What it feels like to work with Mythos

root_axis

I just can't stand this type of fawning language.

asdK120

Mollick runs the Generative AI Lab at Wharton, with all the corporate sponsors. He is a professor but sadly also an AI shill. He should switch to advertising washing power.

382hi

I think Qwen 3.7-Plus is better at reasoning than Mythos, and I've used both for quite a while.

the_doctah

More Mythos Marketing.

gopalv

> It worked for nine and a half hours. > Again, it wasn’t perfect. As an expert, I was able to spot some errors and omissions (some as a result of the design I had asked for) that I had the AI correct That's the bit that stuck out to me - that's longer than I would expect to work on a problem in a day or even expect to go back & fix the output of something that has a core reward loop of hours. My customers are currently clamoring to push down my agent response times from 85 seconds down to below the 20s mark. At the same time, it is very dissonant to see the industry heading towards hour+ long workflows with an agent.

recursivedoubts

would it be possible for mythos to make the space bar scroll the pages on your website properly?

JumpCrisscross

Anecdote: I fed Fable some models I’ve been hand verifying (basically, I sketch out a scenario for Opus to model, it builds it, I ask it to show me the math, I correct it, we iterate like this, then I double check its code to make sure the math matches the model logic). Fable found almost every error I found, and then had some interesting suggestions for additional variables. It also burned through my usage quota like a late-90s Hummer.

theturtletalks

This is what he built: https://isochronic-passage-chart.netlify.app/ Doesn’t work too well on mobile but looks interesting

selfawareMammal

What are people working on that they see such a substantial difference between Mythos and Opus? I'd say I'm working with advanced stuff and more than often Deepseek is even more than enough. Why is everybody a genius in here?

thepasch

What it feels like to work with Fable: > Switched to Opus 4.8: Fable 5 has safety measures that flag messages on most cybersecurity or biology topics. They may flag safe, normal content as well. These measures let us bring you Mythos-level capability in other areas sooner, and we're working to refine them. Send feedback or learn more.

eithed

What I find fascinating that there is so little substance in this article about the quality of produced code and the medium. Is the code documented and tested? Is it understandable and extendable? Is it secure? What language, framework, database was used? Author mentions judgement and taste - well, is the code tasteful? Will the model rearchitecture the entire thing if I ask it to add new functionality, spending another 9.5h in tokens? I assume that the research part is domain knowledge = how different types of travel translate to time making it presentable; how did the author verify this? These questions are even not about AI: if I were to give money to a human agency and were given something they tell me works, I would ask the same questions. If I did not know how to evaluate, I would hire people that do. With LLMs the verification part is what bothers me the most.

zuzululu

> First, how good is Fable? In experiment after experiment I conducted, it outperformed basically every other public model I have used by a considerable margin. What makes me excited is that GPT 5.6 (its actually GPT 6) is going to be crazy

mohsen1

I have been using it for less than an hour so take this with a grain of salt of being excited for the new tech. In a project like mine ( https://github.com/tsz-org/tsz ) I am constantly frustrated that models were not doing enough research and were not taking into account other situations. Again and again models would produce code that would fix one thing and break 2 other tests that were "unrelated". With Fable it seems like tasks are taking much longer (I have not seen a pull request from Fable sessions yet) but reading the transcription of those sessions I can see how it is doing the right thing by not leaving any stone unturned. As the article says, it's hard to communicate this "feeling" about models because it is very project specific but I thought I share

zb3

Was the condition of being granted early access to this castrated model writing a post praising it?

Aperocky

> This is a map that shows the distance you can travel in a given length of time, and the first one was created in 1881 showing travel times from London. The first item on the article, the first thing it showed, was wrong though. It is 100% faster to go from London to New York in 1881 than Volgagrad. Or any of the Russian hinterland colored green or Turkey or Egypt.

ThejaCH

What it feels like to work with Mythos? Feels like am poor

honeycrispy

Reading it, I can't help but feel he's being paid to write this. Or maybe he hopes to be paid. The language he uses makes him sound like he's fawning over the lost days of his childhood. Pardon me for being skeptical, but a trillion dollar company running a net-loss is hoping to IPO, and needs to sway public opinion by any means necessary. I would imagine that no dirty marketing scheme is off of the table, even from the self-proclaimed "good guys".

neaden

Man, that poem it made is terrible. Like just incredibly bad. Sure it's neat that software can make an incredibly bad poem but there is enough bad poetry in the world that we don't need it.

ecocentrik

Reading the first few paragraphs of what he calls "the most sophisticated academic social science paper I have yet seen from an AI" does not impress as much as I hoped. "Posterior beliefs about market demand are purely referencedependent: holding dollars raised constant, they track only performance relative to the founder’s self-chosen goal—jumping half a standard deviation at the threshold, responding steeply for the first ten points past it, and flattening thereafter" Humans generally don't verbalize data this way. The summary document is also very fluffy.