Cost & Evaluation
How should I compare build-versus-buy decisions for a workflow engine to power AI agents?
Compare total cost of ownership by modeling engineering time for building and maintaining a custom engine against platform fees and integration effort. Include hidden costs like on-call burden, state storage, and upgrade cycles for both paths. Factor in the opportunity cost of delaying agent features while building infrastructure. A custom engine can be tailored exactly, but underestimating ongoing maintenance is the most common miscalculation.
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- Cost & Evaluation
How should I scope a proof of concept for a durable agent execution platform?
Focus a proof of concept on resilience over scale to reveal true platform fit for agentic workflows.
- Cost & Evaluation
What key metrics should I track during a durable execution proof of concept?
Measure recovery correctness and operational overhead reductions, not agent logic accuracy, when evaluating durable execution.
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What cost categories do teams often overlook when planning to run a durable execution platform in production?
Engineering for state design, upgrade testing, and on-call triage often outweigh infrastructure costs in durable systems.