The Agent Stack
Vinoth Govindarajan, OpenClaw UnboxedThe Agent Stack is a technical deep dive into how modern AI agents actually work under the hood, from control loops and memory systems to orchestration, evaluation, and production deployment.
| Platform |  | Pricing | Only free issues | Publishes | Weekly |
|---|---|---|---|---|---|
| Issues | 22 | Founded | 6 months ago | Last Issue | 15 days ago |
| Active | |||||
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The Data Agent Stack - Part 7: Evals, Provenance, and Production Feedback Loops
The agent answered the same question correctly yesterday.
Overnight, a context document, metric definition, schema, model, or tool changed.
Today, the SQL still compiles. The query still returns rows. The answer is different.
Which part...
The Data Agent Stack - Part 6: Trust, Permissions, and Governance
The SQL compiled.
The warehouse returned 42,871 rows. The chart matched last quarter’s report. The explanation was clear.
There was only one problem.
The requester could not access the customer-level table.
The data agent’s service iden...
The Data Agent Stack - Part 5: Tools, Query Execution, and the Analyst Loop
More tools feel like more capability.
For a data agent, they often mean more ways to be wrong.
The dangerous part is not that the agent can write SQL. It is that it can run SQL, trust the result, and publish the answer before anyone notic...
The Data Agent Stack - Part 4: Meaning Lives in Code
A user asks for active users.
The agent finds a table with user_id, event_time, and platform.
The SQL runs. The chart looks reasonable.
But the table excludes logged-out traffic. It deduplicates at session grain, not user-day grain...
The Data Agent Stack - Part 3: Context Assembly for Data Agents
A user asks:
“Why did weekly active usage dip after the launch?”
The agent finds a canonical metric definition, an older dashboard query, a human annotation about test tenants, a launch document, a stale incident note, a saved correction,...
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Authors
The writers behind this newsletter.
Systems engineer at OpenAI, open-source contributor, and co-author of Engineering Lakehouses with Open Table Formats, explaining how modern AI agents and data systems actually work in production.
Unbox the AI that actually does things. Build cheaper more capable agents and smarter routing for token efficiency. Copy the configuration. Run your 24/7 team. An independent AI agent community by Josh Davis
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