AI Agent Architecture Cheat Sheet
Every moving part drawn out: reasoning, memory, retrieval, tools, guardrails, and the point where a person signs off.
IndexAgent engineering
Agent engineering
How an agent is put together, and what has to be true before it runs unattended.
All sheets
Every agent engineering sheet, in order.
Agent Development Kit
The five layers a Claude Code team assembles before shipping — memory file, skills, hooks, subagents, plugins.
Agentic Loop Automation Blueprint
Turn a one-shot script into a loop that knows when to stop, what to log, and who to escalate to.
Agentic AI, Without the Mythology
An engineering-led field guide to agentic architecture — what the terms actually mean, and what holds up outside the demos.
The Agent Loop, Verified
A viral 'Loop Engineering 101' poster checked against real agent mechanisms: open vs closed loops, quality gates, the self-learning rules file — what's sound practice, what's folklore, and the numbers nobody can source.
Seven Kinds of Agent Memory, Checked
A viral seven-part taxonomy of AI agent memory, verified against how research and shipping products actually use the terms — a rare poster that's mostly right, plus the build order it implies.
RAG, End to End — the Honest Map
A circulating end-to-end RAG diagram verified stage by stage: this one is the real thing — permission-aware retrieval, reranking, observability rails — plus the three places even a good map compresses too far.
Building Agents: Three Posters, One Working Method
Four viral agent-building graphics consolidated and verified: the durable skeleton they share, the multi-agent cost patterns worth knowing, the 2026 protocol stack (MCP + A2A), and a hard look at a 'bypasses bot detection' promo.
Agent Loop — How AI Agents Actually Work | ImageFirm
A refined ImageFirm explainer of the agent loop: orchestration, state, tool use, termination, reliability, observability, context management and production
How AI Works—and Why We Cannot Fully Explain It | ImageFirm
An academic visual explanation of neural networks, Transformers, training, inference and the scientific problem of AI interpretability.
Agentic AI Knowledge Graph — ImageFirm Field Guide
A verified, production-oriented learning map for agentic AI: foundations, retrieval, memory, orchestration, evaluation, governance, observability, economic
What Happens Inside an AI Agent — The Anatomy of a Run
A stage-by-stage anatomy of a production AI agent run: understand, plan, retrieve, reason, act, observe, loop, verify, deliver — with the controls, failure
Universal AI Agent Architecture
Explore the universal anatomy of any AI agent. ImageFirm presents the definitive architecture diagram explaining perception, reasoning, memory, planning, a
Agentic Memory: A Production Architecture for AI Agents
A research-grounded ImageFirm field guide to short-term context, retrievable working knowledge, durable agent memory, retrieval policy, governance, evaluat
The Agent Go-Live Gate — 24 questions before an AI agent runs unattended
Is your AI agent ready to run without a human checking each run? Score it against six gates and six hard stops in eight minutes. No sign-up, no trackers, n
Enterprise AI Agent Readiness & ROI Framework 2026
A practical 2026 decision framework for enterprise AI agents: score readiness, model ROI, choose autonomy, map governance, and build a 90-day path from wor
Agentic AI Engineering
Another example of an agentic worklflow loop.
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These sheets are the method in the open. If you want it applied to your own agents, rollout or operation, start with an enquiry and tell us what you are trying to build.
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