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Managing AI Coding Costs at Scale

databricks.com

1–10 of 266 posts

Re: Managing AI Coding Costs at Scale

#4
post #2

Really? Because removing it from my company has saved us over 2 million a year and we were able to speed up processing. The chargeback model for databricks is predatory at best.

I think you’ve misunderstood the article. It’s about how Databricks reduced their own costs, not about how adopting Databricks will reduce anyone else’s costs.

Re: Managing AI Coding Costs at Scale

#8
This approach seems fundamentally predicated on being able to evaluate coding agents on your own code by having domain specific evals. With that knowledge, you can trust the routing logic is actually improving/maintaining perf while reducing costs.

Without the insight into agent performance, any changes like this feel like a gamble to save $$ at the cost of developer productivity

I'm actually working on building generic repo-specific benchmarks at https://stet.sh ;)

Re: Managing AI Coding Costs at Scale

#10
These seem like the obvious tweaks akin to "using a cheaper hosting platform". I think the real savings come from careful context control for programmatic agents, careful tool awareness and usage to reduce thrashing, distilling workflows into deterministic processes and, moat importantly, adding friction and boundaries for non-technical users who tend to burn tokens making insane asks like "analyze all documents and give me a summary".
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