Vessel

The rising tide lifts all boats And therefore we've rebranded to Vessel Same product and thesis but the name Vessel is more true to our mission: to build the most optimal craft to traverse the rising tide, no matter which model is cresting this week

Investment Banking is an incredible place to start your career It’s a terrible job while you’re in it because it’s really hard and extremely demanding, but man do you learn a lot really really quickly

@staysaasy But bro I have 265 openclaws running at all times.

Dumbest mistake I’ve seem many smart people make is thinking they can replace somebody else’s product with 1/10th the team size. Almost never, ever happens. You can redefine a category with less people. But people ALWAYS overestimate their ability to win a footrace against much more resourcing (no matter how big and slow they seem).

@Jaytel They cooked ngl

I'd have never guessed that I'm back to using Cursor

@__BOMO @nikillinit This and a yap

@nikillinit Not sure why you’d commit to using one model provider. Seems silly

what happens to all of the companies applications for enterprises on top of the foundation models? Genuinely trying to understand when an enterprise would choose the foundation models straight vs. a company that offers a specific solution using multiple models underneath

@zeeg 🫪🫪🫪

imagine if LLM vendors focused on being infra instead of trying to build (mediocre) versions of all of their customers products

@staysaasy Free failures to learn from if you can

I think that this is very true about competitors' external positioning and product launch PR, but that things tend to go better if you actually pay very close attention to empirical observations of competitors (e.g. win-rates, sales strategies that work/don't work, market intel)

What’s holding you back right now? Product? Recruiting? Competition? Token limits?

@edzitron Doesn’t mean anything

Who gives a shit

@atelicinvest Quality control is the bottleneck

Some stupid late night thought: We assume that as AI gets smarter and smarter things will get faster and faster - and in many areas this will be true. But there's an unexpected source of barrier - from my experience, as AI gets smarter - humans become too dumb to understand / interpret AI's suggestions and solutions. Especially since a lot of use is in areas that they are not fully capable in. Obviously, if AI were 'perfect' this wouldn't be a problem - but it's not - and so the effort required to properly check / implement goes up. it's an interesting conundrum.

If anything, AI might have killed VCs

Anthropic killed this Codex killed that Bro shut the hell up

@dbreunig Walled garden approach!!!

OpenAI winding down fine tuning is an interesting development and one to watch. On one hand, model maximalists will argue the largest models keep getting better at more things, so the need to adjust the weights of them is less necessary. On the other hand, the big labs keep pushing their models to a handful of use cases while training their harness designs into the model, rendering them less generalized. There's an argument _this is fine_, because coding and reasoning abilities will solve most other problems. But what we end up with are models build for their own harnesses. @badlogicgames was wrestling with Claude in the OSS Pi harness this week, trying to wrangle out specific in-harness behaviors, with Claude fighting him every step of the way. If this continues, there's a world where 3rd party harnesses become less valuable when used with frontier lab models because the 1st party harness behavior is already _baked in_. And there's no longer a fine tuning escape hatch to generalize this behavior away. Will then frontier models resemble appliances, not general platforms? With their harness trained in and no ability to adjust it? This might make application building easier for some enterprises, but the trade off is lock in.

Harvey called it quits on their own models Heard Rogo is doing something similar They’re both now betting on workflows, realizing that the race against the labs to build the best model is fruitless But it’s confusing that Anthropic is investing so heavily in UI

@staysaasy @growintfast @elonmusk Probably both

@growintfast @elonmusk legit seems like the only person in it that mentioned anything about mission at all ever. So he’s either pure of spirit or the best marketer by far.

You ever sit back and realize 0.0% of this OAI/Elon case has any evidence anywhere that these folks are pursuing AI from a virtuous good-of-humanity perspective. There’s no diary entry like “May 2: we’re trying to literally cure cancer here.” There’s no text like “Dude let’s squash all of this we’re in the singularity anyway and humanity is about to enter the garden of Eden.”

As someone who studied computer science in high school and college, but had no professional SWE experience, agentic coding has been an insane tool for me Recently though I’ve started to want to write code myself to make sure I know 100% of what is going on

@edzitron Obviously

So…lying?

@levie Space exploration is so close

For everything we’ve seen about agents so far, it’s clear that they will make it far easier for people to get into previously extremely complicated fields. That will most certainly mean far more people will build software, explore creative work, research spaces they couldn’t do before, and so on. Yet, equally, we’ve seen that people with experience in every one of those fields have a huge edge with the right judgment and historical context to leverage these tools in ways that exceed the output of the novices (if they choose to). They know when the agents are making catastrophic mistakes, can give the agents the right context to do the job better than they otherwise would have, and so on. The combination of these two facts essentially means that we will continue to get the same lift as we’ve seen in any other technological revolution. More democratization, but similarly greater output from the experts. This then makes the experts continue to be in higher demand because over time our expectation for what we can get out of any field will just go up. This is going to be true in essentially every important field. You’ll trust a lawyer using an agent for legal advice over someone who’s never had to experience how well a contract holds up. You’ll trust an engineer developing and running software over someone who’s never seen a production system. You’ll rely on the important instincts of a designer using agents over the average prompter. The quality and volume of output we expect from these functions will certainly go up meaningfully, but the person with experience will always have a leg up, which is why the jobs don’t go away.

@leeschmidt123 Hahahahaha

Met a guy who’s a partner at one of the largest consulting firms in the US and globally. He started talking about AI coding. What followed was a stream of nonsensical AI and coding related buzz words. Recommended “forking claude” (whatever that means), and “use github workflows for everything so the agents can talk to each other” (also whatever that means). And it only went downhill from there. Large businesses pay these people millions of dollars. So much waste and cluelessness out there it’s insane.

@CWood_sdf @JFPuget 😂😂😂

i love how people are saying "if we write a sufficiently detailed specification, the agent can write all our code" do you know what writing a sufficiently detailed specification that deterministically maps to what a computer's actions is? it's coding