Agent Architecture Articles
33 articles · Page 1 of 3
How to Build Ambient AI Agents for Always-On CX
Most AI agents wait for prompts. Ambient agents watch event streams and act first. Here's how to build always-on CX intelligence that catches problems before customers notice them.
Managed Agents in 2026: Three Runtimes, Three Trade-Offs
Google, Anthropic, and OpenAI all shipped 'managed agents' in May 2026, and they mean completely different things. Here's what each runtime trades away for CX teams.
How to Build Agent Interrupt and Approval Checkpoints
How to pause an AI agent before high-stakes actions, persist full state through the approval window, and resume cleanly. Covers interrupt gates, approval queues, checkpointing, and EU AI Act compliance for production CX agents.
Structured Outputs: Make Your AI Agent Stop Guessing
JSON mode isn't enough. Learn how constrained decoding, Zod schema validation, and validator-retry patterns cut agent parsing failures in production.
Pre-Execute Tool Calls to Cut Agent Latency 48%
Sequential tool calls quietly kill your agent's response time. PASTE shows you can pre-execute likely tool calls during LLM thinking time and cut latency 48% without touching your model.
How AG-UI Connects AI Agents to Any Frontend
AG-UI is the open event protocol that connects AI agent backends to any frontend. Here's how it works, why the protocol stack now has three layers, and how to wire it into a real CX agent.
Your CX Agent Crashes Mid-Task. Here's the Fix.
When your CX agent crashes mid-refund or mid-booking, the customer is stuck. Durable execution guarantees long-running agent tasks survive failures. Here's how to build it.
Your Agent Is Already a State Machine. Make It Explicit.
Every production AI agent is secretly a state machine. Making it explicit gives you checkpointing, testable paths, and observable state transitions -- without rewriting your agent logic.
Why CX Agents Fail Between Conversations
Your AI agent handles the call perfectly and still fails your customer. The problem isn't the conversation -- it's everything that happens after it. Here's how async task queues fix the gap.
Multi-Agent Systems Don't Fail at Reasoning. They Fail at Handoff.
Multi-agent systems don't fail at reasoning. They fail at handoff. Command objects, memory transfer, and the 8-10 handoff cliff, plus the telemetry that catches drift.
Everyone Benchmarks Opus. Your Chatbot Runs on Haiku.
Haiku 4.5, GPT-5 Mini, Gemini Flash at the $1/MTok tier that powers CX. Tool-call accuracy, first-token latency, structured-output reliability, blended cost math.
Your Agent Should Use Three Models, Not One
Production CX agents route tasks by difficulty, not brand loyalty. The planner/router/summarizer pattern, a concrete rubric, support-deflection cost math, and the failure modes nobody warns you about.
Learn Agentic AI
Weekly. Patterns for shipping agents that work — MCP, scorecards, regression tests, prompts, model comparisons.
