Stop Treating LLMs Like Databases: The Financial Case for Event-Driven AI | by Shakir Majeed Mir | Jun, 2026 | MediumSitemapOpen in appSign up<br>Sign in

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Stop Treating LLMs Like Databases: The Financial Case for Event-Driven AI

Shakir Majeed Mir

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A well thought architecture can save you millionsYour database queries complete in 50 milliseconds. Your Redis cache hits return in under 1 millisecond. Your LLM API call takes 15 to 30 seconds.<br>That is not a performance gap. It is three orders of magnitude. And every architectural assumption your backend runs on — thread pool sizing, connection pool limits, timeout configurations, retry semantics — was built for the first two numbers, not the third.<br>Most teams treat LLM integration as an API swap. Add the client library, call the endpoint, handle the response. Same pattern they use for Stripe or Twilio. It works fine in development. In production, under real load, it starts bleeding cash and dropping users in ways that take months to trace back to the architecture choice made on day one.<br>Read the full article for free at : https://shakirmajeedmir.substack.com/p/stop-treating-llms-like-databases

The Mental Model That Gets You Into Trouble<br>When you call a database, the cost is roughly fixed per query. An indexed read on ten rows costs more or less the same as one on a hundred. Infrastructure costs are predictable, and you build your pricing assumptions on predictability.

Written by Shakir Majeed Mir<br>98 followers<br>·60 following

Software engineer & product builder. Writing about databases, AI, and the hidden challenges of real-world systems. Founder: LayoutCraft

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