CEO/co-founder @dltHub - Claude/Codex/Cursor-native data engineering

Berlin, Germany
Joined April 2007
Matthäus Krzykowski retweeted
In case SF folks are actually interested in learning from Berlin…
My experience partying all night at Berghain in Berlin made me think of how we're lacking this experience in the San Francisco tech scene. We can literally become the coolest, most tasteful social scene on Earth if we had our version of Berghain, but better. So let's build it. The best aspect of Berhain is how they select who gets in. The club has a vibe and atmosphere, and if you aren't wearing the right clothes or have the right demeanor, you don't get in. That's how you cultivate a tasteful crowd. We can improve on this by only letting in high agency, talented operators in the tech scene who can still pull off dope outfits, so no geeks. SF is in dire need of late night venues, and Berghain goes until 8am. That's a little too crazy for high net worth operators who are changing the world so we could do something like 2am. Berghain also is kinda dark and in a weird building so we'd put the club in a SoMa corporate office that we convert to speakeasy or barcade vibe. Maybe add a quiet area for people to bring their laptops and work? I honestly feel like we're improving on the Berghain form here, especially by swapping out the crowd of weird partiers in inappropriate clothes (or lack there of) with insanely cracked founders and engineers. I'm super stoked about this idea, SF tech could really run the dopest parties on the planet.
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Be like Legora for your agents. Don’t point MCP at raw data. Use dlt + an agentic semantic layer. Legora tried agent + MCP first. It failed four ways: Different answer every run. Re-reads raw data on every question. The agent guesses what your data means. No MCP server, no data.
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Goodbye Seattle, hello San Francisco for the week.
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Meeting dlt community members @dltHub customers at Snowflake World Tour NYC. DM me if you are around and want to meet.
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I have seen early mobile when Europe was in the lead, I have seen early commercialisation of mmp databases (which became "cloud" data warehousing). AI, and especially OSS AI, is the most non Silicon Valley opportunity of my lifetime.
Meet Mistral Large 4, aka Le Chonk. • 1T parameters, natively multimodal. 49B active. It is the best open weights model from US or Europe on aggregated benchmarks. • State-of-the-art on critical workloads, including cyber defense, manufacturing and finance and it surpasses closed frontier models on visual grounding. • Forged in Europe end-to-end and is deployable from Europe via our own Mistral Cloud infrastructure. • Available to all via API today. Working with cybersecurity partners privately. Open weights release end of October.
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snowflake.com/en/world-tour/… Looking forward to the Snowflake World Tour in Stockholm tomorrow. Fun fact: Among the speakers Brocc, Legora, Nordea , Sparebank1 and Volvo Trucks all use dlt (and some are paying customers, too).
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Matthäus Krzykowski retweeted
Vielleicht erschreckt sich der eine oder andere nun doch, was er da überhaupt gewählt hat. Parteiprogramme sollte man eben vorher lesen. dielinke.berlin/fileadmin/do…
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Matthäus Krzykowski retweeted
Everyone has been asking me what I’m up to after the @continuedev acquisition The answer: I wrote a paper with Disintegrator titled *The Superdark Factory: Toward the Full Automation of Software* that was published in Antikythera (MIT Press) today superdark.ai
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Great partnering with @AltinityDB & @grafana on Building AI Applications at Scale in Berlin. Robert Hodges (Altinity) on prepping ClickHouse for AI. Goutham Veeramachaneni (Grafana) on vibe-building with observability baked in. Aashish Nair (@dltHub ) on ingesting agent traces. No hype - just engineering.
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Matthäus Krzykowski retweeted
Steve Kerr says Roger Federer taught his Warriors team the secret to sustained success wasn’t outworking everyone, it was building a life around your craft you never want to escape from “I’ll tell you a great story about Roger Federer. We were playing in China with the Warriors in 2017. Roger was in Shanghai for the Masters tournament, so we invited him to come speak to the team.” “Draymond Green asked him, ‘How do you sustain success? How have you managed to win majors 20 years after you first won one?’ Everyone was expecting him to say, ‘I work harder than everybody,’ the will, all the clichés.” “Roger Federer says, ‘I get up every morning and I make breakfast for my kids. Then I take them to school and drop them off. Then I go practice tennis for about two hours, and I’ve figured out a really good routine where I don’t destroy my body, but I can get all the work in I need.” “‘Then I go have lunch with my wife. In the evening, we cook dinner together. The kids are all home from school. We ask them about school. There’s so much joy in the house. We put them to bed, and then I put my head on the pillow and go, “Man, that was just a great day.” And I’ve been doing that for 20 years.’” “And it was like, yes. That’s it. That’s the formula. That’s what leads to sustained success. He loves tennis. He loves his family. He loves life. It’s not outworking everybody and banging your head against the wall, ‘I’m going to be better than everybody.’ It’s allowing your natural talent to shine through with a work ethic, with a great family life, with perspective, with peace, with mindfulness.” “It’s perspective. It’s joy. It’s passion. It’s mindfulness. It’s an awareness that we are truly lucky. To get the most out of ourselves, it’s our daily rituals and experiences and love and joy.”
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If you do not have the capacity to build this stack out in house, then you should consider looking into our commercial @dltHub. If you have any questions, we also have a town hall with our product leaders coming up on Wednesday 17h30 pm CET/8h30am PT luma.com/dlt-k91d where we will also discuss our product roadmap
The Modern Data Stack is over, long live the Post-AI Data Stack🫡🤖 I wrote about how technological shifts change what a data team can build, the features of post-AI data stacks, what we've built at @tryramp, and what data teams can learn from @nbcsnl. iandmacomber.com/blog/post-a…
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Dug up one of our first posts at @dltHub - that's Marcin at DuckCon II in Brussels, February '23, right when DuckDB first crossed 1M downloads/month. He came back from Brussels and we switched all of our docs to be DuckDB-first. dlthub.com/blog/duckdb-1M-do… When we look at our numbers for devices loading data into DuckDB via dlt, the curve is wild - a couple hundred a month in 2023 to 93,784 this July, with a sharp kink upward since January. Feels like DuckDB had its agentic moment: the local, credential-free, spin-up-anywhere engine that coding agents and their users want in their local development environment.
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This was fun to watch ! The Lightdash team internally eg runs Attio/Linear dlt pipelines as part of their GTM workflows, uses the @dltHub AI harness and managed infra, their analytics and MotherDuck as the data warehouse.
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Matthäus Krzykowski retweeted
If you use dlt by @dltHub to move data, you can set up the pipeline to save your results into a cloud storage bucket that everything else reads from. Most teams put that bucket on AWS, right next to the pipeline. However, when something reads the data back, AWS charges an egress fee. This could be a @Snowflake query, a @duckdb analysis, or a training job on GPUs. Tigris Data has no egress fees. Write your data once, read it back from anywhere, as many times as you want, for free. Full setup guide: tigrisdata.com/docs/guides/d…
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