---
name: Dagster Blog
slug: dagster-blog
type: scrape
source_url: https://dagster.io/blog
organization: Dagster
organization_slug: dagster
total_releases: 7
latest_version: 1.13
latest_date: 2026-04-09
last_updated: 2026-04-11
tracking_since: 2026-01-21
canonical: https://releases.sh/dagster/dagster-blog
organization_url: https://releases.sh/dagster
---

<Summary type="rolling" window-days="90" release-count="6">
Dagster shipped major product work alongside educational content exploring how teams use the platform. Version 1.13 introduced partitioned asset checks, virtual assets, and skills—a new capability for encoding domain knowledge into the orchestration layer. In parallel, the team published guides on testing AI-generated code at scale, built Compass to surface operational insights from Dagster+ telemetry, and released a children's book explaining asset dependencies as a narrative device, reflecting a broader push toward making data infrastructure more legible to teams building with it.
</Summary>

<Release version="1.13" date="April 9, 2026" published="2026-04-09T00:00:00.000Z" url="https://dagster.io/blog#1-13">
## Dagster 1.13: Octopus's Garden

Introduces Dagster skills, partitioned asset checks, state backed components, virtual assets, and stronger integrations.
</Release>

<Release date="February 6, 2026" published="2026-02-06T00:00:00.000Z" url="https://dagster.io/blog#evaluating-skills">
## Evaluating Skills

We built a lightweight evaluation framework to quantitatively measure the effectiveness of the Dagster Skills, and these are our findings.
</Release>

<Release date="February 5, 2026" published="2026-02-05T00:00:00.000Z" url="https://dagster.io/blog#great-infrastructure-needs-great-stories-designing-our-child">
## Great Infrastructure Needs Great Stories: Designing our Children's Book

We set out to explain Dagster assets in the simplest possible way: as living characters that wait, react, and change with their dependencies. By designing a children's book with warmth, visuals, and motion, we rediscovered what makes assets compelling in the first place.
</Release>

<Release date="February 3, 2026" published="2026-02-03T00:00:00.000Z" url="https://dagster.io/blog#closing-the-dataops-loop-why-we-built-compass-for-dagster">
## Closing the DataOps Loop: Why We Built Compass for Dagster+

Detection isn't the bottleneck anymore. Understanding is. Compass closes the loop by turning Dagster+ operational data into a conversation.
</Release>

<Release date="January 26, 2026" published="2026-01-26T00:00:00.000Z" url="https://dagster.io/blog#pytest-for-agent-generated-code-concrete-testing-strategies-">
## Pytest for Agent-Generated Code: Concrete Testing Strategies to Put Into Practice

When agents write tests, intent matters as much as correctness. By defining clear testing levels, preferred patterns, and explicit anti-patterns, we give agents the structure they need to produce fast, reliable Pytest suites that scale with automation.
</Release>

<Release date="January 21, 2026" published="2026-01-21T00:00:00.000Z" url="https://dagster.io/blog#dagster-snowflake-building-production-ai-pipelines-with-cort">
## Dagster + Snowflake: Building Production AI Pipelines with Cortex

Snowflake handles AI compute while Dagster handles orchestration, observability, and the operational patterns that turn AI experiments into reliable production pipelines.
</Release>

<Release url="https://dagster.io/blog#sample-level-versioning-for-ml-pipelines-with-dagster-and-me">
## Sample-Level Versioning for ML Pipelines with Dagster and Metaxy

Learn how Metaxy can be used to build multimodal data pipelines with sample-level granularity on Dagster.
</Release>