Why the simplest desktop agent abstraction wins

https://www.bytebot.ai/blog/designing-bytebot-why-the-simplest-desktop-agent-abstraction-wins

by atupem • 1 year ago

43 16 1 year ago

What are the biggest issues that the agent faces at the moment? I still find these general purpose agents frustrating to use at times because people position it as if it could do anything and then when you give it a reasonably complex task it breaks down.

I guess if someone figured out way to minimize the impact of an error, like a way for it to gracefully handle it without it feeling like too much work, that would fix most of the problems.

atupem5• 1 year ago

Lots of interesting issues:

- The agent has a tool to set it's task to 'completed', 'failed', or 'needs_help', with the last one being a option for human in the loop scenarios. Sometimes the agent gets lazy and says it needs help prematurely.

- Additionally, the agent can create subtasks for itself, either to run immediately, or to schedule in the future. Here it again can call that tool a bit too eagerly, filling duplicate subtasks for a task that involves repetitive work.

- Properly handling super long running tasks, that run for 1+ hours. The context window eventually hits it's limit (this will be addressed this week)

Aside from those top of mind issues, there's a whole bunch of scaffolding issues - filesystem permissions, prompt injection security, i/o support, token cost - lot's to improve!

We're still super early, but already these agents are showing flashes of brilliance, and we're gaining more and more conviction that this is the right form factor

lelanthran3• 1 year ago

We're still super early, but already these agents are showing flashes of brilliance, and we're gaining more and more conviction that this is the right form factor

Slow down cowboy; we're seeing "flashes of brilliance" and "that this is the right form factor" for writing code only!

I'm still waiting for AI/LLM's to be posing a danger to jobs other than those in software development and the arts.

latexr• 1 year ago

showing flashes of brilliance

A “flash” of anything is also called a fluke, or a coincidence. The dumbest moron can have a flash of brilliance on occasion. So could a random word masher. Consistency is what matters.

and we're gaining more and more conviction that this is the right form factor

Are we? Who’s “we”? Because it looks to me like the LLM approach is lacklustre if you care about truth and correctness (which you should) but the people and companies invested don’t really have a better idea and are shoving them down everyone’s throats in pursuit of personal profit.

teruakohatu2• 1 year ago

What is your business model?

lelanthran3• 1 year ago

See my comprehensive reply downthread (it's very long, you cannot miss it).

While I am skeptical due to already having explored this for SMME Line of Business applications, I wish you all the best of luck.

My approach is to simply build a new system from the ground up that can take advantage of structured IO.

[EDIT: send me a message with a link to a post about your product (or this blog), I'll connect with you on linked-in and share your post with my network, meager though it may be]

clbrmbr• 1 year ago

Does anyone have experience getting agents to understand terminal applications? Like, in general an arbitrary ncurses application.

A more specific case I’ve struggled with is output from a long-running program like ping. You’ve got to know when to terminate.

soulofmischief• 1 year ago

I wrote a terminal-based falling sand game in rust and incrementally fed the entire screen output to a multimodal LLM (for better generalization) and also got it to attempt to generate interesting initial conditions by spitting out raw characters.

noman-land• 1 year ago

Instead of telling the agent to wait for something like ping, have it write a script to do it and then have it run the script.

Why the simplest desktop agent abstraction wins

Related Stories