Anthropic's CCA Exam as a Field-Guide for Agentic Engineering — Frank Coyle, UC Berkeley
Source
AI Engineer
Author
AI Engineer
Date
Terms in this piece · Glossary
context window — The maximum amount of text a model can consider at once — its working memory for the current conversation or task.
AI agent — An AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.
Why it matters
context windowThe maximum amount of text a model can consider at once — its working memory for the current conversation or task.Full definition → discipline is where most production AI agentAn AI system that doesn't just answer once but works toward a goal in a loop — taking actions, reading the results, and deciding what to do next.Full definition → systems quietly fail, and this names the specific moves that cause it. The critic-without-reasoning trick is a genuinely useful defense against agents converging on one idea.
Key quotes
“understanding what you should not do is the key to leading you to what you should do”
Frank Coyle
“The problem is the LLM can't do anything. It is just a probabilistic next word predictor. It can't execute tools.”
Frank Coyle
“If you add the loop, you have Turing computability.”
Frank Coyle
“context means tokens, tokens mean money, and the more context you have, the more confused the LLM is going to be in giving you an answer”
Frank Coyle
“Nothing is a mistake. There's no win and no fail. There's only make.”
videoI Gave an AI a Body — Cyrus Clarke, MIT Media Lab
videoThe Dark Arts of Skill Engineering — Paul Bakaus, Renaissance Geek
videoOperating Distributed Inference Systems at Scale — Nishant Gupta & Naman Ahuja, Meta
videoVertical Mobility: Inference from MVP to Trillion-Parameter Workloads — Sitanshu Gupta, CoreWeave
