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.
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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%.
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.
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.
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.
StackGen3D: Stable 3D Block Stack Generation from Multiview Silhouettes
arXiv:2610.31803v1 Announce Type: new Abstract: Generating physically stable 3D structures from visual specifications requires resolving geometric ambiguity while accounting for physical interactions among objects. We present StackGen3D, a framework for generating stable block assemblies conditioned on a given block inventory and three orthographic silhouettes. Our approach consists of two stages. First, we develop a physics-informed graph neural network (PI-GNN) that models support relations between blocks and serves as a fast stability predictor for curating a diverse dataset of stable structures. Second, we train a conditional flow-matching model on this dataset to capture the multimodal distribution of block configurations consistent with the target silhouettes. At inference time, ligh
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.
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.
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.
OLTP is expensive, you can ClickHouse it.
Offload settled Postgres data to ClickHouse to reduce storage and query costs while keeping active transactions in Postgres.
How Ridgeline unified Iceberg and ClickHouse into one analytics layer for investment management
Ridgeline rebuilt its performance analytics on ClickHouse Cloud, querying decades of Iceberg history alongside recent data so it can serve investment managers 10x larger than before and more than double the customers live on its platform.
Chasing that 32 ms tail latency in ClickHouse
A customer saw an extra ~32 ms on simple SELECT queries after idle periods. We traced it to unbatched Native protocol metadata packets overflowing a reset TCP congestion window, reproduced it with network namespaces, and fixed it by batching them.
Postgres at Open House NYC
At Open House NYC, we showed how ClickHouse Managed Postgres and ClickHouse work as one stack, with a live WalShadow demo replicating Postgres into ClickHouse in under a second, plus the same-week Google Cloud and chdb extension launches.
How iSAM Funds built an options research platform for a 10,000x data problem with ClickHouse Cloud
iSAM Funds uses ClickHouse Cloud to research full options history, achieving 35–50x compression and 100x faster single-core ingestion while simplifying its data pipelines.
Executable UDFs are now generally available on ClickHouse Cloud
Executable UDFs are now generally available on ClickHouse Cloud across AWS, GCP, and Azure, with native runtimes, network access, observability, and API and Terraform support.
ClickHouse Workload for Microsoft Fabric: sub-second analytics on OneLake, now in public preview
ClickHouse Workload for Microsoft Fabric brings sub-second analytics to OneLake data through a native Fabric workload, with dedicated ClickHouse Cloud compute for agents, dashboards, and applications.
ClickHouse expands collaboration with Microsoft, bringing Fabric integration, deeper OneLake interoperability, and enterprise deployment flexibility
ClickHouse expands its Microsoft collaboration with a native Fabric workload, OneLake read and write capabilities, and ClickHouse BYOC availability in the Microsoft Marketplace.
chDB Durable Layer for agent memory
The chDB Durable Layer keeps agent memory fast to query locally while making its analytical state recoverable across laptops, CI jobs, and short-lived sandboxes.
How Fountain rebuilt its data plane on ClickHouse Cloud to power Cue, the Frontline Superintelligence
Fountain cut analytics latency from three hours to under two minutes and costs by 66% by rebuilding Cue’s data plane on ClickPipes and ClickHouse Cloud.