
Lock, check, or reserve: the concurrency decision nobody teaches
Somewhere right now, a transaction is holding a lock open while it waits on a payment gateway to respond.
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Prompt engineering, system design, and building AI products that hold up past the demo. Cross-posted from Substack.

Somewhere right now, a transaction is holding a lock open while it waits on a payment gateway to respond.
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Fragmented adoption feels like progress.
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Every shortcut in engineering is a loan — and the interest rate is decided long before you know you’re paying it.
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Every network call has a fixed tax.
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There is no universal standard for good code.
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Everyone cites Designing Data-Intensive Applications. It’s on the reading list of every serious engineering team. Engineers drop it in interviews. CTOs reference it in system design discussions. But most people read it once, nod along, and move on without internalizing what the first chapter is actually saying.
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There’s a type of cognitive overhead that engineers have normalized so completely they stopped noticing it.
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Most teams add streaming to their AI products because it feels faster.
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Every company I’ve worked with has the same problem dressed in different clothes.
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Traditional SaaS has a comforting property: infrastructure costs are largely fixed.
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There’s an idea that circulates in AI engineering circles called “caveman prompting.” The premise: write your instructions in stripped-down, telegraphic English — almost no grammar, no courtesy, just the bare intent — and the model will still deliver.
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Everyone tells you to build the moat.
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Getting the architecture right is necessary.
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The previous chapter made the case for workflows.
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Agents are everywhere in the AI conversation right now.
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Every week there’s a new framework, a new model, a new tool that promises to change how you build AI products.
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Most developers learn recursion by memorizing examples.
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Most AI products look great in a demo.
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Most people read a problem looking for what they need to do.
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Most teams adopt event-driven architecture because someone said it scales.
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