AI Agents in Enterprise Workflows: 5 Integration Patterns That Actually Work

Описание и применение

<p>Most AI agent demos die on contact with production. Not because the model is weak, but because the <em>integration</em> was an afterthought: no bounded scope, no enforced permissions, no durable state, no evaluation beyond "looks good to me."</p> <p>This post covers five integration patterns that separate agents surviving in production from agents stuck in demo purgatory. Each pattern is technology-agnostic — it applies whether you build on LangGraph, CrewAI, AutoGen, or plain API calls.</p> <p>I expanded these patterns into a full implementation guide with checklists here: <a href="https:/

Задача

<p>Most AI agent demos die on contact with production. Not because the model is weak, but because the <em>integration</em> was an afterthought: no bounded scope, no enforced permissions, no durable state, no evaluation beyond "looks good to me."</p> <p>This post covers five integration patterns that separate agents surviving in production from agents stuck in demo purgatory. Each pattern is technology-agnostic — it applies whether you build on LangGraph, CrewAI, AutoGen, or plain API calls.</p> <p>I expanded these patterns into a full implementation guide with checklists here: <a href="https:/

Результат

<p>Most AI agent demos die on contact with production. Not because the model is weak, but because the <em>integration</em> was an afterthought: no bounded scope, no enforced permissions, no durable state, no evaluation beyond "looks good to me."</p> <p>This post covers five integration patterns that separate agents surviving in production from agents stuck in demo purgatory. Each pattern is technology-agnostic — it applies whether you build on LangGraph, CrewAI, AutoGen, or plain API calls.</p> <p>I expanded these patterns into a full implementation guide with checklists here: <a href="https:/

Доказательства

AI Agents in Enterprise Workflows: 5 Integration Patterns That Actually Work

Источник