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ChatGPT agent: bridging research and action

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Re: ChatGPT agent: bridging research and action

#281

Post by OtherShrezzing »

slg wrote: post #225
Aurornis wrote: post #127

Earlier quoted context omitted.

> how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... This is where the AI hype bites people. A great use of AI in this situation would be to automate the collection and checking of data. Se…

The proper use of these systems is to treat them like an intern or new grad hire. You can give them the work that none of the mid-tier or senior people want to do, thereby speeding up the team. But you will have to review their work thoroughly because there is a good chance they have no idea what they are actually doing. If you give them mission-critical work that demands accuracy or just let them have free rein with…

I’ve never experienced an intern who was remotely as mediocre and incapable of growth as an LLM.

Re: ChatGPT agent: bridging research and action

#282

Post by fragmede »

imiric wrote: post #262
prettyblocks wrote: post #250

Earlier quoted context omitted.

Given how well it seems to be going in those specific areas, it seems like it's more of a regulatory issue than a technological one.

Ah, those pesky regulations that try to prevent road accidents... If it's not a technological limitation, why aren't we seeing self-driving cars in countries with lax regulations? Mexico, Brazil, India, etc. Tesla launched FSD in Mexico earlier this year, but you would think companies would be jumping at the opportunity to launch in markets with less regulation. So this is largely a technological limitation. They hav…

Can you name any of the specific regulations that robot taxi companies are lobbying to get rid of? As long as robotaxis abide by the same rules of the road as humans do, what's the problem? Regulations like you're not allowed to have robotaxis unless you pay me, your local robotaxi commissioner $3/million/year, aren't going to be popular with the populus but unfortunately for them, they don't vote, so I'm sure we'll see holdouts and if multiple companies are in multiple markets and are complaining about the local taxi cab regulatory commision, but there's just so much of the world without robotaxis right now (summer 2025) that I doubt it's anything mure than the technology being brand spanking new.

Re: ChatGPT agent: bridging research and action

#283

Post by Quarrelsome »

chatmasta wrote: post #233
slg wrote: post #225

Earlier quoted context omitted.

The proper use of these systems is to treat them like an intern or new grad hire. You can give them the work that none of the mid-tier or senior people want to do, thereby speeding up the team. But you will have to review their work thoroughly because there is a good chance they have no idea what they are actually doing. If you give them mission-critical work that demands accuracy or just let them have free rein with…

Yeah, people complaining about accuracy of AI-generated code should be examining their code review procedures. It shouldn’t matter if the code was generated by a senior employee, an intern, or an LLM wielded by either of them. If your review process isn’t catching mistakes, then the review process needs to be fixed. This is especially true in open source where contributions aren’t limited to employees who passed a hi…

"Corporate says the review process needs to be relaxed because its preventing our AI agents from checking in their code"

Re: ChatGPT agent: bridging research and action

#284

Post by freeone3000 »

bo1024 wrote: post #271
NortySpock wrote: post #260

Earlier quoted context omitted.

Oh come on, people have been writing code with bad, incomplete, flaky, or absent tests since automated testing was invented (possibly before). It's having a good, useful and reliable test suite that separates the sheep from the goats.* Would you rather play whack-a-mole with regressions and Heisenbugs, or ship features? * (Or you use some absurdly good programing language that is hard to get into knots with. I've bee…

It sounds like you’re saying that good tests are enough to ensure good code even when programmers are unskilled and just rewrite until they pass the tests. I’m very skeptical.

It may not be a provable take, but it’s also not absurd. This is the concept behind modern TDD (as seen in frameworks like cucumber):

Someone with product knowledge writes the tests in a DSL

Someone skilled writes the verbs to make the DSL function correctly

And from there, any amount of skill is irrelevant: either the tests pass, or they fail. One could hook up a markov chain to a javascript sourcebook and eventually get working code out.

Re: ChatGPT agent: bridging research and action

#285

Post by Terretta »

OtherShrezzing wrote: post #281
slg wrote: post #225

Earlier quoted context omitted.

The proper use of these systems is to treat them like an intern or new grad hire. You can give them the work that none of the mid-tier or senior people want to do, thereby speeding up the team. But you will have to review their work thoroughly because there is a good chance they have no idea what they are actually doing. If you give them mission-critical work that demands accuracy or just let them have free rein with…

I’ve never experienced an intern who was remotely as mediocre and incapable of growth as an LLM.

What about a coach's ability for improving instruction?

Re: ChatGPT agent: bridging research and action

#286

Post by SequoiaHope »

chatmasta wrote: post #233
slg wrote: post #225

Earlier quoted context omitted.

The proper use of these systems is to treat them like an intern or new grad hire. You can give them the work that none of the mid-tier or senior people want to do, thereby speeding up the team. But you will have to review their work thoroughly because there is a good chance they have no idea what they are actually doing. If you give them mission-critical work that demands accuracy or just let them have free rein with…

Yeah, people complaining about accuracy of AI-generated code should be examining their code review procedures. It shouldn’t matter if the code was generated by a senior employee, an intern, or an LLM wielded by either of them. If your review process isn’t catching mistakes, then the review process needs to be fixed. This is especially true in open source where contributions aren’t limited to employees who passed a hi…

I can still complain about the added workload of inaccurate code.

Re: ChatGPT agent: bridging research and action

#287

Post by chairmansteve »

twalkz wrote: post #30

The "spreadsheet" example video is kind of funny: guy talks about how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the…

Yes. Any success I have had with LLMs has been by micromanaging them. Lots of very simple instructions, look at the results, correct them if necessary, then next step.

Re: ChatGPT agent: bridging research and action

#288

Post by sponnath »

levocardia wrote: post #93
alach11 wrote: post #14

It's very hard for me to imagine the current level of agents serving a useful purpose in my personal life. If I ask this to plan a date night with my wife this weekend, it needs to consult my calendar to pick the best night, pick a bar and restaurant we like (how would it know?), book a babysitter (can it learn who we use and text them on my behalf?), etc. This is a lot of stuff it has to get right, and it requires a…

Maybe this is the "bitter lesson of agentic decisions": hard things in your life are hard because they involve deeply personal values and complex interpersonal dynamics, not because they are difficult in an operational sense. Calling a restaurant to make a reservation is trivial. Deciding what restaurant to take your wife to for your wedding anniversary is the hard part (Does ChatGPT know that your first date was at…

I would even argue the hard parts of being human don't even need to be automated. Why are we all in a rush to automate everything, including what makes us human?

Re: ChatGPT agent: bridging research and action

#289

Post by [deleted] »

twalkz wrote: post #30

The "spreadsheet" example video is kind of funny: guy talks about how it normally takes him 4 to 8 hours to put together complicated, data-heavy reports. Now he fires off an agent request, goes to walk his dog, and comes back to a downloadable spreadsheet of dense data, which he pulls up and says "I think it got 98% of the information correct... I just needed to copy / paste a few things. If it can do 90 - 95% of the…

[deleted]

Re: ChatGPT agent: bridging research and action

#290

Post by skywhopper »

AgentMatrixAI wrote: post #47

I'm not so optimistic as someone that works on agents for businesses and creating tools for it. The leap from low 90s to 99% is classic last mile problem for LLM agents. The more generic and spread an agent is (can-do-it-all) the more likely it will fail and disappoint. Can't help but feel many are optimizing happy paths in their demos and hiding the true reality. Doesn't mean there isn't a place for agents but rathe…

Not even well-optimized. The demos in the related sit-down chat livestream video showed an every-baseball-park-trip planner report that drew a map with seemingly random lines that missed the east coast entirely, leapt into the Gulf of Mexico, and was generally complete nonsense. This was a pre-recorded demo being live-streamed with Sam Altman in the room, and that’s what they chose to show.
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