We ordered a wood chest that arrived with cosmetic damage. After logging the damage in their customer support interface, it prompted me to start a chat with their AI virtual assistant. What happened next: 1. It immediately offered me a 15% refund to keep the product 2. I asked for 20% and it immediately agreed 3. I asked for 25% and it immediately agreed 4. I asked for 30% and it turned me down 5. I took the 25%, which was, indeed, immediately refunded Turns out that negotiating with a rules engine is way easier than negotiating with a human tasked with operating a rules engine.

Mitchell Hashimoto, founder of Hashicorp (https://www.hashicorp.com) and, more recently, Ghostty (https://ghostty.org) in a post on his relationship with AI coding (https://mitchellh.com/writing/my-ai-adoption-journey): Instead of giving up, I forced myself to reproduce all my manual commits with agentic ones. I literally did the work twice. I'd do the work manually, and then I'd fight an agent to produce identical results in terms of quality and function (without it being able to see my manual solution, of course). This was excruciating, because it got in the way of simply getting things done. But I've been around the block with non-AI tools enough to know that friction is natural, and I can't come to a firm, defensible conclusion without exhausting my efforts.

My friend Eric Doggett (https://ericdoggett.com) became a Disney Fine Artist a couple years back and he's currently being featured at EPCOT's 2026 Festival of the Arts (https://disneyworld.disney.go.com/events-tours/epcot/epcot-international-festival-of-the-arts/). Each day this week, he's holding court to talk to people about his work at a pop-up gallery just outside the Mexico Pavilion. Myself and a few other friends ganged up on him this afternoon to lend our moral and financial support by showing up and buying a few pieces.

Elon has combined 3 of his 4 businesses and everything makes sense. Also, I went to Japan and all I came back with was another weird story about animal sperm. Other stuff happened too, but let's be honest, it's the typical AI schlock you've come to expect from this decade. Write in with your own takes to podcast@searls.co. Please. Really! Do it. Citations needed?

Glad to see Jerod properly follow up on this one (https://jerodsanto.net/2026/02/the-shovelware-cometh/?utm_source=changelog-news): In September of last year, I covered (https://changelog.com/news/160) a post by Mike Judge arguing that AI coding claims don’t add up (https://mikelovesrobots.substack.com/p/wheres-the-shovelware-why-ai-coding), in which he asked this question: If so many developers are so extraordinarily productive using these tools, where is the flood of shovelware? We should be seeing apps of all shapes and sizes, video games, new websites, mobile apps, software-as-a-service apps — we should be drowning in choice. We should be in the middle of an indie software revolution. We should be seeing 10,000 Tetris clones on Steam.

For however expensive LLM inference supposedly is, OpenAI continues to be stupidly stingy with respect to web searches—even though any GPT 5.2 Auto request (the default) is extremely likely to be wrong unless the user intervenes by enabling web search. Meanwhile, ChatGPT's user interface offers: • No way to enable search by default • No keyboard shortcut to enable search • No app (@) or slash (/) command to trigger search • Ignores personalization instructions like "ALWAYS USE WEB SEARCH" • Frequently hides web search behind multiple clicks and taps, and aggressively A/B tests interface changes that clearly will result in fewer searches being executed All of this raises the question: how does ChatGPT implement search? What is the cost of the search itself and the extent of chain-of-thought reasoning needed to aggregate and discern the extraordinary number of tokens that need to be ingested by those search results?