$TRI Thomson Reuters Tape Reports
Per Ticker.id: $TRI Thomson Reuters Tape Reports — 2 podcast mentions across 2 podcasts (30 days), latest 2026-08-26 10:00 UTC.
And there was this huge panic and all of a sudden Thomson Reuters and a bunch of other sort of, uh, you know, big legal names traded down dramatically. But those were really just prompts. And there was a lot of discussion about if labs were going to integrate, vertically integrate up into the application layer. Instead, we've seen the very opposite, which is yes, they are vertically integrating, but they're vertically integrating down into inference and compute. It's actually logical now in hindsight because the workloads for inference are very homogeneous. So you can build enormous scale in one part of the value chain. Whereas when you think about the application layer, you know, you've got so many idiosyncrasies and unique needs in terms of pricing, packaging, sort of productization, how the market wants to buy. So it's actually a much more challenging and OpEx-heavy proposition to move into the application layer versus moving down into the inference layer. And this is the point I alluded to earlier, which is sort of this discussion of model commoditization. You know, if you use the models every day, which I do, I sort of hold myself to a standard of making something either small or big with every model that comes out. You, you start to appreciate the fact that these things are, are not commodities, that they have comparative advantage at a domain level. So a great example is OpenAI with their new, um, GPT models are just so, so good at knowledge work. The harness is also very well set up for knowledge work. You know, if you've used the ChatGPT desktop app, you know what I mean. If you haven't, please install it. It's very, very cool and interesting, and it's the perfect sort of, when I say harness, I kind of mean kind of product container, like a browser. Um, it's the perfect product container to do spreadsheets and slide presentations and written documents and all of that type of work. If you look at Claude Code, which many of you I'm sure have used, it's just so oriented towards software engineering. You know, it's in a terminal UI, everything from the small design decisions to the areas in which it specializes, like code planning and code testing is oriented towards the software engineer.
Anish Acharya — The a16z Show · The State of AI: Macro, Apps, and Consumer · 2026-08-26