Kostas Pardalis

Kostas Pardalis

@cpard.bsky.social

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

1.1K followers23 following79 posts

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

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). 

Kostas Pardalis reposted

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.

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6/7 Performance & DX Rust optimizations plus leaner default configs deliver performance gains and a frictionless setup experience. so you spend less time tuning and more time building.

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.

View full thread

4/7 Composable Pipelines Save intermediate DataFrames as persistent views in the fenic catalog. Reuse and chain complex transformations across jobs without rewriting or rerunning upstream logic, accelerating iteration and collaboration.

5/7 New Functions & Models Access built-in summarization, new semantic APIs, and multiple embedding providers (e.g. Cohere, Google Gemini) out of the box. This broadens your toolkit, so you can prototype and productionize a wider range of AI workflows quickly.

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.

2/7 Robust Fuzzy Text Matching Ground LLM outputs against your existing data: record linkage, deduplication, and typo-tolerant joins become first-class operations. This improves precision in extraction pipelines and slashes downstream error rates.

3/7 Typed Semantics Define your output schema once with Pydantic and get back validated, strongly typed results. This enforces consistency, surfaces errors early, and eliminates manual parsing of LLM responses.

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

Kostas Pardalis reposted

@steveklabnik.com Joined us on an episode where we discussed about Why: • Cargo & friendly errors > benchmarks • 6-week releases > years-long committees • How Rust united Ruby, FP & C++ devs • Next-gen picks and many more! Check the episode on your favorite platform!

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.

Kostas Pardalis reposted

The value proposition of formal methods becomes clear when dealing with complex distributed transactions involving multiple independent services. Jayaprabhakar(JP) Kadarkarai from ep.5

Kostas Pardalis reposted

User experience and developer interaction with complex data abstractions remain a significant challenge beyond the technical integration. Nikhil Simha & Varant Zanoyan from ep.2

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

Kostas Pardalis reposted

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

lu.maPeninsula 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…

Kostas Pardalis reposted

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

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

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

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/...

The problem is that data engineering is not web development and SQL is not JavaScript. We do need many more people to enter the market but the tooling is not there yet. DBT et.al. tried but wasn't enough. That's a good thing, there's plenty of opportunities out there.

Kostas Pardalis reposted

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.'

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

techontherocks.showTech on the Rocks | From Functions to Full Applications: How Serverless Evolved Beyond AWS Lambda with Nitzan ShapiraIn 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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