Kostas Pardalis

@cpard.bsky.social

Building https://typedef.ai | host @ https://techontherocks.show | Done some cool stuff with trinodb | ex-RudderStack | previously CEO @ Blendo

fenic 0.4.0 brings fenic and its expressive API for working with data, to agents. With tooling becoming a catalog artifact, MCP servers and toolsets being available with just a cli command you can turn any data set you have into well curated context for your agents. check it out!

typedef@typedef.ai · 11mo ago

fenic 0.4.0 is live: declarative tools for agents, a production-ready MCP server, and direct reads from HuggingFace plus big DX & reliability gains.  Highlights: Declarative tools: define function-calling tools as data (type-safe, reviewable, reusable). 

New episode: chatting with bauplan founders Jacopo Tagliabue and Ciro Greco on shipping AI with real-world data constraints. Why listen 1. Data pipelines determine model effectiveness, far more than most teams admit.

Here's a bit more information on each of the new 🦊 fenic 🦊 features. 1/7 🧵 Dynamic Templating Turn any column struct or array into a live prompt fragment. No more string concatenation hacks. You get per row, data driven prompts with minimal code, boosting relevance and reducing boilerplate.

fenic v0.3.0 is out and it's a release I'm really excited about! Here are a few of the things that this release is introducing. Jinja as a column function Robust Fuzzy Text Matching Full Pydantic support in all semantic operators Persistent views More Functions & Models Perf & DX improvements

Using Jinja templates to dynamically create prompts for semantic filtering in fenic.

Everyone’s heads down on AI these days, but please take a break and soak in some deep systems wisdom from Josh Howards. He’s one of the folks behind R2 at Cloudflare. After all, whatever you build in AI will sit on top of these foundations. check @totrrocks.bsky.social for the episode link.

I had the rare opportunity to sit down and chat with someone who helped shape that story of Splunk, co-founder Erik Swan. There's a lot to learn from him but what inspired me the most is his energy. Even after a success like Splunk, still learning and building listen here @totrrocks.bsky.social

Lakekeeper is an open source data catalog built on the Apache Iceberg REST catalog API. If data infrastructure drives you, check out the project and catch Viktor Kessler's insights on the latest @TotrRocks episode!

We'll be hosting another event at our offices in San Mateo. We want to bring together people who are interested in data and infra, from systems engineers who build data platforms, AI engineers, VCs and everything in between. Connect and have fun while we learn from each other. lu.ma/2hc1qm1v

Peninsula Data Happy Hour · Luma

🔥 An Unmissable Evening of Data & Magic! 🔥 🎉 Back by popular demand, it's time for the March edition of our Peninsula Data Happy Hour! This time we've got…

lu.ma

I always wondered why PG’s text indexing and search is not enough. I finally got some good answers on that and many other questions about search in databases from Phillipe, co-founder and CEO of ParadeDB. Great conversation and many insights on the future of search technologies

Tech on the Rocks@totrrocks.bsky.social · 2y ago

New episode! We talked with Philippe Noël about building ParadeDB, an exciting Elasticsearch alternative built on Postgres that offers fast full-text search and analytics with zero ETL. Search is becoming the primary interface for data-heavy applications - and AI.

Make sure you check the conversation with @davidmytton.social on TotR. He has some amazing stories to tell about observability and why it's so hard, security in a world where AI is turning everyone into a scraper and dev tooling. Check the conversation on your favorite podcast platform!

Tech on the Rocks@totrrocks.bsky.social · 2y ago

Join us at another episode of Tech on the Rocks, this time with @davidmytton.social of Arcjet. We talk about security as code, security in a world of AI and dev tooling. Check the episode here: https://buff.ly/4ggWGeO

The "analytics engineer" is a result of the commoditization of data warehousing. Suddenly we ended up with huge demand and almost non-existent supply of engineers who could build and run that stuff. Yes, zero interests amplified the effect but it wasn't the cause. DBT seized the opportunity.

Chris@chris.blue · 2y ago

New post! I've been ranting that creating a analytics engineer role was mistake. I think now's the time to fix it. Let's merge data engineers and analytics engineers back into one role. materializedview.io/...

I missed the announcement of AWS MSK 'Express' Kafka brokers last week. They 'offer unlimited storage without preprovisioning, eliminating disk-related bottlenecks. Cluster sizing is simpler, requiring only ingress and egress throughput divided by recommended per-broker throughput.'

Next week we'll be co-hosting with the amazing people from Tobiko Data, Data Recce and Wilson Sonsini another Peninsula Data Happy Hour. Join us for an evening of conversations, networking and amazing food and drinks! lu.ma/omfb6f4o

Peninsula Data Happy Hour - 2024 November Edition · Luma

Welcome to the Peninsula Data Happy Hour (our November edition)! Please join us and others from the data community for brews and bites. We'd love to chat all…

lu.ma

Serverless is being used a lot lately with many different meanings. I think there’s a bright future to it but there’s still work to be done on figuring out what’s the right type of “serverless” Nitzan is sharing a lot of wisdom on the topic. It’s worth listening to him. techontherocks.show/7

Tech on the Rocks | From Functions to Full Applications: How Serverless Evolved Beyond AWS Lambda with Nitzan Shapira

In this episode, we chat with Nitzan Shapira, co-founder and former CEO of Epsagon, which was acquired by Cisco in 2021. We explore Nitzan's journey from working in cybersecurity to building an obs...

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