Intelligent commerce is shifting from clicks to agents, powered by a new trust stack across identity, provenance, privacy, and programmable payments. This blueprint shows how to build it with open standards.
Platform-native agents are here, OS-level companions are coming, and a real prompt-injection exploit just raised the security bar. This post distills what truly changed—and a practical playbook to adopt it safely.
A practical playbook for building machine-native products in the intention economy—make capabilities callable, discoverable, and governed. Covers interop (A2A/MCP), state-machine orchestration, evaluator-in-the-loop, and the metrics that matter.
Engineering playbook for deploying and governing agentic AI systems in the enterprise. Walks through use-cases, observability gaps, build-vs-buy math, KPIs, and the procurement checklist.
Discover how on-device LLMs are revolutionizing intelligent, personalized AI agents with enhanced privacy & speed. Explore innovative techniques like model quantization and speculative decoding that seamlessly blend edge and cloud computing.
Discover our comprehensive blueprint for building next-generation agentic AI workflows—designed for autonomous, multi-agent collaboration and dynamic decision-making. This guide details modular architectures, advanced reasoning techniques, and integrated
A production guide to semantic routing for LLM agents—architecture, thresholds, abstain logic, evaluation, and copy-ready implementation patterns that cut cost/latency without hurting success.
How Magentic-One’s multi-agent patterns evolved into AutoGen 0.4’s actor-model stack—covering architecture, event contracts, observability, and a pragmatic migration plan.
A practitioner’s blueprint to deploy LLM agents in contact centers—architecture, safety, RAG, metrics, and a 30/60/90 rollout that drives automation and lowers cost per contact.
A practical playbook to cut LLM calls—adaptive routing, one-shot multi-head prompts, deterministic tools, precise RAG, and caching—while protecting task success and user experience.
A production-ready design for implementing a conversational AI evaluation framework—data models, scoring pipeline, slice dashboards, CI gates, and canary rollout.
