Am I the only one having a hard time pricing stuff??? When I ask Claude it seems super dupper high. I aint sure people pay so much. Need help understanding the pricing aspects of the business.

Something I read in The Age of AI made me rethink how I use ICM. My natural tendency is to approach ICM through business process orchestration. I define the stages, describe the steps, and try to make the whole workflow explicit. But sometimes I take this too far and turn the stages into strict rules. The result becomes over-engineered, uses more tokens, and often works less naturally with AI. I recently had the opposite experience. We replaced a detailed process with a simple skill that described the essential pattern, and the results were much better. That made something click for me. Maybe stages should act as an interpretable scaffold, rather than a fixed algorithm. They can clarify the purpose, context, constraints, handoffs, and expected outcome, while still allowing the AI to work out the best path. AI may free us from having to define an entire process in advance. But if we specify less, evaluating the outcome becomes even more important. We need to check the quality of the result, capture what we learn, and use that learning to improve the scaffold over time. Does anyone else start with ICM and then gradually slip back into rigid, rule-based process design? How do you decide what needs to be specified and what should be left for the AI to infer?

Hi everyone, I’m in a bit of a pickle with a client. My client who runs an e-commerce business wants me to create a template for a workflow that helps him with copywriting. The template serves as a framework for him to add his knowledge to, and any additional instructions on how to do the work. However, I don’t want to be held accountable for how he uses the workflow or whatever adjustments he’s going to make to the workflow. E-commerce can sometimes be a questionable business from a legal perspective. I’d like to know if there are ways to protect myself and my work in case he adjusts the workflow to fit his needs. Again, I am only creating a template for him to use. I don’t want to be held accountable for the output. Is that realistic or should I just drop the client? This also applies to more general use cases. How do you protect your work from any adjustments that may be made outside of your control? For example, my workflow might include a part that always includes ‘this text is AI generated’ (in accordance to EU regulations). If I give this workflow to my client, I have no control over him adjusting this part of the workflow. If he deletes this part, how can I protect myself in case he gets sued?

🎁 $1,000 IN EDUBAWARE CREDITS 🎁 One winner takes it. 📋 THE CHALLENGE Build a folder-based AI translator that takes one kind of work and turns it into another kind of work. Same shape in, same shape out, every time. Not a summarizer. Not a writer. A converter with a contract. This week's deliverable is one translator folder that someone could drop into a Claude project, feed it the input it expects, and get back the output it promises. Every time. Without surprises. 🎯 PICK YOUR CONVERSION The conversion is yours. Pick one you do by hand right now and hate. A few sparks to get you thinking: - 📞 Sales call transcript → CRM notes in your team's exact fields - 📝 Long-form essay → LinkedIn carousel, slide by slide - 🎙️ Meeting recording → product requirements doc - 🔬 Research paper → investor one-pager - 🐛 Bug report thread → Jira ticket with repro steps - 📧 Customer email → support ticket with severity and category - 📊 Spreadsheet export → weekly status update - 📖 Interview transcript → case study draft - 🧾 Receipt photos described in text → expense report line items - 📋 Discovery call notes → SOW first draft The more locked-down the output, the better. "Turns notes into a doc" is not a contract. "Turns discovery call notes into a five-section SOW where section 3 is always scope exclusions" is. 🔥 THE ANGLE THIS WEEK Last comp was The Auditor. Every finding cited a provision so a reader could open the standard and check. The comp before that was The Cartographer. Every card cited a file and a line so a reader could open the source and check. The Translator is the same discipline, one more time. Every line in the output traces to a line in the input. ↔️ A translator has three properties that a summarizer does not: 1. The output has a fixed shape. Same fields, same order, same format, regardless of what the input looked like. If the input was messy, the output is still clean. If the input was short, the output still has every field, marked empty where there was nothing to fill it.

I was invited to sit on a panel this morning: "AI in Action: The Mindset Behind the Moves," at Auxiom's Community Appreciation Event, attended by 120 business leaders in Detroit Metro. Grateful to Founder and CEO Matt Loria for the invite. Auxiom is a local IT and cybersecurity company. Before the panel, Ashok Sivanand (Nous) ran the room through a workflow-redesign workshop. He opened with a stat from McKinsey: 80% of companies doing generative AI work saw no change in profitability. He paired it with another: only 1 in 5 companies had actually redesigned a workflow before pointing AI at it. Same 1 in 5, both times. He called it a coincidence. This is similar data I referenced in David's Corner, The Tool is 10 Percent. His worksheet was amazing though: name the constraint, name the workflow, name your customer, find the leak, pick one fix, run a 30-day experiment with a guardrail and a report-back date. His line on the handout: diagnose before you prescribe. All 120 execs walked out of that room with a real next step; that's rare for many speakers. On the panel, I got to talk about an idea I've been writing about here: AI does two different jobs. It's good at mining your own record for what's already true, and it's good at amplifying whatever you give it. Skip straight to amplifying, and the output sounds like everyone else's. Someone asked what my own transition looked like, going from a 12-person team to running alongside 20-plus specialists. Two years chasing tools before I found ICM. Two weeks after that, I converted all my unstructured data into structured markdown and built my routing map and orchestrator, Duke. After, a CIO on the panel asked me how I was able to orchestrate across 50k markdown files. I said, "Simple: a map, and dropped Jake Van Clief and ICM as the solution." The closing session was Aaron Salko and Kelly Johnson on human performance. A line I wrote down: "Technology creates capability; human performance determines the outcome". If you've got performance gaps today, AI doesn't fix them. It multiplies them across more people.