Teach → Hand off. Four weeks, your team runs it independently by the end. Scoped to your team size and existing tooling.
Ongoing access as your team scales. Useful for teams moving fast — new use cases, new integrations, architecture questions, code reviews.
Not sure what you need? Start here:
The goal is always independence, not dependency on me.
Proof
Not concepts. Not prototypes that never shipped. These are deployed, production systems — most of them solo, most in under 3 weeks.
AI Guest Messaging for Vacation Rentals
Property managers spend hours every day answering the same guest questions — check-in instructions, WiFi passwords, parking, local recommendations. Multiply that across 50, 100, or 500 properties and it's a full-time job. I built an AI messaging assistant that integrates with property management software to auto-respond with context-aware replies. It knows which property, the reservation dates, house rules, and local info. Your team gets hours back every day.
24/7 AI Orchestration — 15+ Projects Running
This is the system I'd help you set up. Persistent AI agents with long-term memory, task management, multi-agent coordination, planning gates, verification-before-completion protocols, and automated escalation. It manages a portfolio of 15+ real projects — everything from SaaS products to APIs to marketing pipelines — autonomously. Not a demo, not a side project. It runs every day.
4,246 Jurisdictions. AI-Generated. Production-Grade.
A complete payroll tax calculation API covering every US jurisdiction — 4,246 of them. Built with AI-assisted research, validation pipelines, and structured output generation. The kind of project that would take a team months. Shipped solo with orchestrated AI workflows doing the heavy lifting.
AI-Powered Interior Design Platform
Upload a photo of your room, describe what you want changed, get AI-generated design variations. Full production app — Google OAuth, credits/billing system, and a companion React Native mobile app. From idea to live product in under two weeks.
Every project above: real AI integration, production architecture, shipped solo. This is what orchestrated AI looks like when it's set up right.
About
Most AI consultants learned from papers and courses. I built a 24/7 AI orchestration system — superbot2 — that autonomously manages 15+ real projects. It runs every day. It ships real code. It handles its own task queue, escalates blockers, and distills knowledge across sessions.
That's the system I'd help you set up for your team.
I've shipped real products with this approach: HostReply (live SaaS for vacation rental AI messaging), a Payroll Tax API covering 4,246 jurisdictions, and a skill marketplace for Claude Code agents. Not prototypes — production systems, built solo, in days to weeks.
I understand Claude Code at the internals level — hooks, agents, skills, MCP servers. I've written about the architecture and built plugins for it. When I set up an orchestration system for your team, it's grounded in how the tools actually work, not how the marketing says they work.
Based in Haleiwa on O'ahu's North Shore. Available for in-person meetings on O'ahu, remote-friendly everywhere else.
FAQ
It's the layer between your team and raw AI tools. It handles knowledge management (what context agents have access to), task planning (planning gates before work starts), worker methodology (how agents are structured and what roles they play), and verification (checking outputs before claiming completion). Without this layer, every AI interaction starts from zero and has no quality control. With it, you have a team of AI workers that build on each other's work and catch their own mistakes.
Yes — and this is actually the most common starting point. Teams using Claude Code for individual tasks are getting maybe 20% of what's possible. The orchestration layer is what multiplies the output. I'll assess how you're using it now, then set up the structure that makes it significantly more powerful.
It happens. We handle scope changes through a simple change order — I'll estimate the additional work and we agree before proceeding. No surprises.
Yes — a free 30-minute call to understand how your team uses AI today and whether this is the right fit. No pressure, no pitch deck. I'll tell you honestly if you'd be better served by a different approach.
No — the whole point of the engagement is independence. By the end, your team understands the system, knows how to run it, and can extend it themselves. The optional retainer is for teams that want ongoing help as they scale, not because they need me to operate what they have.
For Hawaii clients, I'm available for in-person meetings on O'ahu. For remote teams, HST overlaps with West Coast mornings and Asia-Pacific afternoons. Most communication is async anyway — Slack, Loom, code reviews. I've worked with teams across every US timezone and internationally without issues.
Let's Talk
Start with a free 30-minute discovery call. I'll ask how your team uses AI today, where it's breaking, and whether this engagement makes sense for you. On O'ahu? Let's meet in person.