Coté

When you don't know what you're doing, do a lot of it

This a good, correct framing of the AI project failure stuff. No one really knows what will work and what they’re doing yet. As we learned in the digital transformation craze of the 2010’s, this means failure == learning. And learning is what you need to do a lot of.

More so, this kind of rapid learning, innovation, and sense making is exactly what a platform like Tanzu Platform with Cloud Foundry is excels at, and has a long, proven history of supporting.

You focus on learning new business models, features for your apps, and what works by writing and deploying code instead of building containers and configuring infrastructure.

And, as I like to say, if your organization writes a lot of their own code, there’s a good chance you already have the Tanzu Platform in place, ready to use. Just ask around.

Check it out: “How To Build Agentic AI That Ships," Brian Friedman and Jonathan Eyler-Werve, The New Stack, September 15th, 2025.

Claude Code for things that are not code - Claude Not Code

Auto-generated description: A presentation slide showcases screenshots of various applications and features related to ChatGPT, programming tools, and AI in applications, accompanied by bullet points on their uses and benefits.

There’s a creeping notion that Claude Code (and OpenAI Codex, I guess) are very useful for things that are not code. In the Obsidian community, where you keep your decades of notes as plain text, markdown files, some people are using Claude Code to do analysis, reformatting, etc. of their notes. I can see that you could do the same thing with the pile of Dungeons & Dragons stuff I have laying around.

This makes sense, really. Source code is just plain text as well.

Doing this kind of thing from your desktop, where you control all of the integrations and data access instead of waiting for a developer to do it for you, feels like it’d be easy. I think the Goose people are figuring out this form-factor for AI apps: focus on building out a tool belt (MCP as plugins) for a general purpose chat app rather than fit-for-purpose apps that use AI in the background. A classic suite versus point-solution situation.

Here is my current theory: the GenAI we start seeing in enterprises won’t be integrated into your existing apps (like online banking), but will show up (still) in the form-factor of chat apps in those apps (those little pop-ups in the lower-right hand corner, except now they have all your context) or tool belt apps like Goose.

That is, AI will not be integrated into existing apps, it will be a new, stand-alone app (or “workload”).

Somewhat related: I’ve been consistently disappointed by Gemini’s integration into Google Suites (we have this at work). Yesterday I asked it to do some simple reformatting of a column in Sheets (convert date formats) and it flat out said “I can’t do that.” I took a screenshot of the dates column, gave it to ChatGPT, and asked it to reformat the dates and output it in a format ready to paste into Sheets. It did it perfectly, instantly. Most of the time when I use AI integrated into an app, I really just what the standard chat interface that can pull from and push back to that app.

That feels like what Claide Code is trying to do. I’ll have to try it out in Claide Not Code style.

How to use Tahoe's new Use Model shortcut to summarize articles

The new Use Model shortcut in Apple Shortcuts opens up a lot of possibilities. For example, I like to summarize a lot of pages. Sometimes, ChatGPT can’t get the text for those pages, or I don’t trust the text it retrieves. There’s a shortcut that will retrieve the cleaned up text of a page (as markdown). So, you can get that markdown, and with the new Use Model shortcut, you can summarize it and then send the markdown summary to Drafts. You could open the text up in another app to view, whatever you like, but as you can imagine, I like to catalog this stuff. Also, it can generate a little link to include for my newsletters link list.

You put this in your Sharesheet, and now when you’re reading the World Wide Web, you can get summaries real quick-like.

Here is the shortcut:

I left in the stop and output for debugging, but I’d take that out.

Here is output from one of my articles:

Developers Aren’t Using Your Platform? Marketing Might Be the Missing Link

Source summarized: Driving Platform Adoption: The Missed Opportunity of Marketing.

Internal Developer Platforms (IDPs) often fail to gain traction despite delivering exactly what engineers request. This piece argues that platform marketing—alongside product management and community building—is the missing discipline most teams ignore, and offers a systematic approach to drive developer adoption.

Key Insights

  • Define your developer audience narrowly before pushing adoption efforts.
  • Craft messaging that focuses on developer benefits, not platform features.
  • Position your platform in clear, specific contexts (cloud-native apps, AI workloads, regulated environments).
  • Lead with value propositions that are measurable, like time savings and frictionless onboarding.
  • Avoid the “platform for everything” trap; targeted positioning accelerates adoption.
  • Integrate marketing with product management for tighter feedback loops.
  • Use developer-friendly proof points (fast deployments, pre-approved services, reduced ticketing).
  • Iterate adoption starting with a few archetypical teams before scaling org-wide.

Most organizations spend years building internal platforms that meet developers’ stated needs, only to watch usage stagnate. Teams often assume technical excellence alone will win hearts and minds. The authors note that marketing—treated as a rigorous engineering-like discipline—can bridge that gap by creating awareness, clarity, and trust. The first step is laser-focusing on the actual developer persona who will use the platform. “Developers” is too broad; target application developers in specific business domains and technology stacks to avoid generic messaging.

Messaging, positioning, and value propositions form the backbone of platform marketing. Messaging should translate features into developer-relevant benefits: zero setup time, fewer meetings, and faster deployments. Positioning narrows the platform’s role in the ecosystem—rather than claiming to be universal, identify where the platform delivers the most leverage, from legacy modernization to AI-driven applications. Value propositions then provide concrete, provable outcomes, like cutting deployment cycles from days to minutes or eliminating 80% of security review meetings.

Finally, the authors emphasize that platform marketing is not fluff—it’s how you engineer adoption as deliberately as you design pipelines. By starting small, learning from early adopter teams, and communicating benefits in precise, outcome-driven language, organizations can finally capture the ROI on their internal platform investments. Marketing is not a side hustle; it’s the connective tissue that transforms a platform from shelfware into a strategic asset.

Summarized by ChatGPT on Sep 16, 2025 at 1:09 PM.

Fantastic! I used to have to do this manually.

And, are the summaries good? They’re not always perfect, but I’m often looking to see if I should spend the time to read the whole thing, especially if it’s long and…not the best of writing.

All of the nerd content I've made this fiscal year, so far

This is “content” I’ve made from November, 2024 to today that has something to do with my work. Mostly “to do with” means “talks about the tech world,” if not directly about the concerns and products we have and do at Tanzu.

Items include videos, podcasts, white papers, published recordings of conference talks, guesting on other things, etc.

That’s 141 items of “content.” The robot helped me generate this, so pardon any linking or date errors. And, I didn’t go back and fetch the exact Software Defined Talk URLs. Boo!

There’s also a list of conferences I’ve spoken at, which has some cross over if there is a published recording of the talk. You can see my selection of those recordings, over the years, over in YouTube.

Export markdown from Apple Notes, even in bulk...almost works.

In macOS Tahoe, you can finally export Apple Notes in markdown. This is great, and even exports images and handwriting from the Apple Pencil. You can also bulk export, which is great! Sadly, bulk exporting images and handwriting doesn’t work. It saves the images and handwriting in a file called Attachements, but then in the actual note markdown, all references to images are to a file called FallbackImage.png. Also, it exports an sqlite database. I’m not sure what’s in there, it’s all gobbledygook to me.

ChatGPT uses, a survey

🤖 What do people actually use ChatGPT for? OpenAI provides some numbers. – OpenAI’s first usage study reveals ChatGPT’s massive growth, demographic shifts, and main use cases. // More concise list of uses here. //

And, more from El Reg, including the conclusion from the paper:

The paper concludes “users currently appear to derive value from using ChatGPT as an advisor or research assistant, not just a technology that performs job tasks directly” and that the bot “likely improves worker output by providing decision support, which is especially important in knowledge-intensive jobs where productivity is increasing in the quality of decision-making.”

Here is the actual study.

Invisible to the robots

In my searches/research, analysts like Gartner, IDC, and Forrester are invisible to ChatGTP, Claude, etc. The robots will find the reports licensed by vendors - I’m guessing only if they don’t require leadgen.

The analysts should probably start publishing some juicy abstracts with just enough numbers, analysis, and advice to get into the training data and search results to get people to funnel to their pages. Of course, converting a rando-click to a $95,000 PDF would be some real funnel-management magic.

When the AI policy board is slowing everything down youtube.com/shorts/Xq…

AI uses at Goldman

Goldman Sachs bankers explore limits of AI: ‘The risk is over-reliance’

Some enterprise uses of AI. In this case, it feels like it’s all just using a chat app integrated with data - if even that!

“Goldman rolled out its generative AI-powered platform – GS AI Assistant – to all its roughly 46,000 employees in June, telling staff the aim was for it to help with tasks such as summarising complex documents, drafting content and performing data analysis.”

And: “They offer enormous efficiency gains, such as drafting documents for an initial public offering in minutes that previously would have taken months, or quickly sketching out a multiyear investment plan. But they can lack the personal nuance that is crucial in a demanding client service business such as banking, which commands multimillion-dollar fees.”

Also: “So far she says AI has helped her do her job in four key ways: getting quick answers to complex technical questions; summarising the key points within dense documents; editing and polishing her own written work; and brainstorming. Time saved can be spent with colleagues and clients.”

From: “Goldman Sachs bankers explore limits of AI: ‘The risk is over-reliance,'" Joshua Franklin, Financial Times, September 14th, 2025

Private Cloud

Somewhere between 40% and 60% of apps run on private cloud, you just never hear about it.

@cote@hachyderm.io, @cote@cote.io, @cote, https://proven.lol/a60da7, @cote@social.lol