Most teams build AI workflows backwards – focusing on tech instead of human problems. Start with daily pain points, map decision bottlenecks, build small automations that save minutes.
The story
Most development teams I work with are building AI workflows wrong.
They’re focused on the tech stack instead of the human workflow. Big mistake.
Here’s what actually works:
Start with your people’s daily pain points, not the AI tool. I’ve seen teams spend months perfecting a chatbot that nobody uses because it doesn’t solve a real problem.
Map the human decision points first. Where does your team get stuck? Where do they waste time on repetitive tasks? That’s where AI belongs.
Build small, test fast, learn faster. The teams crushing it aren’t building massive AI systems. They’re creating tiny automations that save 20 minutes here, an hour there. Those minutes add up to massive efficiency gains.
Train your humans, not just your models. The best AI workflows fail when people don’t understand how to work with them. I spend more time on change management than coding.
Most leaders think they need an AI expert. What they actually need is someone who understands both the technology AND how teams really work. A player-coach who can build alongside your developers while multiplying their abilities.
The companies winning with AI aren’t the ones with the fanciest tools. They’re the ones who figured out how to make AI feel invisible to their users while solving visible problems.
Your team doesn’t need another AI consultant who talks theory. They need someone who can roll up their sleeves and help them build workflows that actually work.
The difference between AI that impresses and AI that transforms? Understanding humans first, technology second.
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