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The true cost of the prompt
A developer asks for a change. Behind the scenes, agents read files, call models, run tests, and try again — each step adding cost and potentially moving sensitive context. Our white paper traces that hidden workload and explains the controls platform teams need as agentic coding takes over.
What you’ll learn
The token invoice tells you what you spent. But it can’t tell you whether the work was worth it. This paper connects model choice, data movement, and operating cost, giving platform and engineering leaders a practical basis for deciding how agentic coding should run in production.
- Follow the work behind a prompt to see where assistant-era controls leave gaps in agentic workflows.
- Explore how local and frontier models can work together, with policy governing which requests can go where.
- Find the measures that connect inference spending to completed work, including retries, fallbacks, and task success.
- Account for the maintenance and engineering effort that’s easy to miss in a local-inference business case.
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Fill in the form to get the paper and use it to review your agentic coding architecture.
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