live wire
▸IBM makes watsonx Orchestrate AgentOps, custom LLM judging and Bedrock-agent discovery generally availableIBM▸SchemaGate 0.1.45 fixes broken Oracle ADB wallet connections and an OCI stack pinned 28 releases behindSchemaGate▸PDI’s Amazon Quick procurement agent grounds spend answers in vendor, category and contract contextAWS Business Intelligence Blog▸BigQuery’s ML.METRICS example returns 0.84 accuracy but 0.30 macro-F1 on the same 100-row classification queryGoogle Cloud BigQuery docs▸SchemaGate 0.1.44 auto-selects sentence embeddings, lifting bundled-schema retrieval from 90/98 to 93/98SchemaGate▸SchemaGate 0.1.43 adds read-only SQL execution with per-principal table checks—and documents unauthenticated client assertionsSchemaGate▸Databox adds reusable AI Analyst Skills with personal/company scope, auto-matching and marketplace installsDatabox▸Fabric previews an AI builder for data-agent instructions, source guidance and example queriesMicrosoft Fabric▸Databricks trains data-agent retriever to stop early or spend bounded extra search steps, reporting 5.8-second latencyDatabricks▸ThoughtSpot adds SpotterCode coding agent to its Visual Embed PlaygroundThoughtSpot▸LongMemEval-S audit: 67–73% of restore-fixable 80k-budget errors came from evicted evidence under three policiesarXiv▸SchemaGate 0.1.42 adds dimension-aware retrieval and fixes complex multi-table SQL promptsSchemaGate▸Snowflake agent toolsets can silently drop inherited tools when callers lack accessSnowflake Documentation▸Looker’s VS Code extension reaches GA with MCP-assisted LookML generation, editing and validationGoogle Cloud Looker release docs▸IBM makes watsonx Orchestrate AgentOps, custom LLM judging and Bedrock-agent discovery generally availableIBM▸SchemaGate 0.1.45 fixes broken Oracle ADB wallet connections and an OCI stack pinned 28 releases behindSchemaGate▸PDI’s Amazon Quick procurement agent grounds spend answers in vendor, category and contract contextAWS Business Intelligence Blog▸BigQuery’s ML.METRICS example returns 0.84 accuracy but 0.30 macro-F1 on the same 100-row classification queryGoogle Cloud BigQuery docs▸SchemaGate 0.1.44 auto-selects sentence embeddings, lifting bundled-schema retrieval from 90/98 to 93/98SchemaGate▸SchemaGate 0.1.43 adds read-only SQL execution with per-principal table checks—and documents unauthenticated client assertionsSchemaGate▸Databox adds reusable AI Analyst Skills with personal/company scope, auto-matching and marketplace installsDatabox▸Fabric previews an AI builder for data-agent instructions, source guidance and example queriesMicrosoft Fabric▸Databricks trains data-agent retriever to stop early or spend bounded extra search steps, reporting 5.8-second latencyDatabricks▸ThoughtSpot adds SpotterCode coding agent to its Visual Embed PlaygroundThoughtSpot▸LongMemEval-S audit: 67–73% of restore-fixable 80k-budget errors came from evicted evidence under three policiesarXiv▸SchemaGate 0.1.42 adds dimension-aware retrieval and fixes complex multi-table SQL promptsSchemaGate▸Snowflake agent toolsets can silently drop inherited tools when callers lack accessSnowflake Documentation▸Looker’s VS Code extension reaches GA with MCP-assisted LookML generation, editing and validationGoogle Cloud Looker release docs
nl2sql.ai
newsLAUNCH

Welcome to nl2sql.ai

A trade publication for one technical beat: systems that turn natural language into SQL. Continuous coverage, evidence-diffed rankings, public corrections.

By The Editorial Desk· Aug 10, 2026the quick take — two AI hosts go live when you do

nl2sql.ai covers one beat, relentlessly: natural language to SQL. New model releases, benchmark movements, open-source projects, enterprise platform features, research papers, and the occasional post-mortem when things go wrong.

What we publish

  • The wire — a continuously updated feed of short, sourced items: releases, papers, leaderboard moves, announcements.
  • Stories — reported pieces when events deserve more than a headline.
  • The leaderboard — a monthly, evidence-diffed ranking of the systems that matter.
  • The directory — reference entries for every serious system on the beat, kept current.
  • The benchmark tracker — BIRD, Spider 2.0, and whatever credible evaluation comes next, with every number linked to its source.

The rules we publish under

  1. Every claim cites a source. Wire items and stories link to the primary artifact — the release notes, the paper, the leaderboard entry.
  2. Rankings are evidence-diffed. Score changes name the evidence that moved them. No pay-for-placement, ever.
  3. Corrections are public. Corrected or retracted stories stay visible with a note explaining what changed.

Why this beat

Text-to-SQL sits at the exact pressure point of enterprise AI: it is the interface between "everyone can ask questions of data" and "the SQL was subtly wrong and nobody noticed." Benchmarks like Spider 2.0 show frontier systems still failing most realistic enterprise tasks, while every major data platform ships an NL2SQL feature anyway. That gap — between demo and dependable — is a news beat. We intend to cover it relentlessly.

Tips, corrections, and challenges: desk@nl2sql.ai. The wire is live.

Filed by The Editorial Desk. Corrections: desk@nl2sql.ai · Our standards →

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