Practical Agent Patterns: Super Employees v. the AI Org Chart
See how engineers who've already shipped agentic systems are rethinking the architecture — from the people who built fleets, watched them fail, and rebuilt around a different model.
You've got agents running. The question now is whether one well-trained agent could outperform all of them.
This is for AI engineers who've moved past deployment and are working on the harder problems like:
what actually breaks when you give a single agent broad access and real autonomy
how to train, evaluate, and optimize an agent that understands how your whole company runs
what it takes to push reliable autonomous time horizon past the point where you'd trust it overnight
what non-technical team members actually adopt in mature organizations
SPEAKERS
Arnaud Ferreri, CTO at Headway
Healthcare AI infrastructureMike Taylor, Head of AI Technology Consulting at Every
Leading AI consulting engagements with technology teams
TOPICS
When Compliance Forces You to Build
Arnaud Ferreri on what it takes to deploy agentic systems inside a regulated environment. Why standard tooling failed their security requirements, what they had to build instead, and how that custom infrastructure enabled roughly a quarter of their non-technical staff to ship production code.
Against the AI Org Chart
Mike Taylor on why his team built a multi-agent system, watched their people ignore it in favor of a single unified agent, and rewrote their entire internal AI strategy as a result. He'll cover how to train and optimize a super-employee using structured evals and programmatic prompt refinement, and where this architecture is heading.
Fireside: Where Control Breaks Down
Arnaud and Mike on the real failure modes — maintaining control over an agent with broad access, what cost per successful task looks like in a unified model versus a fleet, and the architectural decisions that determine whether your agent runs reliably for 40 minutes or four hours.
WHAT YOU'LL GET
A framework for building custom connectors and tooling when off-the-shelf options fail your compliance requirements
A mental model for the super-employee architecture — how a single orchestration layer with unified context outperforms fragmented specialist agents for most real-world tasks
A working approach to training and optimizing agents using DSPy, structured evals, and programmatic prompt refinement
Two contrasting case studies: one inside a regulated healthcare environment, one inside an AI consulting practice — and what the failure modes look like from both sides
Happy Hour specials: enjoy cheap drinks and food all night at the newest hip spot on Union Square
🚨 This event is for engineers and technical leads already shipping agents in production who are ready to rethink how they're structured.
AGENDA
6:00 — Arrive & Mingle
6:30 — Arnaud Ferreri: When Compliance Forces You to Build
6:50 — Mike Taylor: Against the AI Org Chart
7:10 — Fireside chat + Q&A
7:30 — Meet the Speakers