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Blog
January 7, 2026
Evaluating Model Behavior Through Chess
Benchmarks measure outcomes, not behavior. By letting AI models play chess in repeatable tournaments, we can observe how they handle risk, repetition, and long-term objectives, revealing patterns that static evals hide.
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January 6, 2026
How to Enforce Data Quality at Every Stage: A Practical Guide to Catching Issues Before They Cost You
This post gives you a framework for enforcing data quality at every stage so you catch issues early, maintain trust, and build platforms that actually work in production.
Alex Noonan
Engineering
January 5, 2026
When Sync Isn’t Enough
This post introduces a custom async executor for Dagster that enables high-concurrency fan-out, async-native libraries, and incremental adoption, without changing how runs are launched or monitored.
Steven Ayers
Engineering
December 22, 2025
How to Build a Data Platform That Actually Scales
Most teams build data platforms reactively when you should be architecting one that scales with your business, not against it.
Alex Noonan
Engineering
December 16, 2025
Orchestrating Nanochat: Deploying the Model
Once the model is trained, the final step is getting it into users’ hands. This guide walks through turning your model into a fast, reliable RunPod endpoint—complete with orchestration and automated updates from Dagster.
Dennis Hume
Product
December 15, 2025
Data Ingestion Patterns: When to Use Push, Pull, and Poll (With Real Examples)
A practical guide to choosing between push, pull, and poll data ingestion patterns. With real Dagster code examples to help you build reliable, maintainable pipelines.
Alex Noonan
Engineering
December 11, 2025
Dagster + Atlan: Real-Time Asset Observability in Your Data Catalog
Automatically sync asset materialization events and lineage from Dagster Cloud to Atlan
Alex Noonan
Product
December 9, 2025
Orchestrating Nanochat: Training the Models
Training an LLM isn’t one job—it’s a sequence of carefully managed stages. This part shows how Dagster coordinates your training steps on RunPod so every experiment is reproducible, scalable, and GPU-efficient.
Dennis Hume
Product
December 3, 2025
Orchestrating Nanochat: Building the Tokenizer
Every great model starts with great data. This first part walks through how to structure ingestion with Dagster, prepare your text corpus, and build a tokenizer that shapes how your model understands the world.
Dennis Hume
Product
November 17, 2025
When (and When Not) to Optimize Data Pipelines
Engineers often optimize the wrong parts of their pipelines, here's a profiling-first framework to identify real bottlenecks and avoid the premature optimization trap.
Alex Noonan
Engineering
November 13, 2025
Your Data Team Shouldn't Be a Help Desk: Use Compass with Your Data
Compass now supports every major data warehouse. Connect your own data and get AI-powered answers directly in Slack, with your governance intact and your data staying exactly where it is.
Alex Noonan
Product
November 5, 2025
Introducing Our New eBook: Scaling Data Teams
Learn how real data teams, from solo practitioners to enterprise-scale organizations, build in Dagster’s new eBook, Scaling Data Teams.
Dennis Hume
Engineering
October 30, 2025
Dagster 1.12: Monster Mash
A refined Dagster experience. Faster navigation, GA Components, plug-and-play deployment, improved orchestration with FreshnessPolicies, and a new Support Center for builders at scale.
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