Matthaus Krzykowski

@matthausk.bsky.social

CEO/co-founder dltHub, the makers of OSS Python library dlt. At the intersection of single node compute, open storage, Python/in-memory & some others

Berlin, it’s meetup time! Join us for the dltHub Community Meetup, an evening of real-world demos, lessons learned, and conversations with builders. 📍 Rosebud, Berlin 📆 Feb 17 | 18:00 – 21:00 Curious about what we’re building at dltHub? Come by 👋

dltHub Community Meetup in Berlin with Cognee, Untitled Data Company, Gemma Analytics & Babbel · Luma

Join us for the dltHub Community Meetup in Berlin. This evening is for curious minds who want to learn more about what we’re building at dltHub. We’ll share a…

luma.com

TLDR; we launched on ProductHunt! After months packed with community-driven features our AI memory tool @cognee.bsky.social has evolved to new heights. Finally AI agents meet the memory they deserve - structured, accurate, and reliable - in 5 lines of code.

🚀 In the last 6 months we have seen early adopters in the dlt community take advantage of AI code editors such as Cursor. Check our initial assistants and building blocks for custom workflows such as Anthropic MCP servers for dlt on the recently launched hub.continue.dev/dlthub from @continue.dev 🚀

dlthub (dltHub)

data load tool (dlt) is an open source Python library that makes data loading easy 🛠️

hub.continue.dev

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We at dltHub are releasing the initial two features of dlt+, our framework for running dlt in production, in early access: 👉dlt+ Project: A declarative YAML collaboration point for teams 👉dlt+ Cache: A database-like compute layer for developing, testing & running transformations

kinda admire the boldness of a blog on 'robust generative AI agents' w/no actual solutions to make these robust Lots of monitoring & observability to quantify how flaky your system is, but still just a "prompt and pray" approach to having LLMs execute tasks aws.amazon.com/blogs/machin...

Best practices for building robust generative AI applications with Amazon Bedrock Agents – Part 2 | Amazon Web Services

In this post, we dive into the architectural considerations and development lifecycle practices that can help you build robust, scalable, and secure intelligent agents.

aws.amazon.com

Was pretty exhausted emotionally by a great work week in SF. Looking for 2h at the creativity inside MoMa NYC today (including seeing studying this Rauschenberg in person after only seeing digital + print copies of it before) was all I needed to revitalise.

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