I'll be speaking at @ClickHouseDB user conference Open House in London at the end of September. Registrations are now open & I'm very much looking forward to being in 🇬🇧 - clickhouse.com/openhouse/lon…

thank 👏 you 👏 xi 👏 jinping 👏

RT @levelsio: Jesus christ

how awesome would it be if every new table created, every column name change, every column TYPE change is replicated from Postgres to @ClickHouseDB ? WalShadow does all of these, crazy to see users experience this magic. checkout: clickhouse.com/blog/introduc…

me talking to claude in english as a german

S tier shitpost

Based on our experiments, Jev bears big potential for evals ✔️ It is up to 400x cheaper than frontier models, making full scoring of production traces feasible, no more sampling needed, even at huge scale ✔️ It allows for concurrent questions on the same state, where LLMs previously struggled with interaction effects and common wisdom was to not mix evals in the same requests. This makes Jev even cheaper. ✔️ The structure of Jev's output forces thinking in distinct categories during setup, improving the engagement with defining the exact evaluator categories Play around with this demo here: langfuse.com/blog/2026-09-18…

Finally got to record a 15 min overview of what @langfuse is based on an end-to-end example - how it helps build great AI agents/apps - how to continuously improve them with Lanfguse - how the integration works - why langfuse and no closed-source solutions - how agents use it

Fresh walkthrough of @langfuse

On demand compute on @ClickHouseDB is neat. @peignonmel dives in on Oct 7: clickhouse.com/company/event…

Why Jev is interesting for evals > Every question is evaluated in parallel and in isolation against the same state. So adding a fourth question, or a fourteenth, barely changes response time, costs only the tokens of the question itself, and cannot degrade the answers to the others. You can ask speculatively and throw away what you do not need. Fits very nicely to how good evals should work. Let's see what competition will do to this segment (make it even better, cheaper, faster).

🇮🇳 Bangalore - my co-founder @maxdeichmann is bringing @langfuse to India for the first time at @ClickHouseDB Open House conference. He's going to be there sunday-tuesday & would be keen to connect with folks locally, please tag here!

Good read! Most often your users will leave implicit feedback signals (do they accept an edit, copy an output etc) that you can use to infer whether your app provides a good/bad answer. Scalable, free, mostly unbiased

Germans really get around. You'll be in the most isolated place hiking up a mountain most of the locals don't even know about and a German on their 5th vacation of the year will pop out of nowhere

Props to @langfuse for their excellent docs and learning materials! 👏 If you’re trying to wrap your head around concepts like LLM observability, monitoring, and evaluations, these resources are well worth checking out: 🎓 Academy: langfuse.com/academy 🛠️ Workshop: langfuse.com/workshop 📚 Guides: langfuse.com/guides

listen man sometimes you gotta put the manhattan project on hold to sell b2b SaaS

🇫🇷 Speaking at @aiDotEngineer Paris by @MistralAI next week! talk slightly from left field: What Can Economic History Teach Us About the AI Moment? industrial Revolution, printing press, railways, electricity, internet and so on! Wednesday, 17:40 Main Stage

@Waymo is preparing to launch in Berlin?! Hell yessss

same thing here this weekend, german version -- give check24 access, instinct gets car insurance. so bullish

Yesterday, the @tryramp team shared the story of how/why they use @langfuse at OpenHouse New York. When creating software gets cheap, collaborating with tasteful teams at the frontier is what makes Langfuse great.

. Today, we’re taking Postgres replication to the next level. With WalShadow, you can now replicate Postgres to ClickHouse directly from the physical write-ahead log (WAL), without the hassles of logical replication, and with sub-second replication latency. This one is especially personal and honestly, a little bittersweet. We benchmark WalShadow against @PeerDBInc, something @iskakaushik and I founded years ago. PeerDB eventually became the foundation of Postgres CDC for thousands of customers. Seeing a benchmark showing up to 50x lower replication latency than PeerDB creates mixed emotions :)It also makes me incredibly proud. Because this is exactly what we always wanted: to keep pushing Postgres CDC/replication forward. WalShadow takes a different approach. Instead of logical replication, it works directly with the physical WAL, getting us as close to Postgres as possible and enabling replication into ClickHouse in less than a second. Some of our best engineers have spent months working through some very hard problems to make this possible, and I’m incredibly grateful to the team for getting us here. The ambition is the same one we had: build something that thousands of customers can reliably depend on. And, make Postgres + ClickHouse feel less like two databases connected together and more like one deeply integrated stack. Very excited to finally share WalShadow with the world. Give it a try we’d love your feedback! 🚀 clickhouse.com/cloud/postgre…