Prompt Caching Pricing 2026: Anthropic, OpenAI, Google, and the Savings Math
Prompt caching pricing varies a lot across providers in 2026. The numbers, the savings math, and how to architect for cache hits.
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Prompt caching pricing varies a lot across providers in 2026. The numbers, the savings math, and how to architect for cache hits.
Sub-second agent decisions need explicit budgets at every step. The 2026 latency-engineering patterns from real production deployments.
A New York hedge-fund team uses AutoGen 0.5 to coordinate research analyst agents on equities. The team-of-experts pattern in finance and what made it ship.
Domain vocabulary breaks generic embeddings. The 2026 patterns for medical, legal, and financial RAG that actually retrieve the right docs.
End-to-end performance profiling across LLM, retrieval, tool, and UI layers. The 2026 patterns for finding the real bottleneck in AI pipelines.
How production AI agents actually decide in 2026 — from cheap heuristics to Bayesian inference to utility-based scoring, and where each one wins.
Telling the model what not to do is its own discipline. The 2026 patterns for negative prompts, constraint engineering, and safe behavior.
By 2026, sub-10B models beat 2024-era GPT-4 on most benchmarks. The Phi-4, Gemma-3, and SmolLM-3 family compared head-to-head.
Enterprise CIO Guide perspective on Vapi 2.0 added a visual workflow builder, multi-agent 'squads', and OpenTelemetry-grade observability — closing real gaps for production teams.
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