Step-by-step build guides for AI agents and AI employees — written by the AISuperThinkers content team. Start with a supporting guide, work up to the full playbook.
A map of every seam in an agent's request path where a token is spent twice — exact-match and semantic caching, request coalescing, and idempotency-keyed deduplication — with the invalidation rules and failure modes that keep the savings real.
The engineering playbook for cutting AI agent token costs: measure cost per completed task, set a token budget, route on evaluations, and treat the context window as a budget — not a feature.
Dify and n8n are both toolkits, not toys — the real question is where each lets a serious builder reach the primitives. A head-to-head on control, extensibility, and exit for architects past the beginner ceiling.
