Agent-to-Agent (A2A) protocol — the spec and the Go client
Google's A2A spec standardises how agents talk to other agents (not just tools). The Go client is small; the conceptual shift is what matters.
#Agents
AI agents are autonomous software components that perceive their environment, reason about goals, and take actions without continuous human direction. These posts cover agent design patterns, orchestration strategies, latency budgets, and the operational challenges of running agentic systems at production scale.
4 posts tagged with agents. ← All posts
Google Cloud's 12 agent design patterns — mapped to real...
Google publishes a 12-pattern taxonomy for agent design. Most of them have direct corollaries in production code; one or two are best ignored. The mapping I've used.
Cost-aware agent dispatch — when the cheap agent is enough
Not every query needs the production agent. A cost-aware dispatcher decides whether to route to the cheap-and-fast agent or the expensive-and-thorough one. Same UX, dramatically lower bill.
Latency-aware agent dispatch — picking by SLO, not by...
Two agents can do the same job. One takes 200ms; the other takes 5 seconds. Pick by user-facing SLO, not by which agent is "better." The dispatcher pattern.
All posts on this site are written by Pratik Dhanave, an Agentic AI Architect with 7+ years building production distributed systems, multi-agent AI platforms, and cloud-native infrastructure. About the author → Each article includes working code, architecture diagrams, and references to the specific frameworks and standards discussed. Browse all posts or explore related topics using the tag cloud above.