Production AI Projects
Real systems running in production — not demos, not proofs-of-concept.
J5 Mail
2026–PresentAn attention firewall for email
Private-beta email product combining typed Jev judgments with deterministic policy, explained routes, scoped feedback learning, and explicitly gated mailbox side effects. Next.js web app and native SwiftUI client, running on my own mailbox.
Read Case StudyAgent Infra Index
2026–PresentEvidence-first infrastructure research
Independent comparison site and Agent Infra Weekly newsletter. Repeatable sandbox/browser workloads, raw samples and visible failures, source-linked pricing/access claims, freshness review, and explicit usage and publication gates. A live research product, not an opaque ranked leaderboard.
Read Case StudyJ5 Social
2026–PresentSocial platform for humans and AI agents
Invite-only production platform where people and their AI agents have distinct profiles, visible ownership, revision-pinned publishing gates, comments, reactions, private media, friend-scoped messaging, durable callbacks, REST and MCP access, and a native iOS app in TestFlight.
J5 Agent Fleet
2026–PresentAgent fleet & operations platform
Production platform managing 95 specialized AI agents across 15 divisions: Goal Mode task loops, project decomposition, Kanban and Gantt timelines, Slack agent sessions, multi-agent Meetings, approval gates, local browser/computer automation, durable execution events and signals, token/cost governance, native iOS/macOS/Apple TV/Electron surfaces, and local or managed-cloud execution through Claude Code, Copilot CLI, Codex, Antigravity, Kiro, LM Studio, and API models.
J5 A2A
2026–PresentAgent-to-agent coordination protocol
Coordination layer for agentic development tools at j5a2a.com. Gives coding assistants, IDE agents, MCP clients, CLIs, scripts, local-model bridges, and humans a shared session for typed events, presence, lease-aware claims, conflict detection, questions, requests, decisions, inbox wake patterns, artifacts, digests, semantic advisories, and operator visibility.
J5-Trade
2026–PresentAutonomous Multi-Agent Crypto Trading Platform
Production-grade autonomous cryptocurrency trading system featuring AI-generated trade summaries, an integrated chat assistant, and a 4-agent analysis system: a Pricing Agent, News Sentiment Agent, Trade Agent, and a Coordinator Agent that manages the other three. Includes real-time monitoring dashboard and signal resolver with veto hierarchy.
J5 AI Test
2026–PresentPlain-English end-to-end testing, driven by an AI agent
Write end-to-end browser tests in plain English — an AI agent drives a real browser (Playwright) to execute them, so anyone can author tests without selectors or framework knowledge. Tests are markdown + YAML frontmatter (version-controllable and diff-able); failures produce structured, screenshot-rich briefs you can paste straight into Claude or Cursor to fix. Works across CLI agents (Claude Code, Cursor, Codex, Gemini) and direct API providers (Anthropic, OpenAI, Google).
Johnny5
2026–Present24/7 AI Assistant powered by OpenClaw
Personal AI assistant (Johnny5) powered by the open-source OpenClaw platform. Multi-channel communication across Telegram, Discord, and email. Mission Control dashboard for monitoring subagents, cron jobs, and vector memory. Integrated with cloud model providers and local LLMs, with workflows that helped build J5-Trade.
AI Image Validator
2025AutoGen + GPT-4o Vision Pipeline
Multi-agent image validation using AutoGen framework and GPT-4o-mini vision model with natural language criteria, structured outputs, and full OpenTelemetry tracing.
Trading Floor Simulation
2025MCP-Powered Multi-Agent Trading
Capstone project: Gradio-powered trading floor with multiple AI trader agents backed by different LLMs, MCP market data server, and real-time P&L dashboard.
Executive Summary
Since ChatGPT launched, I have maintained a sustained hands-on practice across model evaluation, agent architecture, orchestration, and production delivery. That work has produced operating AI platforms, autonomous workflows, and practical experience across the major agent frameworks. Combined with 15+ years of enterprise engineering leadership, I approach AI as both a technical and organizational system: capability, governance, observability, cost, adoption, and measurable value.
AI Learning Journey
A sustained progression from early experimentation to shipping and operating production AI systems.
Immediate Adoption
Day-one experimentation with ChatGPT and GPT-3.5
- Started using ChatGPT within days of launch — recognized the paradigm shift immediately
- Explored prompt engineering patterns, chain-of-thought reasoning, and system prompts
- Began integrating LLM-powered workflows into daily engineering leadership work
- Started dedicated 10–15 hr/week AI self-study habit that continues today
Deep Exploration
API integration, multi-model evaluation, and applied AI
- Built first production integrations with OpenAI API and Claude API
- Evaluated and compared GPT-4, Claude, Gemini, and open-source models
- Studied RAG architectures, vector databases (Qdrant), and embedding strategies
- Adopted AI-powered development tools: Cursor IDE, GitHub Copilot
Building Production AI
Shipping autonomous agents and real-time trading systems
- Built Johnny5 (personal AI assistant) powered by the open-source OpenClaw platform: daily newsletters, Mission Control for monitoring subagents and cron jobs, and vector memory
- Shipped J5 Agent Fleet — production Next.js agent fleet and operations platform: 95 agents across 15 divisions, Goal Mode, Slack, Meetings, durable telemetry, token governance, native apps, and local or managed-cloud runner execution
- Built J5 A2A — an agent-to-agent coordination layer for Codex, Claude Code, Cursor, MCP clients, CLIs, scripts, local-model bridges, and humans working in shared sessions
- Launched J5 Social — an invite-only platform where humans and their AI agents share profiles, feeds, private media, messaging, and owner-controlled publishing through REST and MCP
- Built J5 Mail — a private-beta email attention firewall with typed model judgments, deterministic routing, feedback learning, and native iOS
- Launched Agent Infra Index — an evidence-first infrastructure directory with repeatable benchmarks, source-linked claims, and Agent Infra Weekly
- Configured Johnny5 with cloud model providers and local LLMs, integrating across Telegram, Discord, and email
- Explored vector databases, semantic search, and long-term agent memory systems
Framework Research
Systematic deep-dive into the most popular agent frameworks
- Completed intensive 6-week Agentic AI Engineering course across all major frameworks
- Built 20+ projects spanning OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, and MCP
- Mastered multi-agent orchestration patterns: handoffs, group chat, adversarial, and pipeline
- Implemented production MCP servers with FastMCP for standardized AI-tool integration
AI-Native Development
Full-stack AI-assisted engineering with Claude Code, Codex, and agentic IDEs
- Adopted Claude Code, Codex CLI, GitHub Copilot CLI, Antigravity, and agentic IDE workflows for end-to-end AI-assisted software development
- Built AI Image Validator using AutoGen + GPT-4o vision with OpenTelemetry tracing
- Created AI Assistant Human Questionnaire — privacy-first AI context builder
- Built J5-Trade: autonomous multi-agent crypto trading platform with 4-agent analysis system (Pricing, News Sentiment, Trade, and Coordinator agents)
- Actively shipping production code with agentic development workflows daily
Agent Framework Experience
Hands-on, project-based experience with most of the popular agentic AI frameworks — not tutorials, real working systems.
OpenAI Agents SDK
Multi-agent handoff pipelines, deep research agents, tool calling with side effects, multi-model routing across GPT-4o, DeepSeek, and Ollama.
Projects Built
CrewAI
Role-based agent teams simulating real-world workflows — engineering, finance, debate, and code review — with knowledge base integration.
Projects Built
LangGraph
Stateful autonomous agents with Playwright browser automation, memory checkpointing, evaluator loops, and human-in-the-loop escalation.
Projects Built
AutoGen
Distributed actor-model agent networks with 20+ autonomous agents, group chat pipelines, and asynchronous message routing.
Projects Built
Model Context Protocol
Built production MCP servers and A2A coordination adapters for market data, account management, memory persistence, push notifications, and shared agent sessions.
Projects Built
Claude & Anthropic
Primary LLM provider for OpenClaw automations and daily AI development. Daily use of Claude Code for agentic software development and code generation.
Projects Built
AI Toolkit
LLM Providers
Agent Frameworks
AI Development Tools
AI Infrastructure
Languages & Runtimes
Deployment & Ops
Why This Matters for Enterprise
Framework-Agnostic
Deep hands-on experience across most popular agent frameworks means I can evaluate, select, and implement the right tool for any enterprise AI initiative — not locked into a single vendor.
Ships Production AI
Not just prototypes — I build and operate production AI systems running 24/7. From autonomous trading to persistent AI assistants with real users and real stakes.
Full-Stack + AI
15+ years of enterprise software engineering combined with deep AI expertise. I bridge the gap between AI research and production-grade software delivery teams.
AI-Native Leadership
Currently leading engineering teams at a major bank while simultaneously building AI projects. I understand both the technical execution and organizational change management required.
AI Education
2025 · Udemy / Ed Donner
CompletedThe Complete Agentic AI Engineering Course
Comprehensive 6-week course covering the most popular agentic AI frameworks: OpenAI Agents SDK, CrewAI, LangGraph, AutoGen, and MCP. Built 20+ hands-on projects from multi-agent research pipelines to distributed trading floor simulations.
2026 · Udemy / Ed Donner
In ProgressAI Builder: Create Agents, Voice Agents & Automations in n8n
3-week intensive on building production AI agents with n8n. Covers autonomous business agents with OpenAI and open-source models, real-time Voice Agents with ElevenLabs and Twilio, Agentic RAG with Supabase, and a capstone multi-agent Go-To-Market system using MCP with self-hosted n8n and Ollama.
2026 · Udemy / Ed Donner
In ProgressAI Engineer Production Track: Deploy LLMs & Agents at Scale
4-week production deployment course shipping enterprise-grade AI across Vercel, AWS, GCP, and Azure. Covers SaaS apps with Next.js and Clerk, AI platform engineering with Bedrock, Lambda, Terraform, and CI/CD, multi-agent systems with Aurora Serverless, SQS, and LangFuse observability, plus MCP-powered Researcher and Cybersecurity Analyst agents.
The Bottom Line
AI is a sustained engineering discipline in my work, not a side interest. Since ChatGPT launched, I've been building, testing, and shipping AI systems. I understand the technology at every layer: from prompt engineering and model selection to multi-agent orchestration and production deployment. Combined with 15+ years of engineering leadership at major financial institutions, I'm ready to drive real AI impact from day one.