Blogsby GlyphNov 5
How to assess your organization’s AI readiness
AI adoption moves fast. Readiness takes longer. Assess 6 dimensions to see where your data foundation limits AI.
dbt Labs Blog the company blog of dbt Labs: latest posts and feed
dbt Labs · Company blog · 16 a month · 77 posts since Jun 16, 2026
Oct 27
Apache Iceberg on Snowflake got a lot simpler in 2026, and dbt's new catalog config is what makes it click
Changes across Snowflake, dbt, and DuckDB made Apache Iceberg simple enough for a small team to set up in an afternoon.
Oct 27
dbt without the warehouse (or the bill): DuckDB end to end
dbt v2 ships with a built-in DuckDB adapter, so connecting dbt to a local, offline warehouse takes only a small profile change.
Oct 27
With great context comes great autonomy
AI agents need governed context, not just more data, to be trusted.
Oct 27
Why a semantic layer is the difference between a 96% and an 80% accurate AI analyst
Why conversational analytics stalls and the data fundamentals that make it reliable.
Oct 27
What a year of building ADBC drivers taught Columnar about zero-copy's non-zero problems
Columnar co-founder Matt Topol shares the type-system challenges of building production ADBC drivers, now used by dbt v2.
Oct 27
dbt Charts: a new open-source language for dashboards that live inside your dbt repo
dbt Charts is a plain YAML language for building dashboards that version and deploy alongside your dbt models.
Oct 27
Charts worth stealing: the design calls BI should ship
RJ Andrews explains the design defaults behind dbt Charts, from consistent colors to the small choices that make charts work.
Oct 27
Ship AI agents like tables: dbt materializations for Snowflake CoWork
Under Armour turned Snowflake AI agents into dbt models, giving every agent the same review and CI process as every table.
Oct 27
How a one-person data team at Keep built real-time banking infrastructure on dbt
Keep's one-person data team used dbt, Artie, and Snowflake to cut credit underwriting from one business day to under a minute.
Oct 27
How LangChain grew self-serve analytics questions 40x by giving its AI agent layered context
LangChain gave its Hex agent layered context, turning self-serve analytics questions from occasional to routine.
Oct 27
How Sweetwater catches broken dbt pipelines before anyone notices, with Datadog
Sweetwater uses Datadog to catch broken dbt pipelines before dashboard users notice missing data.
Oct 27
How Guitar Center rebuilt its data platform on trust
Guitar Center rebuilt its data stack around control, speed, and trust, cutting Snowflake spend 40% along the way.
Oct 27
How Checkr cut an hours-long metrics investigation to minutes by engineering AI context on dbt and Omni
Checkr gave its AI agent a structured dbt context layer, cutting a support-metric investigation from hours to minutes.
Oct 27
How Ecolab used an AI migration agent to shrink 84,000 lines of legacy SQL by 6x
Ecolab and Datafold used an AI migration agent to rebuild a decade of tangled Snowflake logic as clean, documented dbt models.
Oct 27
Why most of your dbt models aren't in a hurry, and what that's worth in Snowflake credits
Most models in a dbt DAG aren't on the critical path. Espresso AI and Authentic Insurance on turning that slack into real savings.
Oct 27
How DoorDash scaled merchant-facing analytics to thousands of users in weeks, on dbt and ThoughtSpot
DoorDash used a dbt-defined semantic layer to scale analytics from pilot to thousands of merchant users in weeks.
Oct 27
Why an AI agent's revenue query was $3.5 million wrong, and how AWS fixed it with dbt Semantic Layer
A plausible AI revenue query was $3.5 million wrong. AWS explains how business context helps prevent those errors.
Oct 27
How KOHO built a Claude-powered self-serve analytics tool on years of dbt governance
KOHO explains why AI self-serve analytics needs a strong data culture and a governed dbt foundation first.
Oct 27
ClickHouse + dbt: Building a GitOps workflow at Twilio
Twilio replaced Kafka, Spark, and Elasticsearch with one ClickHouse pipeline governed by dbt and GitOps.
Oct 27
How Sigma runs a 2,883-model semantic layer on dbt and Dagster
Sigma shows how it manages its semantic layer as version-controlled code across thousands of dbt models.
Oct 27
How to put generative AI directly into a dbt pipeline with plain SQL
Google Cloud on wiring BigQuery's AI SQL functions into dbt pipelines, from sentiment scoring to LLM-generated product briefings.
Oct 26
Shrink the surface: governed self-service for analyst-owned dbt pipelines
Liftoff made self-service dbt stick by narrowing analyst responsibilities, not by teaching them more of the platform.
Oct 26
How Compare the Market cut report delivery from 6 weeks to under 1 by retiring most of its dashboards
After finding 179 abandoned Power BI reports, Compare the Market rebuilt analytics around reusable dbt models.
Oct 26
How Mitratech cut new customer data onboarding from six weeks to three days with dbt
Mitratech turned one-off customer data requests into a dbt-powered offering, cutting onboarding time 90%.
About this blog
Analytics engineering, dbt, the semantic layer and data teams.
Posts per week, last 26 weeks
16 a month over the last six months (or since the feed's oldest post)
Posts by month
Writes about
Data engineering (53), AI and agents (14), Product and company (7) in the last six months.