The latest finding in the LangSmith Signal: Open Models are having a moment.
1 in 3 AI teams ran an open-weights model in April 2026, up from 1 in 5 nine months ago.
The overall number of teams using open weights grew 3x.
We’re seeing newer users choose open models at a higher rate than those who came before.
In addition to data being the moat, isn’t the router / optimization of the LLM router the moat for many of these businesses? Why would a company out-source that kind of data
I have multiple friends that still use https://t.co/lmis90zrKu as their on computer calculator, always was and always will be a beautifully made product
Today we're announcing our Series C funding: $355M at a $4.65B valuation, led by some great investors @generalcatalyst and @Redpoint.
We've had insane growth in the last year, but we're still very early. So proud of the team and what we have built so far!
Personal update: I've joined Anthropic. I think the next few years at the frontier of LLMs will be especially formative. I am very excited to join the team here and get back to R&D. I remain deeply passionate about education and plan to resume my work on it in time.
my prediction is that most of the neolabs will start releasing research previews of various products in the next 6 months
new models with cutting edge research ideas will create hyper specific capabilities that end up crushing generalized benchmarks
lot of interesting ramifications if so
lot of alpha here: the vc-ification of public market trading accounts is definitely here: just need some of these asymmetric bets to work out, which as we've seen can return entire funds