There’s a belief circulating in AI circles right now that a cleverly written prompt is proprietary gold. That if you can coax the right output from a model, you’ve created something defensible.
I get the instinct. When something works, and nobody else seems to have figured it out yet, it feels like IP. But that feeling won’t last. Not because prompts aren’t useful, but because they’re legible, replicable, and quite disposable.
Prompts at their core are specs. They describe what you want a model to do, given a certain input and output shape. You write them in English, wire them into some UX or tooling, and if you’re lucky, the system does what you hoped it would.
But we’ve seen this pattern before. Every generation of software development starts with hand-tuned instructions, then moves toward abstraction and automation.
First, we wrote in binary. Then came assembly. Then C. Then Python. We built compilers and interpreters that took your vague intent and optimized it into something performant.
We’re about to hit the same inflection point with LLMs.
Tools like DSPy are already acting like early compilers, taking high-level intent and generating prompt graphs, optimizing them over time. With Selvedge, I’ve been exploring what it means to treat prompts not as text but as composable programs. Structured, typed, and abstracted from the model itself. The system handles the orchestration — which model, which format, which chain — based on the spec.
This is where prompts as a moat break down. If the compiler is doing the hard work, the prompt itself isn’t the moat. It’s a temporary interface, a layer that’ll be rewritten, tuned, or discarded automatically based on what the developer wants to do.
So what actually compounds?
Usage. Feedback loops. Distribution. You build defensibility by owning the layer where users express intent — not the syntax of that expression. The edge won’t come from the prompt itself, but from the infrastructure that improves with every interaction.
We’re moving from being prompt authors to becoming compiler designers. From crafting clever phrasing to building systems that know how to reason backward from a goal. The moat, then, isn’t the instruction at all. It’s the interface.
Prompts are just the starting point. The leverage lives in what you do after the user speaks.
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If you have any questions or thoughts, don't hesitate to reach out. You can find me as @viksit on Twitter.