Artem

I ask you to look in the mirror and ask yourself – what are you doing in this time of great challenge?

My claw talks to me in beltalowda and it's glorious

@thsottiaux It's not shareable with the team

What are we obviously not getting right with Codex?

@nealagarwal haha so good

Introducing Cursor Camp, a website to hang out with other cursors. Out now, enjoy :)

It's like we dug up a powerful alien artifact and society is humping it while taking selfies

@JeffBezos 🔥🔥🔥

Lets go @lukaschmiell

One to many digital employee is the next wave of adoption just wait for it

Reset my cell state, make no mistakes nature.com/articles/s4158…

a few weeks ago someone called work without AI “tradwork” and i can’t stop thinking about it

the quality of ai harness is the only moat

People don't seem to realize that they can create their own custom end-to-end harnesses in Cursor w sub-agents and hooks

@vanadium23 cursor.com/blog/composer-2

@codesfaster nah, too messy

composer 1.5 is holding up surprisingly well for a model released 6+ months ago

@vanadium23 wait for it :)

Wow

The real north star for the upcoming age of abundance: to make both labor and intelligence too cheap to meter

@nem035 U really need to try bugbot - it’s great!

Building AI code reviewers is useful, but it does not solve the core problem. AI systems still make major mistakes. Having one AI review another AI’s work does not remove that problem. It only pushes it further down the process. This may catch some issues, but it does not remove the need for human judgment. The system itself is still not reliable enough to trust on its own. A common response is that humans also make serious mistakes. That is true. Humans break things all the time. But humans also have agency. When something goes wrong, they can notice it, reason about what is happening, and change course. They can improvise and respond without being prompted. We do not need to engineer humans into a system to monitor and fix problems. Humans adapt, react, and take responsibility. If an AI creates a problem, it does nothing unless something asks it to. If people still have to find and fix the mistakes, then the system is not truly automating the work. We are only shifting the work around. Even if AI were close to perfect at execution, we still do not know how to engineer systems that give it the right context at the right time and at the right cost. The real bottleneck to large scale AI code generation is not review. It is reliability. AI needs to produce code that is correct often enough that humans no longer have to check every important change. It also needs to be integrated into systems in a way that allows it to detect and respond to problems. Reliability also takes time to prove. We trust airplanes because they earned that trust through decades of consistent performance. AI systems have not had that kind of time yet, and longevity cannot be rushed. So cost needs to go down and reliability needs to go up before we even get a glimpse of the digital panacea many people are imagining.

New F1 is up to a shaky start. I don’t remember the last time cars would just fail drivers one by one.

zirp is coming back, i can feel it

@steipete it simply doesnt work lol x.com/codesfaster/st…

it’s a good model. the coding specific jump is more in line what we had in 5.0 to 5.1; but it’s now unified and smarter on everything else, writes better docs, is a better general purpose agent and is overall more pleasant to use.