Vinoth Govindarajan

@iamvinoth

San Francisco, CA

Joined December 2008

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Vinoth Govindarajan
@iamvinoth
Jul 22
Schemas tell you shape. Pipeline code tells you meaning. In Part 4 of The Data Agent Stack, I wrote about why production data agents need code-enriched context: grain, freshness, filters, exclusions, and provenance before they write SQL. theagentstack.substack.com/p/the-data-age…
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Vinoth Govindarajan
@iamvinoth
Jul 21
The hard part of a data agent is not the model call. It is deciding what context the model sees before it reasons. Part 3 breaks down context assembly: table usage, annotations, institutional knowledge, memory, runtime checks, and provenance. theagentstack.substack.com/p/the-data-age…
Vinoth Govindarajan
@iamvinoth
Jul 20
No agent architecture can save messy data. If ownership, freshness, lineage, and canonical tables are unclear, the agent will make that mess conversational. Part 2 is about why the data foundation is the agent. theagentstack.substack.com/p/the-data-age…
Vinoth Govindarajan
@iamvinoth
Jul 19
A data agent is not just text-to-SQL. It has to resolve meaning, find trusted data, execute safely, validate results, and show evidence. I started The Data Agent Stack with the loop behind a verified answer. theagentstack.substack.com/p/the-data-age…
Vinoth Govindarajan
@iamvinoth
Jul 18
A demo can be a story. Production is a reconstruction problem. In the final part of The Agent Stack v1, I wrote about observability, evaluation, and feedback loops. Traces explain what happened. Evals decide whether it was good enough. theagentstack.substack.com/p/the-agent-st…