When you're plugging an LLM agent into an external API, you have three reasonable patterns: hand-rolled HTTP, AgentKit's action provider model, or LangChain's tool calling. They all work. They produce identical outputs against the same input.

So which one should you actually use?

I built the exact same agent three different ways — answering the same Kelly Criterion question — and the answer to "which one" depends on your stack, your team, and (most underrated) your wallet model. Here's the honest comparison.

The test case

Question: "I have a 55% win rate, $150 average win, $100 average loss. What's my Kelly fraction?"

Answer: f* = 17.5% (full Kelly), or 8.75% (half-Kelly — what most quant funds actually use).

The math doesn't care which integration computes it.…