After running out of Fable credits in a day on my max plan I started looking around for ways to trim down my token usage and came to the realization that all of the type spaghetti that opus wrote is probably eating up like 50-70% of my tokens.

A clean django project is probably 3-4x less code than the equivalent TS based service.

It made me consider dropping strict mode and defaulting to js for most simple things.

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jw1224 2 hours ago | parent | next [-]

Interesting, I've come to the opposite conclusion: a lack of types (or types that are only weakly enforced) costs me significantly more tokens in the long-run to maintain, and makes it far too easy for models to silently introduce bugs.

I run all my projects now in TypeScript with the strictest possible settings, including disabling `ts-ignore` markers.

(This would drive me absolutely insane, but my agents get over it pretty quickly!)

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kodama-lens 2 hours ago | parent | prev | next [-]

In a world where code generation is cheap, why use untyped languages? Types add confidence, stricter interfaces, and most likely a better runtime performance.

	▲	m_ke 2 hours ago \| parent [-]
		With agentic coding the costs of tokens compound with each message / tool call and etc. Having to load in and update large files makes things slower and way more expensive. Databricks actually just posted some of their own benchmarks on how harness alone impacts costs https://www.databricks.com/blog/benchmarking-coding-agents-d... simple things like passing more file context, model having to explore the code base at start of each session, writing comments or markdown docs ends up increasing, running into test / build issues can 3-10x your costs. PS: my code is still mostly TS and rust but I'm considering moving some of my annotations into .d.ts files and having them generated from runtime types (ala MonkeyType).

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IceDane 2 hours ago | parent | prev [-]

Why not just do like.. actual engineering, and stay in control of what the LLM builds?