I’m running into a massive bottleneck with corporate clients right now. Because they’re handling market-sensitive data, their IT compliance teams have them completely locked down into Microsoft. No external APIs, no Claude—nothing. Ideal world would be building solutions in CC. I’m convinced the only real solution here is building custom tools and agents natively inside their system (Azure OpenAI, Power Platform, Copilot Studio, etc.) rather than trying to pitch external pipelines they'll just reject anyway. Has anyone actually built robust, advanced agent workflows strictly inside an MS-only corporate environment? Curious to know how you handled the architectural constraints, and if it's worth the headache of building inside their sandbox. Let me know what you've found works.

You learned the framework. Now try it on something you're actually working on. Vote below, then drop your prompt structure in the comments. Not the output. The structure. Show us how you set it up.

Last night, before bed, I picked up my phone. Old habit. Check YouTube, X, Reddit. See what I missed. Hunt for the hidden gem someone posted about AI. I put it back down without opening any of them. Not because I was tired. Because I didn't want to. And when I thought about it, I realized I haven't actually done that routine in a while. For most of us, the answer to the title question is probably the same: "Stop Building AI Agents. Use This Folder System Instead." That was two months ago. It's why most of us are here. Everything I was hunting for out there, I have now in this community. The videos that came before that were all the same. Everyone was copying each other. New model, new skill, someone's hot take on what changes everything. I kept watching because I thought the next one would be useful. It wasn't. Curious if anyone else has had this happen - where the community replaced the hunting behavior that used to eat your nights. What did you stop or start doing once you found Clief Notes?

This is a little bit of a rant cause I can’t post these thoughts anywhere else. At least, I’m not ready to get publicly crucified yet, so… I cannot talk to almost anyone I know about ai. They have no idea what’s going on, or about the kind of stuff we do. It’s all doom and gloom. There is something that really bugs me about it, beyond the naivety and half-glass-full mentality. It’s that, gatekeeping does nothing for humanity and is a selfish mentality at its core. So ai has access to lots of data, and artists data. So what? If you’re really good, it doesn’t matter. Great products, great services, great talent all have one thing in common which makes them in-demand. They’re great. And greatness is witnessed by all the people who consume their work. There’s no gatekeeping because it’s literally on display. From Harry Potter to Michael Jordon, Disney to Taylor Swift, Steve Jobs to Crayola Crayons. If no one is trying to copy you, then your work isn’t loud enough. Either because it’s not good enough (yet), or because you’re hiding it away from the world out of fear. Bringing it full circle… Nobody lost money cause I finally had a tool that could do work for me for free. Rather, everyone in my companies will literally make more money because of massively efficient operations. It also means we’ll be able to afford remarkable talent with the extra profits we bring in due to that efficiency. I’m SO glad I have more options to take care of the people I bring into my sphere. One last thought… a little side quest here.. Whenever I ask people about why it isn’t a good thing that robots will be able to farm all the organic food we need at extremely low costs to produce compared to what we have now, no one has a good answer. I used to be of the mindset that really rich people should use their money to fix problems like world hunger. Then I actually looked at the challenge of getting the recipients to use money the way it’s intended, and crunching numbers to see how long they could solve it for, and full stop, it doesn’t work. Complex problems require complex solutions. A billion dollars solves world hunger for how long… a day? A week? A month? And then what?

Today, I stumbled over this video short and just began looking at it. It's about HTML files handling a lot more that MD files. Some of what I found: Thariq Shihipar from Anthropic's Claude Code team recently sparked a major industry debate by advocating for HTML over Markdown (.md) as the default format for AI agent outputs. His core thesis, titled "The Unreasonable Effectiveness of HTML", argues that Markdown has become a "cognitive nightmare" for humans as AI models handle increasingly massive context windows and complex, multi-hundred-line tasks. Why Anthropic Engineers are Ditching Markdown - The "Wall of Text" Problem: When Claude generates complex 200-line development plans or code reviews, humans stop reading them and just blindly skim or approve them. - Rich UI Elements: HTML natively supports collapsible sections, internal jump-links, side-by-side grids, and interactive scaffolding. - Native Visualizations: Instead of forcing AI to build ugly ASCII diagrams or fake charts using Unicode, HTML allows models to generate fully styled tables and actual SVG illustrations. - The Token Cost Trade-Off: While generating HTML consumes significantly more tokens and takes longer, modern context windows make the extra cost negligible compared to the massive value of a highly readable document. Ultimately, the theory suggests that instead of viewing AI as just a text generator, outputs should be treated as dynamic, interactive interfaces that keep humans engaged in the loop. Thariq Shihipar introduced the concepts in a widely discussed essay and social media breakdown titled Using Claude Code: The Unreasonable Effectiveness of HTML. He later expanded on these exact workflows and operational data during an interview on Lenny's Podcast. I think adding an HTML file could look like the image I've attached. Where a clickable report for presentation for your prospect outlines everything in an easy-to-read format.