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Jeffrey Michael Johnson

Jeffrey Michael Johnson

AI Engineer & Agent Orchestration · Phoenix, Arizona

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Design-driven AI engineer building agent infrastructure, local and cloud. I ship products to the App Store, and the systems that orchestrate the agents behind them.

Jeffrey Michael Johnson

AI Engineer, Agent Infrastructure & LLM Systems

Phoenix, AZ
Claude Code
Claude Design
MCP Protocol
CrewAI
LangChain
n8n
Pinecone
Vercel
Next.js
Supabase
React Native
TypeScript
GitHub Actions
AWS
Framer Motion
Three.js
iOS
Android
Obsidian
Ghostty
OpenClaw
Hermes
Figma
Lovable
Claude Code
Claude Design
MCP Protocol
CrewAI
LangChain
n8n
Pinecone
Vercel
Next.js
Supabase
React Native
TypeScript
GitHub Actions
AWS
Framer Motion
Three.js
iOS
Android
Obsidian
Ghostty
OpenClaw
Hermes
Figma
Lovable
MCP Builder
4Public Repos
31Private Repos
20Skills published (25 authored)
6AWS Training

Selected work

Each of these fed the next.

The through-line is agent orchestration: making autonomous systems produce work you can actually verify, and publishing the failures alongside the wins. The complete index follows below.

01 · Currently building

antfarm

The agent factory inside anthill. A person types what they want done, a cloud model plans it, writes it, and the result lands in the repository. The safety argument is one property, and it is a test rather than a promise: a generated agent is merged but never scheduled, so a bad one is a revert away and the machine is never handed it. 3 agents written this way are in the repo, behind 143 tests across 8 suites.

  • Merged, never scheduled
  • The planner holds no authority
  • Model output is untrusted input
Read the case study(opens in a new tab)

Stack

02 · Currently building

GBuild

A macOS AI build environment driving a fleet of coding agents behind 5 first-party drivers, with on-device voice and a signed marketplace.

  • Rust core
  • Edge backend
  • Signed marketplace
View live(opens in a new tab)

Stack

03 · Currently building

G Training Center

The harness lab for GBuild's assistant. Edit the persona and the next run reads it, with no rebuild and no release. The soul A/B runs 3 arms, two of them identical, so an overlay has to beat the engine's own noise before it counts as having done anything.

  • Null-baseline A/B
  • Human grading only
  • Loopback only
Read the case study(opens in a new tab)

Stack

04 · Live on the App Store

PrayerMap

A real-time prayer platform spanning mobile, watch and web, with a glassmorphic design system carried straight over from the Figma prototypes.

  • Real-time
  • watchOS companion
  • Mapbox GL
View live(opens in a new tab)

Stack

05 · Currently building

Latch

DNS automation an agent can drive: detect where a domain is hosted, write the records where it can, and verify propagation server-side against several resolvers. 270 test cases in a 4-day build.

  • SPF merge, never a second record
  • Multi-resolver verify
  • Zero-dependency engine
View live(opens in a new tab)

Stack

06 · Currently building

anthill

A local code reviewer running on owned hardware, with a frontier model auditing its work. Built to find out whether free inference can hold a quality bar, and to publish the answer when it cannot.

  • Local 8B inference
  • Adversarial review
  • Measures its own precision
Read the case study(opens in a new tab)

Stack

// Building

Agent orchestration,
end to end.

Control planesGuardrailsEvaluationVoiceSupply chainOn-device

// Stack

What I reach for.

TypeScriptRustPythonSwiftReactNext.jsReact NativeElectronCloudflare WorkersDurable ObjectsSupabasePostgresClaude APIMCPMLXFigma

// Let's talk

Let's build something that matters.

Open to full-time, contract, and fractional or advisory work, especially where an AI system has to survive contact with real users.

Remote-first from Phoenix, travels for client-site work, open to hybrid or on-site for the right role. I reply within 24 hours on weekdays.

If you are building something where the guardrails have to hold, let's talk.

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