vojay

DevRel @ @astronomerio 📚 Tech writer & speaker | 📸 Creative soul | 💪 Gym × 🎮 Gaming × 🤝 Community | Building bridges between data & people

[vojay @vojaydev]

California, here we come 🌇 Extraordinary Alien status confirmed 👽 O-1A approved! Shoutout to @0xSigil for helping others pursue their dreams and the inspiration. Looking forward to exploring the U.S. data / AI scene! My journey from Hamburg to Hollywood: https://t.co/ZHOiUPIEJA

[Astronomer @astronomerio]

🆕 New to Airflow?

Join @vojaydev for a 60-minute intro to Airflow webinar, where you'll learn:

👩‍🏫 Airflow fundamentals every data engineer needs to know
↔️ How to write and run your first real pipeline
🤖 How teams at @OpenAI, @Uber, and @salesforce use Airflow

Register at the link below.

[vojay @vojaydev]

Shridhar Iyer (Director of Data Engineering @ Meta) in the latest Data Engineer Things Community Spotlight:

"From writing logic to specifying intent, from governing code to governing knowledge."

The next gen of DEs owns semantics, not scripts. Two skills matter most:

1️⃣ Domain modeling: mirror how the business thinks
2️⃣ Evals: define what good looks like and how to measure it

💡 DE + AI = own semantics + master evals

Full interview 👇

https://t.co/CgHYNkwJiH

[Claude @claudeai]

Introducing Claude Opus 4.8: it builds on Opus 4.7 with sharper judgment, more honesty about its own progress, and the ability to work independently for longer than its predecessors.

Available today at the same price.

[Astronomer @astronomerio]

🌁 San Francisco! We can't wait to see you next week at @Snowflake Summit ‘26.

Here’s where to find us on-site:

🤖 Visit booth #2605 to check out the latest from Astronomer, including Otto, our new data engineering agent built for Apache Airflow, for your shot at a @KeychronMK keyboard
❄️ Carter Page, @vojaydev, and @StevenHillion each have speaking sessions, covering production AI, context problems, data governance, and unified orchestration
☕ Club @_hex_tech, an elevated lounge for conversations, food, and drinks

Link below.

[Astronomer @astronomerio]

Writing Dags the old-fashioned way is slow, manual, and why your backlog never moves. ✍️

Join Airflow experts for a live walkthrough of modern Dag authoring built for Airflow 3, so you can write better Dags, faster.

You'll learn how to:

→ Generate production-ready Dags faster with agents trained on Airflow best practices
→ Let analysts define pipelines in YAML within guardrails you set
→ Use Dag versioning and human-in-the-loop to ship with confidence

Link below.

[Astronomer @astronomerio]

"Building it on Astronomer’s Astro platform means Otto has access to full operational history of an organisation’s data platform, i.e., every pipeline execution, failure, and correction is a record of how data actually moves…and that context is what lets Otto reason about the environment with precision." – @ComputerWeekly

@ABridgwater does a deep dive with @JulianLaneve and @tayloramurphy into all things Otto, our new data engineering agent purpose-built for Apache Airflow.

Otto incorporates our team's accumulated Airflow knowledge about what breaks, what works, and what it actually takes to keep a production data platform healthy to make the lives of data engineers easier.

Article link below.

#ApacheAirflow #Airflow

[vojay @vojaydev]

Can’t wait to be back in SF for this one 🫶!

[Astronomer @astronomerio]

🌁 See you soon, San Francisco, for @Snowflake Summit ‘26!

Here’s where to find us June 1-4:

❄️ Carter Page, @vojaydev, and @StevenHillion each have their own speaking sessions, covering production AI, context problems, data governance, and unified orchestration
☕ Club @_hex_tech, an elevated lounge for conversations, food, and drinks
🤖 Stop by our booth #2605 to check out the latest from Astronomer, including Otto, our new data engineering agent built for Apache Airflow, for your shot at a @KeychronMK keyboard

Find us on-site: https://t.co/rQqzYwvwU9

[vojay @vojaydev]

@AskFrontier That is exactly what an agent would say 🤖. Jokes aside, your service today was outstanding, kudos to the team!

[vojay @vojaydev]

Shoutout to @AskFrontier .. was really impressed by the service offered via XChat today 🫶. Still not sure if I talked to an agent, but if so, it would be even more impressive 🤖

[Astronomer @astronomerio]

🆕 Meet Otto: the first agent designed to run your data platform built on Apache Airflow.

⏩ Coding agents are great for writing code. Otto is an Airflow expert, always available directly in your terminal, and built to accelerate any data engineering workflow with:

- Data exploration
- DAG authoring and debugging
- Investigation & root cause analysis
- Airflow upgrades
- More

🧠 Grounded in the compatibility knowledge and failure patterns from over 1k+ enterprise Airflow deployments, plus your team's specific memory that compounds every session, Otto blends open and proprietary knowledge to help your data team do more.

Because there IS a difference between an agent that helps you write pipelines and one that knows your entire Airflow environment, your team's conventions, and what broke last Tuesday at 2 AM.

Read more in the blog below and type "astro otto" into your terminal to start using Otto today.

[Astronomer @astronomerio]

⏩ @cursor_ai. @claudeai Code. MCPs. The way data engineers build locally is changing fast.

Apache Airflow experts Tamara Fingerlin and @vojaydev will demonstrate what a modern local dev setup looks like and how to build one yourself.

You’ll learn how to:
🌀 Spin up a local Airflow environment using Cursor, Devcontainers, and the Astro CLI
⚡ Write and test Dags faster using the Astronomer Cursor plugin and Claude Code skills
🧠 Apply practical patterns for AI-assisted data engineering that produce suggestions worth using

Link below.

[vojay @vojaydev]

@PixiJS Need this as a Chrome plugin, so many websites where my first thought is, "I want to destroy it with a laser." 🎯 Seriously impressive demo, can't wait to try this.

[Kaxil Naik @kaxil]

What if your @ApacheAirflow task asked an LLM whether the error is retryable before wasting 3 blind retries?

Landing in Airflow 3.3. (AIP-105) 🧵

[vojay @vojaydev]

Wait, so soon I can use mIRC again and meet friends from the good old IRC era and it’s considered modern? Amazing 😍.

[Orhun Parmaksız 👾 @orhundev]

We're now hanging out in the terminal! 💯

☕ https://t.co/gBjB0zEKio — SSH-powered social clubhouse for devs

🌐 Chat, lofi beats, games & news in a shared always-on TUI space

➡️ Run "ssh https://t.co/gBjB0zEKio" to join!

🦀 Written in Rust & built with @ratatui_rs

⭐ GitHub: https://t.co/hftWyfNIQW

#rustlang #ratatui #tui #terminal #community #social #ssh

[Astronomer @astronomerio]

Apache Airflow 3.2 is here, bringing partitioned Dag runs and asset events, async Python support for @ task and PythonOperator, and UI theming.

This quick notes guide comes with code examples for every new feature to use as patterns in your own Dags.

Download the guide to learn how to:

↔️ Pass timestamps between Dags scheduled based on assets without custom workarounds
⚡ Cut task runtime by running concurrent async API calls in a single @ task
🎨 Flag critical production deployments by adjusting the colors in the Airflow UI using an Airflow configuration variable

Link below.

[vojay @vojaydev]

🎙️ "How should data engineers think about AI's impact on humanity?"

Great panel at the Data Engineering Open Forum by @dataengthings with Vikram Koka (Astronomer), Laura Pruitt (Netflix), and Paul Ellwood (OpenAI):

👉 Astronomer (Vikram Koka): Writing software with AI is fun, and risky. Stay aware of the pitfalls.
👉 Netflix (Laura Pruitt): If you see something, say something. If something doesn't fit, speak up.
👉 OpenAI (Paul Ellwood): How do we make AI observable? How do we assess whether it's acting responsibly, and make that information actionable? As humanity, we need to understand what AI does.

Data engineers are uniquely positioned here. We build the systems that make AI traceable, auditable, and accountable. That's responsibility.

[vojay @vojaydev]

🎙️ "What's the one skill data engineers should focus on over the next 24 months?"

Great panel at the Data Engineering Open Forum with Vikram Koka (@astronomerio), Laura Pruitt (@netflix), and Paul Ellwood (@OpenAI):

→ OpenAI: Semantic ownership, become the business translator. Understand what the data means, not just how it moves.
→ Netflix: Flexibility and openness. Tech comes and goes. The engineers who thrive are the ones who adapt.
→ Astronomer: Keep building reliable, auditable, fault-tolerant pipelines, and be able to define those principles for production AI systems.

[Astronomer @astronomerio]

🆕 Introducing Blueprint in Astro: self-service Dag authoring for your entire organization.

Now in public preview, Blueprint in Astro is built around two distinct roles:

1️⃣ Platform and data engineers define templates using the Blueprint open source framework.
2️⃣ Analysts and other teams build pipelines using those templates and no-code interface in Astro.

Once templates are available in your Astro environment, anyone can open Astro IDE and start building. The Blueprint interface presents your organization's approved templates as a library of building blocks, and the Dag gets committed through the same Git workflow as any hand-authored pipeline. This includes the same audit trail and governance.

Get started with Blueprint in Astro today at the link below.

[vojay @vojaydev]

10:30am at the Data Engineering Open Forum, still early but met so many amazing people already 🫶 @astronomerio

[Claude @claudeai]

Introducing Claude Opus 4.7, our most capable Opus model yet.

It handles long-running tasks with more rigor, follows instructions more precisely, and verifies its own outputs before reporting back.

You can hand off your hardest work with less supervision.