Analytics agents built by data teams

A curated list of articles from data teams building analytics agents.

Recommended first reads · Internal builds · Browse by problem · Related reading · Contribute

Recommended first reads

1. Anthropic — How a team makes self-service analytics work. Skills, metric definitions, documentation, and evaluations (Jun 2026), including how the team keeps them current as data models change.
2. OpenAI — Inside an in-house data agent. The architecture behind context preparation, retrieval, permissions, and evaluations (Jan 2026).
3. Ramp — Building one around an existing dbt project. SQL and Jinja examples for context tables and domain documentation (Oct 2025).

Internal builds

Read an article directly from the right column, or click a company for its full reading notes. Dates are publication dates; stacks reflect what the authors used at the time.

Team	Stack	What to read
Alan	Nao, Claude Code, Dust	Adoption across the data team and beyond (Apr 2026)
AngelList	dbt, Snowflake, Devin	Generating context from metadata and code (Aug 2026)
Anthropic · 2 posts	Claude Code, Claude Tag, MCP, Slack	Skills, documentation, and evaluations (Jun 2026) · Deploying it in Slack (Aug 2026)
Astronomer	DuckDB, Snowflake, Airflow, Slack	Inferring a context layer from metadata and pipeline code (Mar 2026)
Bitrise	PydanticAI, Claude, BigQuery, dbt, Slack	Tools, memory, guardrails, and post-launch lessons (Jul 2026)
BlaBlaCar	dbt, BigQuery, Markdown	Rebuilding a warehouse and its documentation for analytics agents (Sep 2026)
Cloudflare	Trino, R2, DataHub, Workers AI, MCP	A unified data platform and the Skipper analytics agent (May 2026)
DoorDash	GPT-5.5, SQL	Vera: retrieval, domain-owned evaluations, and model trade-offs (Sep 2026)
Faire	Cursor, Snowflake, Mode	Moving analytics into an IDE (Nov 2025)
GitHub	Copilot, Kusto, Trino	Shared context ownership and PR evaluations (Jun 2026)
Gorgias · 5 posts	dbt, BigQuery, LangSmith, BM25	Cortex platform (Jul 2026) · Context (Mar 2026) · Debugging (May 2026) · Evals (Jul 2026) · Skill retrieval (Aug 2026)
incident.io	Claude Code, Cowork, BigQuery, dbt	Compiling, auditing, and observing an agent’s guidance (Aug 2026)
LinkedIn	LangGraph, LangChain, DataHub	SQL Bot: retrieval, repair, and user experience (Dec 2024)
Meta · 2 posts	SQL, Python, YAML	Personal context, iterative analysis, and reusable domain knowledge (Mar 2026) · Parameterized patterns and deterministic SQL (Oct 2026)
OpenAI · 2 posts	GPT-5.2, Codex, ChatGPT Work, MCP	Context enrichment and runtime retrieval (Jan 2026) · How the data team works with it (Sep 2026)
Qonto	Snowflake, Claude, Markdown, Omni	From text-to-SQL to a governed context layer (Oct 2026)
Ramp · 3 posts	dbt, Snowflake, Looker, Slack	Research overview (Sep 2025) · dbt implementation (Oct 2025) · What changed next (Aug 2026)
Red Hat	OpenShift, MCP	Owner-written guidance, a logged query pipeline, and open-source templates (Aug 2026)
Replit	Git	Sharing reviewed corrections between agents (Aug 2026)
Sourcegraph	Gemini, BigQuery, Cloud Functions	DataBot’s tools and feedback loop (Feb 2026)
Uber	GPT-4 Turbo	QueryGPT: domain, table, and column selection (Sep 2024)
Vercel	Claude, AI SDK, Sandbox, Cube	Simplifying the agent around filesystem access (Dec 2025)
Webflow	Snowflake, dbt, Cursor, Slack	Governed context and controls that sit outside the prompt (Sep 2026)

Browse by problem

• Giving the agent context: Ramp, Gorgias, AngelList, Astronomer, Bitrise, BlaBlaCar, Cloudflare, DoorDash, incident.io, Meta, OpenAI, Qonto, Checkr, KOHO, LangChain, Okta, Red Hat, Webflow.
• Testing answers and model changes: Gorgias, Anthropic, ClickHouse, DoorDash, Ramp, LinkedIn, Meta, Uber, Checkr, KOHO, Webflow.
• Fixing mistakes and keeping context current: Bitrise, DoorDash, GitHub, Gorgias, incident.io, Meta, Replit, Astronomer, Checkr, LangChain, Okta, Red Hat, Anthropic, OpenAI.
• Reducing cost and latency: Cloudflare, DoorDash, Gorgias, Vercel.
• Getting people to use it: Alan, Astronomer, Bitrise, Faire, incident.io, Ramp, LinkedIn, Meta, Qonto, KOHO, LangChain, Red Hat, Anthropic, OpenAI.

Related reading

Product engineering, technical studies, benchmarks, and conference recaps that complement the internal builds.

• Cube: Building an Agentic Analytics Harness · Vendor implementation. Errors, result limits, and permission-aware tools. Stack and notes.

• Omni: Benchmarking Omni’s agentic analytics harness · Vendor implementation. Testing quality, latency, and cost on a vendor’s analytics workload. Stack and notes.

• Cassis: Your data context should be debuggable · Vendor implementation. Organizing context as a tree of business domains so a missed rule can be traced to the wrong turn that skipped it. Stack and notes.

• Cassis: How to assemble context for analytics agents from your existing assets · Vendor implementation. Building the first context from existing data assets, with an open-source bootstrap kit. Stack and notes.

• Cassis: Context engineering for analytics agents · Vendor implementation. How we structure tables, metrics, and business rules so an agent can find what it needs. Stack and notes.

• Lyft: From Day 1 to Production · Production engineering. Taking an existing analytics agent from a Streamlit prototype to an authenticated, observable internal application. Stack and notes.

• ClickHouse: The Agentic Analytics Benchmark · Benchmark. A reusable harness built from 201 real questions, with model-jury scoring, cost and latency measurement, and contamination checks. Code · Notes.

• Benchouse: The Analytics Agent Benchmark · Benchmark. Compare accuracy, completeness, restraint, and cost per question across analytics agents. Notes.

• Cassis: Analytics agents at dbt Summit 2026 · Conference recap. Where the summit’s 40 sessions on analytics agents and context agreed, where teams still differ, and what the talks left open. Notes.

• Checkr: How Checkr cut an hours-long metrics investigation to minutes · Talk write-up. dbt Labs write-up of a dbt Summit 2026 talk. Evals whose failures an agent clusters, drafts a fix for from existing docs, and re-tests before an expert reviews the merge request. Stack and notes.

• KOHO: How KOHO built a Claude-powered self-serve analytics tool · Talk write-up. dbt Labs write-up of a dbt Summit 2026 talk. A Claude skill limited to certified dbt marts, tested by an "eval council" of about 375 real analyst questions. Stack and notes.

• LangChain: How LangChain grew self-serve analytics questions 40x · Talk write-up. dbt Labs write-up of a dbt Summit 2026 talk. Layered context in Hex: dbt descriptions rewritten for agents, workspace guides kept in the dbt repo, and selective endorsements. Stack and notes.

• Okta: What Okta learned governing context for AI agents at scale · Talk write-up. dbt Labs write-up of a dbt Summit 2026 talk. Moving agent context into dbt behind pull requests so Claude and Snowflake Cortex read the same rules. Stack and notes.

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