Why It Is So Hard To Build Real AI Agents?

Agents, Agents, Agents, everywhere I look I see people talking about agents or agentic AI. Yes, it is a very cool thing, but we are yet to justify the costing and scaling. Most of the agents I see around have almost ZERO (or minimal) impact on real businesses. This doesn’t mean that all the productionized agents are bad, but a lot of them are BAD.

Most agents today either:

1. Work only as flashy POCs that collapse in the wild, or
2. Actually run in production but deliver almost zero business value.

So, today we will try to understand, why it is so hard to get the agent work in the first place and then actual business impact of these agents.

Table Of Contents

• Introduction
• Not Every Problem Needs Agents
• Agentic AI POC Don’t Scale Well
• Justifying Agentic Cost At Organization Level Is Very Hard
• Building Reliable Agents Is Super Hard
• Why Things Like LangChain Are So Hard to Get Right?
• End-2-end AI Agents Problems

Introduction

The other day I was sitting with my wife while she was on a meeting. I overheard her boss talking about rolling out AI across the whole company. Apparently, they already have their own LLM — some fine-tuned version of DeepSeek or LLaMA — and now they’re planning to add a reasoning…