Before we build it, let’s understand the work. Every Monday, we’ll take a recurring task and break it down: what starts it, what information it needs, what decisions happen, and what should come out the other side. Last Wednesday, we looked at a workflow we’ve been building at GLR and asked: What happens when the workflow runs again? That question matters before you build anything, too. Mapping the work helps you spot the decisions that are easy to skip when you’re focused on getting something running. For this first one, let’s use a simple example: 📝 A meeting ends. You have messy notes. Now those notes need to become something you can act on. “Have AI summarize them” sounds like a complete task. But there are a few decisions hiding inside it. Here’s the map: ⚡ TRIGGER The meeting ends and the notes are ready to review. 📥 INPUT The notes you actually captured. Some things may be incomplete or unclear. 🔀 DECISIONS / TRANSFORMATION Separate confirmed decisions, action items, reference information, and open questions. Was that an actual commitment, or just an idea someone brought up? Was an owner assigned? Was a deadline agreed on? 🧑‍💻 HUMAN CHECK Compare the result with the notes before treating it as the record of what happened. Confirm commitments, owners, and dates. Keep anything unresolved marked as unknown. 📤 OUTPUT A reviewed recap and task list, with unanswered questions still visible. ⚠️ WHAT COULD GO WRONG? “I could probably handle that” becomes an assigned task. “Maybe next week” becomes a deadline. An idea becomes a decision nobody made. The result can look organized and still be wrong. 🧪 FIRST TEST Try this with one set of notes. Check every action item against the original. Can you trace each owner, deadline, and commitment back to something actually recorded? If you can’t, that’s something to resolve—not a blank for AI to fill. Your turn: Pick one task that keeps coming back and map these five parts: Trigger → Input → Decisions / transformation →

Welcome to the workbench. Every Wednesday, we’ll open up something real — a build, problem, decision, failure, experiment, or lesson from inside the Lab. For the first one, here’s something from a system we’ve actually been building at GLR. We had a workflow that could find leads due for follow-up, send the right alert, and update the record. That worked. But working once isn’t enough. ⚠️What happens when the workflow runs again?⚠️ If a lead has already been handled, the system needs to recognize that and do nothing. So we tested it again. The workflow still woke up. It still checked the data. But there were no eligible leads. The alert paths stayed inactive. No duplicate message. No unnecessary update. That small test represents a much bigger systems principle: A workflow isn’t finished when the happy path works. You also need to know: → What happens the second time? → What happens when there’s nothing to do? → What happens when something already happened? → What stops the system from repeating itself? Sometimes the most important thing a system can do is know when not to act. My workflow is dropped below! Your turn: Think about a workflow you use, want to build, or deal with regularly. What could go wrong if it accidentally ran twice? 👇Drop it below.👇 🧪 Unfinished answers are welcome — this is the Lab.🧪