I've been reading about the new Claude Duet - it's another place you might run your AI work. It's a good test for the idea behind AWML: describing the work separately from the platform. Say you want an AI to chase unpaid invoices. What starts the check? Which record holds the amount due? Who approves the message before it goes to the customer? What happens if the job stalls? Duet may be one way to do parts of that work. Its research preview can check connected apps, prepare a reply and ask before sending it. But the job belongs to your business, not to Duet. That's why I made AWML: to draw the steps, the people, the AI and the approval boundaries before choosing where they run. Duet goes in the platform view. It isn't the workflow. chrismdp.com/awml/

I don't trust AI workflows I can't draw, yet I had no way to draw one! I invented AWML to get around that. Through this process I spotted a prompt injection vulnerability in my sales funnel agent, and discovered I couldn't tell where my data was coming from in all cases. Amazingly helpful. Give AWML a try on your workflows, and give me feedback! chrismdp.com/awml/

I’ve open sourced a modelling language for agentic workflows (AWML) I’ve been working on. Modelling workflows independently of eg Cowork, Codex, Managed Agents etc gives you auditing, automatic optimisation, and intentional security boundaries. AWML shows who does each step, where information crosses permission boundaries, and which platform runs it. This is early stage so very keen to get feedback - comment or open a GitHub issue. GitHub: github.com/chrismdp/awml Blog: chrismdp.com/awml

A successful AI demo tells you very little about what's going on under the hood, and who's checking it. chrismdp.com/seven-ai-predic…

I use AI to help with writing and thinking, but I must stand by each word I put out. My new article explains where I draw that line. In short, don't be like Laura :) chrismdp.com/writing-with-ai…

Instead of selling books, will we be selling skills in the future, with the book coming free with the skill? chrismdp.com/slice-your-job-…

AI is good enough, but rollouts stall, and it's normally due to people problems. An example: put your best people in a small AI team and they'll move fast. The rest still have a product to maintain. They watch the new work race ahead while their own chance to learn gets postponed. You can connect the two: share what the team learns, without asking everyone to abandon their existing work. It sounds obvious, but you have to make sure it happens! This is one of seven people problems in my talk at Øredev in Malmö this November. If you're going, come and tell me how your team is handling it! oredev.org/program/25377809-…

Is AI just helping a bit, but not transforming the work yet? I'm trying to learn what small teams hoped AI would do for them vs what it's actually doing, especially where impact is disappointing. If your small business is paying for AI, what did you hope would change, and what actually changed? Reply here or DM me if you'd rather answer privately.

I wondered what it might be like to create video summaries from blog posts, so I tried it. Results below. It took five minutes of my time to get this 80% good enough, but another hour and a half of my effort (and much longer for Claude) to get it to 99%. I had to rewrite the script after seeing the first version, which cost a lot of wasted tokens. David’s point about reviewing early draft outputs is a good one! I’m wondering whether to build this into my blogging process now. Feedback welcome: am I just contributing to the avalanche of slop out there, or is this a good way to reuse content? chrismdp.com/seven-ai-predic…