You can be ambitious without the huge token bill. Here's how.
While advanced AI agents increase capability and token consumption, the rising cost is defensible only if the work they perform is genuinely new and valuable. The core strategy for cost control is not simply finding a cheaper model, but fundamentally redesigning the business workflow by eliminating unnecessary 'interoffice envelope' steps. By focusing on the desired business outcome, engineers can minimize handoffs and reserve expensive, frontier models for complex, exceptional cases, while using cheaper models for routine, deterministic tasks.
Key takeaways
-
Redesign the Workflow, Don't Just Buy an Agent
24:12
Before selecting a model, determine which work should exist at all. Start by defining the desired business outcome (e.g., an accurate quote) and map the most efficient path to achieve it, rather than simply automating the existing, often redundant, process.
-
Separate Value-Add Work from Administrative Overhead
26:40
Many existing enterprise steps (like summarizing requests for different departments) exist because previous systems lacked interoperability. Identifying and eliminating this 'admin work' can drastically shorten the workflow and reduce token consumption.
-
Match the Model to the Task Complexity
Not all work requires the highest intelligence. Reserve expensive, frontier models for the 1-5% of challenging, exceptional cases. Use cheaper, open-weights models for routine, deterministic tasks (e.g., calling a CRM or applying known pricing rules).
-
Implement Evaluation (Evals) for Reliability
To ensure a redesigned process works, implement rigorous evaluation (Evals) to check if the agent's output is not just 'approximately right,' but factually correct and meets business requirements. Evals are a critical human skill for maintaining quality.