Stop Building AI Agents Until You Watch This (When They Actually Make Sense)

Описание: Everyone is building AI agents right now—but most of them shouldn’t exist.

In this video, I break down what AI agents actually are, when they make sense to build, and when a simple script or workflow is objectively better.

After building real production agents—from token scanners and research agents to fully autonomous execution loops—I’ve learned the hard truth: agents are powerful, but they’re also overused, fragile, and often unnecessary.

This video covers:

• The difference between scripts, workflows, and true agents
• When agents create real leverage vs artificial complexity
• The biggest mistake developers make when building agents
• Why most “agent startups” are just wrappers with extra steps
• The architecture behind effective, production-grade agents
• How to decide if you actually need an agent or not

We’ll also look at real-world examples of agent systems, including research agents, trading agents, and autonomous execution loops—and why most fail.

If you're building with Claude, GPT, OpenAI tools, or open-source frameworks, understanding this will save you months of wasted effort.

Agents aren’t magic. They’re just software with decision loops.

The advantage comes from using them at the right abstraction layer.