In Part 1 and Part 2, we used 🐠 Dory and 🖖Spock to explain the difference between Chat and (Co)work. That leads to the next logical question: 🤔 Okay, but which Spock do I use—ChatGPT’s Work or Claude’s Cowork? Personally, I use and like both. The honest answer is that ChatGPT Work and Claude Cowork are built around the same core idea: Give the AI a goal, provide the right context, and let it complete the work. Both can research information, analyze files, create documents, build spreadsheets and presentations, use connected tools, and work through assignments involving several steps. The meaningful difference is where each one feels most at home. Claude Cowork: Best When Your Work Lives in Files and Folders Claude Cowork is especially comfortable when your work lives in files and folders. You can connect a folder on your computer and ask Claude to: - Read and compare several files - Edit or create documents - Rename and reorganize files - Build spreadsheets and presentations - Research missing information - Deliver the finished materials for your review It can work directly with the material inside that folder rather than requiring you to open each file, copy the information into a conversation, and direct every step. Claude Cowork is no longer limited to the desktop. Cowork sessions can also run remotely and be accessed through web and mobile as availability rolls out (more on that later). However, its ability to work with selected local folders remains one of its most recognizable strengths. Claude can also use connectors and plugins: A Claude plugin can package skills, connectors, and sub-agents into a reusable workflow. When a direct connector or tool is not available, Claude can use your computer by navigating applications, clicking, and typing. ⚠️ Note: Claude Cowork requires a Pro level subscription. ChatGPT Work: Best When Your Work Lives Across Connected Apps ChatGPT Work is especially comfortable when your work is spread across connected business tools.

You can choose one AI company for the rest of your days. You may use any tool it creates—and any technology from companies it acquires. What are you choosing? No switching. No backup company. No “it depends.” Which AI ecosystem are you betting on for the rest of your days—and why?

The fastest way to lose a customer isn't bad service. It's a slow response. I've seen businesses spend thousands on marketing, only to lose leads because no one followed up for hours—or sometimes even days. In most cases, the first company to respond earns the opportunity. That's why I believe every growing business should have a system that: ✅ Responds instantly ✅ Books appointments faster ✅ Keeps every lead organized ✅ Reminds customers automatically Technology doesn't replace great customer service—it makes it more consistent. Question: What's your average response time to a new lead? Do you think it's costing you jobs?

I have a joke at work. I call it "the other 80%." Since I started using AI for documents, code, and other projects, I've noticed it scaffolds so fast — and so densely — that it's created a strange paradox around the old 80/20 rule. This joke applies to plenty of other things too, but let's stick with AI. What does it mean? a) It's amazing how quickly you can get almost there the 80%, yet how slowly you actually get there. Hence "the other 80%." b) After scaffolding, it feels like you're 80% done. In reality you may be closer to 20%. What you made may look wonderful and seem wonderful, but hold it up to a quality, context, and clarity lens and often it's more sizzle than substance. c) By the time you've reviewed, updated, and simplified everything, you're drained (but satisfied) — and your tokens are gone. 🙂 **Have I solved it?** Not exactly. But here are a few patterns that are helping: **1) Create lots of skills.** Skills travel better than memory. My rule now: anytime I have to haggle with the AI more than once or twice over the same thing — a missing font, the wrong tone in a document, an ugly table — I stop and say "record what you just did to fix that into a skill, so you know better next time." **2) Create lots of support docs.** AI is great at this. If you're reading this here then you probably already know about markdown. When I'm working on something, or building a spec for an app, I'll tell it at frequent intervals to update the docs and the skills. That keeps those files relevant and lets the AI capture the small details as it goes. **3) Build help and instructions into the thing itself.** When I scaffold, so much gets created that it overflows my mental model, fills me with doubt, and slows me down. Now, if I'm building an app, my pages get little "?" bubbles with the what and how of a given thing. For example, at work right now I'm analyzing phone data for abandoned calls — accounting for short abandons, filtering out internal calls, outbound, extension-to-extension, voice mails. Who can remember all that detail a month from now? Build it in. Then as you iterate, your own notes show up in easy-to-find places. If you're having AI build slide decks, ask it to populate the notes fields so later you can re-absorb your original intentions.

Your feedback is helping shape the future of AI Bits & Pieces, and I appreciate everyone who took the time to vote. Top Three Topics, by votes: 🥇 Introduction to ChatGPT Work / Claude Cowork — 5 votes 🥈 What Is an AI OS (Second Brain)? — 3 votes 🥉 How I Used Obsidian to Create an AI OS — 3 votes We’ll begin creating content around all three topics. 🎁 Giveaway Winner! Congratulations to @Garry Cole, who was randomly selected by AI from all eligible participants! Garry will receive a $25 Amazon eGift Card. ❤️ Winning Charity The winning charity is Winning Futures (@Kristina Marshall)! As promised, AI Bits & Pieces will make a $25 donation to Winning Futures in honor of this giveaway. Thank you again for being part of this community. Congratulations to Garry Cole and Winning Futures! 🎉