iiinova — where your digital self keeps evolving

Adrian Brudaru @datateam.bsky.social · 06/07/2026

AI writing pipelines is cool. AI remembering the entire workflow is better. dltHub Pro carries context from ingestion to deployment to maintenance instead of starting over every step. Try it: dlthub.com/products/dlthub

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Adrian Brudaru @datateam.bsky.social · 25/06/2026

Text-to-SQL doesn't break because models can't write SQL, it breaks because they don't know what your data means. An agent can return valid SQL and still be wrong, and a clean wrong number looks just as trustworthy as a right one.

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Adrian Brudaru @datateam.bsky.social · 24/06/2026

Human in the loop shouldn't mean copy-pasting context into an agent every 5 minutes. It should mean judgment, not errands. If your agent needs a Rube Goldberg machine of prompts, tabs, and slack messages, the problem isn't human. It's missing context. dlthub.com/blog/context

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Adrian Brudaru @datateam.bsky.social · 18/06/2026

91% of the 81,000 new dlt pipelines shipped in January 2026 were built by agents. The bottleneck in data engineering is no longer implementation, it's meaning.

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Adrian Brudaru @datateam.bsky.social · 09/06/2026

How much data can $1 of compute move? We benchmarked dltHub on a small worker (2 vCPU / 4 GB) loading into BigQuery: Parquet: ~170 GB Postgres: ~65 GB JSON: ~4.6 GB REST: whatever the API allows Methodology + results ↓ dlthub.com/blog/benchmark-dlthub

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Adrian Brudaru @datateam.bsky.social · 14/05/2026

Building pipelines with AI usually means losing context between tools. dltHub AI Workbench runs the full 12-step workflow as a continuous session, schemas, incrementals, traces, transformations, and notebooks share context across the stack. dlthub.com/blog/agentic-data-engine…

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Adrian Brudaru @datateam.bsky.social · 30/04/2026

We’re excited to share that Violetta Mishechkina will be speaking at GOSIM Paris 🇫🇷 Invited by probabl.ai to join the “Own Your Data Science and AI” workshop. 🎤 From Agent Traces to Analytics Agents generate code, text, telemetry, yet most teams still rely on stale datasets.

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Adrian Brudaru @datateam.bsky.social · 24/04/2026

1/ dlt is now available as a Snowflake Native App. Replicate MSSQL, MySQL & PostgreSQL → Snowflake, without leaving Snowflake. Create, schedule, and monitor pipelines from the Snowflake UI. No external orchestrator. app.snowflake.com/marketplace/listi…

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Adrian Brudaru @datateam.bsky.social · 03/04/2026

Tasman Analytics (20-person consultancy, enterprise clients) went from 2 weeks to scope an API connector → 20 minutes with dltHub Pro. But speed isn’t the story. The real question is: what happens after the code runs?

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Adrian Brudaru @datateam.bsky.social · 02/04/2026

Most AI coding tools stop at “here’s your code.” But getting pipelines into production, and trusting them there, is the hard part. We built a deployment toolkit that closes that gap 🧵

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Adrian Brudaru @datateam.bsky.social · 31/03/2026

Most teams still build connectors from scratch, one at a time. Different patterns. Different implementations. Accumulating tech debt. What if you built the system instead? We just released dlt Skills, a pipeline factory powered by Claude. 👇

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Adrian Brudaru @datateam.bsky.social · 26/03/2026

The craziest part of the new dltHub AI release? The MCP integration. Asked Claude Code for an OpenAI pipeline -> it searches the dlt context -> scaffolds the exact code with schema & incremental loading. No more starting from scratch. dlthub.com/blog/ai-workbench

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Adrian Brudaru @datateam.bsky.social · 24/03/2026

Before anything goes to production, the agent: – converts dev → prod workspace – removes dev artifacts – pins dependencies – validates credentials (without reading them) Then deploys, monitors, and fixes if needed.

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Adrian Brudaru @datateam.bsky.social · 24/03/2026

Once data is loaded, you don’t switch tools. The agent can: – validate row counts, keys, timestamps – inspect nested data – generate queries – build dashboards (via @marimo.io) The feedback loop goes from days → minutes. (validation in action 👇)

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Adrian Brudaru @datateam.bsky.social · 24/03/2026

Start with a prompt: "write a dlt pipeline for OpenAI models" The agent uses an MCP server to pull API context (9,700+ configs at dlthub.com/context) and scaffolds a full pipeline: – auth – pagination – schema – incremental loading Production-ready from the first run. (how it looks 👇)

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Adrian Brudaru @datateam.bsky.social · 19/03/2026

Curious what people here are actually using for AI coding 👀 Copilot? Cursor? Claude Code? We put together a super short (1-min) survey. 👉 dlthub.notion.site/3039fb8e23cf8048…

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Adrian Brudaru @datateam.bsky.social · 15/03/2026

❄️ Module 2 is live in our course dlt + Snowflake Learn how to run dlt pipelines inside Snowflake using Snowpark Container Services (SPCS), enabling native execution and scheduling with no external infrastructure required. Continue the course: dlthub.learnworlds.com/course/dlt-s… ↓

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Adrian Brudaru @datateam.bsky.social · 13/03/2026

Small data teams deserve better tools. We’re opening early design partnerships for solo and small data teams to try dltHub Pro before launch. Early access, influence the roadmap, and an early-bird discount. dlthub.com/solutions/for-small-data…

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Adrian Brudaru @datateam.bsky.social · 08/03/2026

Spring brings good things and more than just flowers. 🌸 ❄️ Catch up on Module 1 of our dlt + Snowflake course before Module 2 drops next week! Learn nested data normalization, schema evolution, incremental loading, and merge strategies (upsert, SCD2), all in plain Python.

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Adrian Brudaru @datateam.bsky.social · 05/03/2026

Tasman.ai runs data engineering projects for mid-market and enterprise clients. Their biggest challenge? Scoping. Every new client meant figuring out which APIs to connect, how long it would take, and what the data actually looked like, often before seeing a single row.

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Adrian Brudaru @datateam.bsky.social · 22/02/2026

The engine behind the insights: dlt → automated ingestion + schema evolution dbt → reproducible SQL transformations Metabase API → BI-as-code A declarative, portable pipeline from source to visualization. Full breakdown: dlthub.com/blog/ufc-analyser-dlt-db…

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Adrian Brudaru @datateam.bsky.social · 22/02/2026

Who is the UFC GOAT? 🥊📊 We turned that curiosity into a full-stack pipeline analyzing 30+ years of UFC fights. Everything programmatic, even dashboard creation via API. Production-grade insights. Full traceability. Zero manual overhead.

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Adrian Brudaru @datateam.bsky.social · 16/02/2026

Stack: dlt → dbt → Metabase Prefect + Scaleway Mon: Validate dlt Tue: Add sources Wed: Move to self-hosted worker Thu: Remove Airbyte Fri: Stabilize + Slack alerting Timeline: 5 days. Enabler: Claude Code. Our blog on moving from Airbyte to dlt 👇 dlthub.com/blog/convert-airbyte

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Adrian Brudaru @datateam.bsky.social · 16/02/2026

Ingestion shouldn’t be a maintenance trap. From Airbyte to dlt in one week. Slides 👇 docs.google.com/presentation/d/e/2P…

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Adrian Brudaru @datateam.bsky.social · 10/02/2026

Production pipelines don’t fail loudly, they drift. Feb 12 · 16:00 CET - Online Hands-on workshop on operating pipelines in production: • schema changes • backfills • CI/CD • long-term reliability Register → community.dlthub.com/workshop-maint…

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Adrian Brudaru @datateam.bsky.social · 09/02/2026

💘 Data Valentine Challenge started today. 5 days. 5 live data sessions with: @datarecce.bsky.social, Greybeam, @databasetycoon.bsky.social, @bauplan.bsky.social Our slot: Wednesday → Pipelines That Don’t Ghost You Feb 9–13 | 9am PT | Online reccehq.com/data-valentine-week-cha…

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Adrian Brudaru @datateam.bsky.social · 09/02/2026

January’s Rising Stars in the dlt ecosystem 👇 Builders are vibe coding pipelines around real-time markets, AI dev platforms, macro data, and more. What’s trending right now:

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Adrian Brudaru @datateam.bsky.social · 15/01/2026

🎤 Call for Speakers Using dlt in your projects? We’re opening the mic to the community for short 10–15 min talks sharing: 🛠️ real use cases 📚 lessons learned If this sounds like you, reach out via the event page. Let’s learn from each other in Paris!

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Adrian Brudaru @datateam.bsky.social · 11/01/2026

Data quality is the vegetables of data engineering: everyone agrees it's important, but nobody wants to implement it. To increase your 𝚟̶𝚎̶𝚐̶𝚎̶𝚝̶𝚊̶𝚋̶𝚕̶𝚎̶ ̶𝚒̶𝚗̶𝚝̶𝚊̶𝚔̶𝚎̶ test coverage, check out these 11 delicious recipes. dlthub.com/blog/practical-data-qual…

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Adrian Brudaru @datateam.bsky.social · 04/01/2026

Most data quality failures happen because checks come too late. dlt + dltHub treat quality as a lifecycle: in-flight checks, safe staging, and production monitoring. Catch issues earlier, fix less and trust your data more. docs: dlthub.com/docs/general-usage/data-…

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Adrian Brudaru @datateam.bsky.social · 25/11/2025

Each integration came together quickly: Stripe with just a token, AWS CUR from S3, and GCP billing straight from BigQuery. This powerful tool stack combined with dlt's connectors, @duckdb.org and @rilldata.com's interactive dashboards, deliver a real-time, consolidated analytics view.

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Adrian Brudaru @datateam.bsky.social · 25/11/2025

At the core is a single incremental pipeline powered by dlt, loading everything into Parquet & DuckDB for fast analysis. Handling auth, pagination, and schema changes, the pipeline remains simple end to end, and because it’s fully pluggable, adding Azure or Cloudflare is easy.

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Adrian Brudaru @datateam.bsky.social · 12/11/2025

Ever launched a data pipeline & wondered what’s happening under the hood? The dlt Workspace Dashboard gives real-time visibility into pipeline state, schemas, live dataset queries, run traces → all in one web app. Built with @marimo.io. Try it now: 👉 dlthub.com/docs/general-usage/dashb…

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Adrian Brudaru @datateam.bsky.social · 17/10/2025

The real AI win isn't superhuman agents, it's scaled mediocrity. Doing less with less at massive scale unlocks tasks that were once uneconomical. The magic is in aggregate value, not perfect outputs. Empower teams with practical AI tools. 🔗 dlthub.com/blog/the-real-ai-win-sca…

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Adrian Brudaru @datateam.bsky.social · 14/10/2025

For years, the most celebrated person on the data team was the one who could write the heroic, last-minute query. We celebrated firefighters. Craftsmen. We built a culture around reacting, not architecting. A leverage trap of our own making.

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Adrian Brudaru @datateam.bsky.social · 14/03/2025

What can we learn from how humans think, to apply that to LLMs? Humans think in steps, ranging from "right now" to "overnight" Here are a couple of examples

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Adrian Brudaru @datateam.bsky.social · 11/03/2025

I put on my robe and wizard hat #dlthub hoodie #dagster hat #databs

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Adrian Brudaru @datateam.bsky.social · 05/12/2024

Our ELT with DLT workshop is back, as a self paced course! So if you wanna learn some durable knowledge this holiday season, sign up for the course! If you submit homework by 17th Jan, we will grade it and grant certificates. Sign up here! dlthub.com/events #DataEngineering #databs #python #etl

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Adrian Brudaru @datateam.bsky.social · 04/12/2024

Does closing your eyes when thinking of hard problems help? Yes, closing your eyes stops visual processing and creates an alpha wave burst, helping with creativity, memory recall and focus. alpha waves increase in the absence of visual processing: pubmed.ncbi.nlm.nih.gov/35075196/

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Adrian Brudaru @datateam.bsky.social · 21/11/2024

At our #1 Paris User Meetup, Modeo presented how they use dlt for data ingestion for getstash.io Read more here www.linkedin.com/feed/update/... talks will be published next week

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Adrian Brudaru @datateam.bsky.social · 05/11/2024

Those 2000 open tabs? Oh that's just my cache.

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