Blogsby GlyphApache 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.
46 of 800 posts
Tue Oct 2721 posts
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.
With great context comes great autonomy
AI agents need governed context, not just more data, to be trusted.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
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.
ClickHouse + dbt: Building a GitOps workflow at Twilio
Twilio replaced Kafka, Spark, and Elasticsearch with one ClickHouse pipeline governed by dbt and GitOps.
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.
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.
Mon Oct 2625 posts
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.
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.
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%.
How Figma turned dbt tests into consistency checkers that catch 100+ bugs a month
Figma's data science team built an early warning system for billing bugs out of nothing more exotic than dbt tests.
A dbt "logic mesh" with packages: standard model and metrics across 25 autonomous organizations
Greenpeace unified metrics across 25 autonomous organizations with three layers of dbt packages, without a central mandate.
How Obie Insurance cut its month-end close from 25 hours to 2 with dbt State and a lake house rebuild
Obie Insurance rebuilt on dbt and Apache Iceberg, cutting a critical monthly process from over 25 hours to 2 hours.
The dbt governance framework that cut new project setup time 70%
Two principal analytics engineers explain the three-layer dbt governance framework that cut project setup time 70%.
How a data scientist at Kilo built the business context layer his AI agents were missing
How a data scientist built an AI context layer for organizational knowledge a dbt project alone can't hold.
How to solve dashboard debugging in six minutes with an MCP-connected AI agent
An AI agent used dbt lineage from inside the BI layer to answer three data mysteries in the time it takes to get coffee.
What a swarm of rogue AI agents can teach us about having better ideas
Benn Stancil uses the Hugging Face hack to explain why the most useful ideas come from the weirdest connections.
From mainframe to AI-powered maturity: Verisk's data modernization journey
Verisk modernized decades of insurance data, from mainframe to dbt, to get AI-ready.
How Ramp's internal AI agents crossed a million sessions
Ramp shares the agents, sandboxes, and dashboards it built by treating internal AI as analytics engineering.
How Virgin Media O2 cut compute costs 30% by giving dbt a memory
Virgin Media O2 cut dbt compute costs 30% and model run times 35% by adopting dbt v2 and dbt State at scale.
How DocuSign cut analytics engineering time in half by pairing Claude Code with dbt v2, dbt MCP, and agent skills
DocuSign wired Claude Code, dbt Agent Skills, dbt MCP, and dbt v2 into one workflow and measured a 50% productivity gain.
From prompt to PR: how Careem’s AI writes and validates dbt models before a human ever sees them
Careem's AI agent writes and validates dbt models end to end before a human ever reviews the PR.
Showing our work: a controlled experiment in context engineering
We ran one AI skill 80 times against four context sources. Engineered summaries cut cost 48.5% and run time 43.2%.
Optimizing your runs for lower compute, fresher data, and faster iteration with dbt State
dbt State turns freshness rules into model-level code, and it took dbt Labs' own project from nineteen scheduled jobs down to two.
dbt v2 lands: faster parsing, one shared adapter layer, and a docs experience that skips the giant manifest.json
dbt v2 bundles adapters, speeds up parsing, and replaces manifest.json with smaller, queryable files for people and AI.
Inside dbt Wizard, the AI agent built to show its work
dbt Wizard's designer and engineering lead show how the agent validates its own work before code ever reaches production.
Beyond medallion architecture: the written rules that keep a growing dbt project consistent
Silja Märdla on why medallion layers fall short and how 14 explicit rules keep a growing dbt project consistent.
What Okta learned governing context for AI agents at scale
Okta rebuilt how it governs context for AI agents, using dbt as the single source of truth.
How customer pressure pushed dbt past a cautious platform team at Delivery Hero
At Delivery Hero, dbt adoption came from customer teams pushing past platform caution, not from a platform mandate.
How Kramp cut analyst onboarding from days to minutes with a self-serve dbt Mesh factory
Kramp used one Terraform module to let 15 domain teams provision governed dbt projects in minutes.
How Verily Health monitors wastewater for 30-plus pathogens with a 5-person team and 1 dbt package
Verily Health's five-person team uses one dbt package to monitor wastewater for over 30 pathogens in near real time.
How Data Culture measured its way from zero trust to a shippable AI analytics agent
Data Culture built a 3-step evaluation framework that took one AI analytics deployment from 0% accuracy to 94.7%.