Ethan B. Holland

Over 51,300 manually organized AI links and counting

AI Virtual Inn of Court: Links for Tuesday February 17, 2026

These links are for our February 17th meeting. The information is up to speed as of January 16, 2026 and goes back to September 2025. The only major topic I’ve left out is robotics, because it’s too esoteric (for now).

Every week I organize 200-600 links, and I write accessible executive summaries of the top 20-30 stories. The archive is here if you’re interested: https://ethanbholland.com/category/this-week-in-ai/

Before reading this month’s links, here are three helpful archived AI Virtual Inn links, if you’re new or looking to refresh what we’ve discussed previously:

AI Virtual Inn of Court: Links for Tuesday February 17, 2026

If you take a few days to skim these links during breaks, you’ll be more informed than most of your peers. I’ve curated these carefully to be all killer no filler. I’m happy to discuss these anytime. In April, I’m presenting to the Inn and I’ll review many of these with the group on the Zoom. For today, consider these take home reading and something to share with coworkers.

Agents

Tools

Law and Ethics Milestones

Autonomous Vehicles

“Unique Situations”

Deep Fakes

Imagery

Quick example of Gemini’s ability to digest and display large amounts of information…

I pasted the following two sections (everything in italics below the image) verbatim into Gemini’s image tool and prompted “Please read this overview and then make a illustration or cartoon that shows the two sides of the equation getting chipped away like the tunnel analogy”… this is what it made for me:

Open AI Apps
Returning to the top story, OpenAI’s Dev Day included a live demo of apps inside ChatGPT. At launch, the app partners include Booking.com, Canva, Coursera, Expedia, Figma, Spotify, and Zillow. I’m proud of myself for calling Spotify two years ago. They are clearly a predictable launch partner!
https://openai.com/index/introducing-apps-in-chatgpt/

This will push the dialogue about how publishers view getting paid for their content. Historically, publishers were upset that they were “training the chatbot,” whereas I’ve always felt that the chatbot is simply a language interface and not meant to be an answer-bot.

There’s a very big difference between asking a chatbot to do something…and getting lost in the sauce because LLMs are so good at general knowledge that we think they should riff facts as part of next token prediction. It’s insane that it works at all for answering questions… We called the predictable gap in chatter prediction… hallucinations.

In reality, there’s no need for hallucinations If we know what it’s meant to do, it’s meant to understand our question… and then it can go get the answer with tool use and integrations. We’ve been dunking on six-year-old LeBron. Dunning Kruger at its finest. Now LeBron’s getting competitive.

The more we think about chatbots as interfaces for agents… which then go out and do work, the better we’re all going to be. That shifts the conversation away from publishers arguing that they should be paid to train a chatbot to speak, and instead toward the idea that their content should be paywalled so that if you want real-time access within a chat, the chatbot has to verify that you’re paying for it… or at least subscribing in some way.

The more we think about chatbots as interfaces for agents… which then go out and do work, the better we’re all going to be.

The big conundrum now will be the combination of web browsing and agents that can find free content as an alternative to paid content. A lot of content is plentiful, not copyrighted, and easily discoverable, for example, sports scores, the weather, a recipe for chili… these may hard to put behind a paywall.

However, for the things we rely on, where we can’t risk hallucinations and we require confidence security and structure, like commerce , finance, real estate, or legal interactions, the app model will work really well. The impact on page views and browsers will be a ring on the tree of history… and could mark their end over the next few years.

Open AI Agent Tools
As if connecting two ends of a tunnel, OpenAI also released their agent development toolkit… that allows developers and companies to build and optimize agents. These are very robust tools for building production-level, complex agents with pipelines, tuning, and front-end design. It might even be better to think of these as enterprise applications. Agent Builder includes a visual development canvas where you can drag and drop logic and connect tools. It’s very similar to n8n, if you’re familiar with that. In fact, it basically competes directly with a lot of these development tools. https://openai.com/index/introducing-agentkit/

So, as you can tell, we’ve got commerce and apps being integrated into chats, and then offline from the chats we’ve got agents that can use the engine to accomplish tasks. As they say, it’s difficult to fight a two-front war, and that’s what’s happening right now with the entire internet legacy infrastructure.

I haven’t had a chance to play with the app agent developer kit, but it seems really fun, especially for simple things. Even if you’re not a developer, there are things you can do to take routine tasks, automate them, and have some fun.

Feats of Strength

No Code Annotated Website of Large Corpus
“I took the surviving syllabus of W. H. Auden’s 1941 “Hardest Class in the Humanities” (6,000 pages of reading, memorization of poems, etc.) & turned it into an annotated site with all the readings. (Would have taken hours, instead it was 4 prompts)”

Here’s the website the AI built (must see link!)
https://68f4202753e83cc5fbf8172e–tiny-tarsier-c997a9.netlify.app/

https://www.theparisreview.org/blog/2018/04/11/a-homework-assignment-from-w-h-auden

No Code Correlation vs. Causation App
Ethan Mollick also built an interactive explainer app using Claude that demonstrates correlation vs. causation. He literally created it with a one-sentence prompt. I think everyone needs to see this to understand just how powerful the tools have gotten, and how little is needed to generate significant results.

An instant interactive explainer from Claude for a frequent debate about correlation & causation. Prompt: “Create an interactive tool that explains all the ways two variables can be correlated (causation, random chance, reverse causation, etc)”
https://x.com/emollick/status/2005554673240195455

Try out the app at the link below… it’s incredible.
https://claude.ai/public/artifacts/5e9ad491-a9e3-4f5f-a290-8130d2c25733


Too complicated? Mollick changed it completely with a one sentence criticism:

“Cool but too complicated for people without a stats background”

And now he got this app as a more friendly version:
https://claude.ai/public/artifacts/71eb192e-245d-45b0-aa80-3a0e76fd18a9

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