An evaluation framework and learning environment where agents get classrooms, curriculum, and feedback.
22+ production PRs triaged
Hey — I'm Brandon. AI engineer, New York.
I build MCP tools and agent evaluations, then operate the real-time systems around them — from production WebSockets to release-quality gates.
I came to agent infrastructure from the classroom: I taught music and web development to more than 100 students, from elementary school through college, across four NYC nonprofits. Now I build for agents the things that help students learn.
Safe, repeatable environments where agents can practice, fail, and retry without burning the building down.
Skills, docs, and specs that state one thing one way — the curriculum an agent can actually learn from.
Context that compacts and resets, memory that consolidates overnight — rest is infrastructure, not downtime.
Evals, feedback, and human judgment that set the quality bar — including triaging real production PRs.
An evaluation framework and learning environment where agents get classrooms, curriculum, and feedback.
22+ production PRs triaged
A server-authoritative multiplayer music platform, with production WebSocket infrastructure and monitoring.
100+ concurrent players
Reusable agent skills that declare and resolve their tool dependencies.
MCP Skills Working Group implementation
An adversarial testing skill that finds security and correctness issues before production.
WDE Break prototypes before users do
4 projects
The school for agents: an evaluation framework and learning environment where agents get classrooms, curriculum, and feedback. Its eval system triaged 22+ production PRs through failure-pattern distillation — the quality bar that gates releases.
22+ production PRs triaged by the eval system
A server-authoritative real-time multiplayer music battle platform — the live system where I operate infrastructure in production: WebSocket broadcast layers, CI/CD gates, Discord OAuth, health checks, and monitoring on Railway + Cloudflare Pages.
100+ concurrent players at sub-50ms latency
The textbook side of the school: reusable skills that declare the tooling they depend on and resolve it. I'm spearheading the reference implementation for tool-dependency resolution in the MCP Skills Working Group, so skills can carry their own syllabus.
WG reference implementation for tool-dependency resolution
An adversarial stress-testing skill that tries to break prototypes before production does: security and correctness audits, edge-case abuse, severity-graded findings, and ELI5 explanations. It teaches agents (and their humans) where the weak joints are.
WDE break it on purpose, before users do
Protocol specifications, runtimes, and agent automation — the plumbing that makes external agents trustworthy.
Protocol specs · SEP-2106 · SEP-2640
Relaxed the output schema type gate to accept arrays, primitives, and compositions while keeping inputs strict — 17 new tests, 424 passing, merged upstream after review.
PR 895 ↗Agent runtime infrastructure
Resolved a 64× budget-multiplication defect that caused cascading service failures under concurrent agent load, and deployed a fair-scheduling budget that restored capacity. Also built Notion/Obsidian connectors with scope-enforced OAuth and closed an authz gap on 24 dynamic tools.
budget fix ↗Cross-platform agent automation
Eliminated a prompt-delivery race that left agent automations idle at startup — verified across five platforms and shells (POSIX, PowerShell, cmd, SSH, WSL) to restore reliable initialization.
race fix ↗I write about the pedagogical lens on agentic engineering — what schools figured out centuries ago that agent systems still need.
Longer essays on building environments where agents — and the people who work with them — can actually learn. New posts as the school gets built.
schoolcore.substack.com ↗Curious what I'm up to, or sourcing me for a role? Ask away — human or agent, same desk.
New York based, operating live systems in production, 10 merged upstream PRs across the MCP Rust SDK, OmniRoute, and Orca — and a teacher's instinct for making complex systems learnable.
— Brandon