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.
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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.
OpenAI has rewritten the history of human science! “The King’s Conjecture” has been disproven on all fronts, and the 30-year-old ironclad rule governing ETH has collapsed.
New智元 reports: Honestly, the history of human science has been completely rewritten tonight! Just now, OpenAI dropped three major announcements in quick succession, officially revealing that its internal AI independently achieved three groundbreaking discoveries—each a true “milestone”: In mathematics, it proved the “local smoothness conjecture” in all dimensions, finally putting an end to the “Kakeya conjecture,” which had puzzled the mathematical community for a century; in computer science, it refuted the “Exponential Time Hypothesis” (ETH), which has dominated the field for nearly 30 years; and in theoretical physics, it provided insights into four-dimensional quantum chromodynamics (QCD) and pure...
Wang’s conjecture was solved by AI overnight.
AI has already begun turning in its answers, but humans may not even have time to grade them. #Follow the iFanr official WeChat account: iFanr (WeChat ID: ifanr) for more exciting content delivered straight to you.
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.
Supabase’s Plan for a Billion AI-Built Apps
AI agents are creating more software—and that changes what a backend needs to do. Supabase co-founders Paul Copplestone and Ant Wilson join swyx to discuss running long-lived workloads alongside the database, making schemas easier for agents to underst...
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.
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.
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.
Microsoft and Hugging Face have open-sourced the ThinkingBox framework: using the database’s final state as a deterministic reward signal to advance post-training reinforcement learning for agents.
Microsoft and Hugging Face have jointly launched the open-source framework ThinkingBox, which generates binary 0/1 rewards by comparing the LLM agent’s final database state after execution with the expected state, for reinforcement learning-based fine-tuning. The accompanying benchmark, ThinkingBox-Bench, includes 507 real-world backend tasks, none of which were used during training. After 50 steps of GRPO fine-tuning, Qwen3.8-27B achieved a 9.08-percentage-point improvement in pass@1 on the held-out test set, with Observed 20/20 nearly tripling; however, pass@20 declined in some domains, reflecting a trade-off between breadth and stability.
PHP ‘Doomsday Vulnerability’ Exposed: OpenAI and Wiz Use AI to Discover a High-Risk Flaw Spanning 20 Years
The U.S. National Security Agency (NSA) issued an urgent alert: OpenAI and Google’s Wiz team, working together using AI tools, have discovered two critical vulnerabilities affecting all PHP versions 5 and above (since 2004). These vulnerabilities could allow remote exploitation of the server’s file system or database. While there are currently no reports of real-world exploitation, AI has significantly lowered the barrier to attack, making it imperative for tens of millions of websites worldwide to urgently upgrade to PHP 8.5.12.
Google’s Antigravity platform accelerates antimicrobial peptide discovery: an end-to-end AI scientific workflow powered by ProtNLM and AlphaFold
Google has launched the Antigravity scientific AI platform, integrating the ProtNLM protein function prediction model, the AlphaFold structural database, and genome-context reasoning capabilities to help biologists, in a single interactive session, identify, validate, and prioritize novel antimicrobial peptides (AMPs) from vast pools of unannotated proteins—such as the millions of “dark matter” sequences in UniProt—throughout the entire workflow. The first candidate molecule (UniProt ID: A0A0U0D591) has already entered the wet-lab validation phase.
The Agent Said It Was Done. The Database Disagreed.
The Agent Said It Was Done. The Database Disagreed.
AutoSynthData: Generating Training Data for Enterprise Agents
AutoSynthData: Generating Training Data for Enterprise Agents