The chatbot is only a weird, limited first-generation interface that works well for a narrow set of tasks and people, not a sufficient product form on its own — most use cases need dedicated tooling, configuration, and interface design built by people other than the end users.
Evans argues the chatbot is a crude v1 interface, not the final product — most real use cases require dedicated tooling, data setup, and interface design that the chatbot format alone doesn't provide. ✦ AI generated
Benedict Evans · a16z Podcast · 2026-06-08 · original ↗
starts at this moment · 18:55
“You mentioned the prediction of you don't think foundation models are are the product you think it'll move up. Explain that that that the re the reasoning there there a bit and what that could look like.”
the chatbot itself is like a kind of a weird limited v1 UI and there's some things and some people and some kind of task where it works really well but there are most of the others you need a bunch of other stuff you need tooling and it needs to be set up right. It needs to have the right data and it needs to be configured and controlled.
verbatim transcript · starts at 18:55
18:55works really well but there are most of the others you need a bunch of other stuff you need tooling and it needs to be set up right. It needs to have the right data and it needs to be configured and controlled and have the right user interface and people need to have kind of sat down and thought about how this should work because generally people who are good at using the tool and doing the
19:15job that needs the tool are not the same people who are good at deciding what the tool should be. So you know people who are really really good at you know designing print publications are not the people who should create and design. That's a different set of skills [snorts] and you know people who are really really good at doing financial advice are not the right people to
19:34design Turboax. Those are different people with different skills. So um and you have kind of groping around the middle of this. So you now have you know Claude for this, Claude for that and you have skills and so on. To me this is kind of like well one question is well who builds the skill? Another question is like well you know that seems to be a bit like what you get if you do file new
19:55in Excel like these are templates and they'll take you so far but a certain point you know people outgrow the templates. Um there's a slide in my presentation which is a quote from that somebody said to me on Twitter years ago you said they were a consultant and half of the jobs were telling people who used Excel to use a database and the other half were telling people who used a
20:09database to use Excel. So there's this kind of fuzzy swirly place of like do you need dedicated software? Do you need horizontal software? Do you need vertical software? But you can't just do everything in Excel. There's always, you know, you know, we've all like seen the department that [clears throat] runs along on a 10 megel file. Now, I run my business in numbers, but on a spreadsheet, but like there's a certain
20:28point where like you outgrow that. Um, and so following that on, well, can the model labs build all of that? Well, of course not. No more than like Microsoft or Apple could build every Windows app or every iPhone app. So then, do the model labs have leverage? Are they are they are they Windows? Are they iOS? And again, well, is there a network effect? Like if you're a law firm right now and
20:47you buy a piece of software like you know do the C all the pieces of enterprise software that A6Z is invested in um how often does like the law firm or the manufacturing company or the bank say oh well does this use claude or does it use or open AAI because we we standardize on claude well no that's not how it works anymore than worked like that for cloud like you didn't say well