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.
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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.
With great context comes great autonomy
AI agents need governed context, not just more data, to be trusted.
Why dbt Labs thinks AI agents will finally make the semantic layer stick
Why AI agents can make semantic layers stick, if teams can solve the trust problem.
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.
CFBrainAug: Modularity-Induced Counterfactual Brain Network Augmentation for Interpretable fMRI-based Autism Diagnosis
arXiv:2610.32184v1 Announce Type: new Abstract: Machine learning on resting-state functional magnetic resonance imaging (rs-fMRI) brain networks is promising for diagnosing Autism Spectrum Disorder (ASD), but existing methods are prone to overfitting on limited training data, and their post-hoc statistical attribution offers limited clinical interpretability. We propose CFBrainAug, a counterfactual brain network learning framework that unifies data augmentation and counterfactual explanation by learning label-altered brain networks. Unlike conventional label-preserving augmentation, CFBrainAug first retrieves a label-opposite yet topologically similar candidate and then refines it under a module-number constraint. Jointly training on factual and counterfactual networks enriches the trainin
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.
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.
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.
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%.
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.
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.
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.
Expanding Customer Notifications for ClickHouse Managed Postgres
ClickHouse Managed Postgres is adding five new customer notifications: inactive replication slots, planned switchovers, unplanned failovers, long-running transactions, and connections approaching their limit.
How Shipsidekick replaced Neon with ClickHouse Managed Postgres for 10x faster queries and better reliability
Shipsidekick moved from Neon to ClickHouse Managed Postgres in a single weekend, cutting CPU usage from 100% to 5-10% and making queries about 10x faster.
Front-end observability at scale: How OpenReplay captures billions of daily events in real time with ClickHouse
OpenReplay replaced Postgres with ClickHouse to ingest billions of events and up to 6 TB a day on a single, vertically scaled instance, with sub-second queries and retention handled by a single TTL setting.
Trace and evaluate Cursor agents with Langfuse, powered by ClickHouse
Connect Cursor to Langfuse to trace every agent turn, pinpoint expensive model and tool calls, and use evaluations to confirm a fix actually helps, with ClickHouse powering the analytics underneath.
The Agentic Analytics Benchmark, round two: GPT-6, Claude Opus 5.5, Claude Sonnet 5.5
We added GPT-6 Astra, Luna and Sol, Claude Opus 5.5 and Claude Sonnet 5.5 to the Agentic Analytics Benchmark: all five land mid-board within a point of each other, and Sonnet 5.5 brings the biggest change in turns, cost and truncated runs.
Postgres wait events, now in Query Insights
Query Insights for ClickHouse Managed Postgres now shows what active sessions are waiting on, with wait event breakdowns, blocked-session and lock-wait charts, and the same metrics in Prometheus.
Introducing the (blazing fast!) native TCP client for .NET
ClickHouse’s new native TCP client for .NET brings faster reads and inserts with fewer allocations, columnar APIs, POCO support, and a path to migrate from HTTP.