Build AI apps around human review and adjustable autonomy

Transcript

Transcribed by machine (Whisper) from the episode’s audio, so a word may be off here and there.

1. 18:23

   just some of the things that I thought were interesting for this talk. The first thing I'm kind of excited about is what I would call partial autonomy apps. So for example, let's work with the example of coding. You can certainly go to ChatGPT directly and you can start copy-pasting code around and copy-pasting bug reports and stuff around and getting code and copy-pasting everything around. Why would you do that? Why would you go directly to the operating system? It makes a lot more sense to have an app dedicated for this.

2. 18:49

   And so I think many of you use cursor. I do as well. and cursor is kind of like the thing you want instead. You don't want to just directly go to the chat CPT. And I think cursor is a very good example of an early LLM app that has a bunch of properties that I think are useful across all the LLM apps. So in particular, you will notice that we have a traditional interface that allows a human to go in and do all the work manually, just as before.

3. 19:15

   But in addition to that, we now have this LLM integration that allows us to go in bigger chunks. And so some of the properties of LLM apps that I think are shared and useful, to point out. Number one, the LLMs basically do a ton of the context management. Number two, they orchestrate multiple calls to LLMs, right? So in the case of Cursor, there's under the hood embedding models for all your files, the actual chat models, models that apply diffs to the code, and this is all orchestrated for you.

4. 19:43

   A really big one that I think also may be not fully appreciated always is application-specific GUI and the importance of it. because you don't just want to talk to the operating system directly in text. Text is very hard to read, interpret, understand, and also, like, you don't want to take... Some of these actions natively in text. So it's much better to just see a diff as like red and green change and you can see what's being added and subtracted.

5. 20:08

   It's much easier to just do command Y to accept or command N to reject. I shouldn't have to type it in text, right? So GUI allows a human to audit the work of these fallible systems and to go faster. I'm going to come back to this point a little bit later as well. And the last kind of feature I want to point out is that there's what I call the autonomy slider. So for example, in cursor, you can just do tap completion.

6. 20:29

   you're mostly in charge. You can select a chunk of code and command K to change just that chunk of code. You can do command L to change the entire file, or you can do command I, which just, you know, let a rip do whatever you want in the entire repo. And that's the sort of full autonomy agentic version. And so you are in charge of the autonomy slider, and depending on the complexity of the task at hand, you can tune the amount of autonomy that you're willing to give up for that task.

7. 20:56

   Maybe to show one more example of a fairly successful LLM app, perplexity. It also has very similar features to what I've just pointed out in cursor. It packages up a lot of the information. It orchestrates multiple LLMs. It's got a GUI that allows you to audit some of its work. So, for example, it will cite sources and you can imagine inspecting them. And it's got an autonomy slider. You can either just do a quick search or you can do research or you can do deep research and come back ten minutes later.

8. 21:24

   So this is all just varying levels of autonomy that you give up to the tool. So I guess my question is, I feel like a lot of software will become partially autonomous. And I'm trying to think through, like, what does that look like? And for many of you who maintain products and services, how are you going to make your products and services partially autonomous? Can an LLM see everything that a human can see?

9. 21:43

   Can an LLM act in all the ways that a human could act? And can humans supervise and stay in the loop of this activity? Because, again, these are fallible systems that aren't yet perfect. And what does a diff look like in Photoshop or something like that? You know and also a lot of the traditional software right now it has all these switches and all this kind of stuff That's all designed for human all of this has to change and become accessible to LLM's So one thing I want to stress with a lot of these LLM apps that I'm not sure it gets as much attention as it should is We're now kind of like cooperating with AIs and usually they are doing the generation and we as humans are doing the verification It is in our interest to make this loop go as fast as possible so we're getting a lot of work done.

10. 22:26

    There are two major ways that I think this can be done. Number one, you can speed up verification a lot, and I think GUIs, for example, are extremely important to this because a GUI utilizes your computer vision GPU in all of our head. Reading text is effortful, and it's not fun, but looking at stuff is fun, and it's just kind of like a highway to your brain. So I think GUIs are very useful for auditing systems and visual representations in general.

11. 22:52

    And number two I would say is we have to keep the AI on the leash. I think a lot of people are getting way overexcited with AI agents, and it's not useful to me to get a diff of 1,000 lines of code to my repo. Like, I have to, I'm still the bottleneck, right? Even though that 1,000 lines come out instantly, I have to make sure that this thing is not introducing bugs. It's just like, and that it's doing the correct thing, right?

12. 23:16

    And that there's no security issues and so on. So I think that, yeah, basically, we have to sort of like, it's in our interest to make the flow of these two go very, very fast, and we have to somehow keep the AI on the leash because it gets way too overreactive. It's kind of like this. This is how I feel when I do AI-assisted coding. If I'm just by coding, everything is nice and great,