Patterns for the Agentic Age

A working library of patterns for building with AI agents.

Each page below is one pattern, one failure mode, or one hard-won lesson from actually running multi-agent systems in production — not theory, not a framework pitch. Read the ones that match the problem in front of you.

13 specs, newest first
2026-07-28

Why LLMs Fail: The 5 Root Causes Behind Every Agent Failure Mode

LLM agents fail in 22 named ways, but those trace to just 5 root mechanisms in how the model works. Guard the root, cover the whole group.

Read the spec →
2026-07-28

The Post-Office Pattern: How Agents Should Send Each Other Mail

A centralized mail-routing pattern for multi-agent systems: agents drop messages in one shared outbox, a shell script routes them to inboxes. Scripts for mechanics, agents for judgment.

Read the spec →
2026-07-27

The Roster: 101 Agents, 11 Teams, One Conductor

The actual scale of a production multi-agent system: 101 agents across 11 available teams, roughly 20 disciplines, and one conductor above all of them.

Read the spec →
2026-07-27

The Handoff Graph: Why This Agent System Isn't a Pipeline

Eleven agent teams declare only what they consume and what they produce. The conductor infers a run order from those declarations, live, every time — a graph that grows by wiring one team, not rewriting a chain.

Read the spec →
2026-07-27

The Depth Gauge: How Deep a Real Agent Team Actually Goes

Eleven agent teams, sounded three layers deep: the contract the conductor gets, the real headcounts and skills behind it, and how the pieces move.

Read the spec →
2026-07-27

The Conductor Pattern: How a Real Multi-Agent System Actually Coordinates

A growing roster of independent agent teams, one conductor that never reads their internals, and the rule that makes it work: trust is built by refusing to look.

Read the spec →
2026-07-27

The Anatomy of an Agent Prompt: 5 Parts Most Prompts Are Missing at Least Three Of

Identity, boundaries, procedure, voice, and self-report tell a model how to behave under pressure. Most agent prompts only have two of the five.

Read the spec →
2026-07-27

Field Report: What a Production Multi-Agent System Actually Taught Us

A real multi-agent system's failure, what it revealed, and why the specifics stay redacted. Proof of operating depth, not a blueprint to copy.

Read the spec →
2026-07-27

Stop Listening to the Edges: AI Takes Are Noise, the Middle Is a Conversation

One edge says AI does the thinking for you. The other says AI does no thinking for you. Both absolutes, both wrong — the signal is the conversation in the middle.

Read the spec →
2026-07-27

Agent Architecture: The Org Chart Every Multi-Agent System Already Has

Every multi-agent system is secretly hub-spoke, mesh, or hierarchy. Each shape has a name and a predictable way it breaks. Pick on purpose.

Read the spec →
2026-07-22

The Memory Ladder: Files, Database, RAG, or Knowledge Graph?

When to use files, a database, RAG, or a knowledge graph for AI and agent memory. Four rungs, and a climb trigger for each.

Read the spec →
2026-07-18

22 LLM Agent Failure Modes (and the Prompts That Guard Against Them)

22 ways LLM agents fail, each with the drop-in prompt that counters it. Guardrails for agentic systems.

Read the spec →
2026-06-28

ActiveAI — ActionMailer for LLM Calls in Rails

ActiveAI does for LLM calls what ActionMailer does for email — a Rails gem with generators, agentic loops, and full ActiveSupport instrumentation built in.

Read the spec →