GLM AI Model for Agent Builders by Steve Hopkins

You picked up this book because you can feel the ground shifting under software, and typing code line by line is no longer the scarce skill. Maybe you are a developer who senses that agents will write boilerplate while you judge the result. Maybe you run a small business and cannot hire a 120000 $ engineer for every idea, yet you need an app that ships. Or you are a tinkerer who wants to own the model that runs your tools, not rent it forever from 1 vendor. Whatever brought you here, you want a stack you can control, verify, and repeat, and this book builds it with you.
This book is not a prompt trick list that works once and fails on your data, and it is not a vendor pitch for 1 subscription. What you actually need is a portable build loop, Specify, Delegate, Verify, Iterate, plus pieces that make the loop cheap and private, an open-weight GLM model you can run locally, a terminal agent that plans over 600 iterations, a cloud sandbox with proof, and an editor that keeps context. The pages that follow are organized as a tower, with project memory files and test harnesses that survive model updates.
Inside, you'll discover:
• The 4-part task template, goal, context, constraints, and acceptance criteria, with real before and after examples
• How to run GLM locally via a runtime, plus API and coding plan routes at 10% of competitor cost
• Claude Code in the terminal for meaty features and Codex in the cloud for batchable jobs with citations
• Cursor as the thinking surface where inline edits and project chat keep the loop fast
• The handoff discipline, 1 branch per task, plus verification via tests, diffs, and click-throughs
• Automations that check bookings, draft reminders, and write a plain language daily summary while you sleep
• Security, cost, and trust budgets, secrets in the environment and narrow permissions
Ship an appointment scheduler in 1 week, not 1 quarter.