Big problems paralyze. Small steps liberate.
When facing a complex AI implementation, your mind races to the finish line. You see the grand vision, the complete transformation, the perfect end state.
But that’s exactly what holds you back.
The most successful AI adopters think in pieces. They break down massive challenges into bite-sized chunks that can be tackled one at a time.
A chatbot becomes:
– One conversation flow
– A single use case
– Three test users
– Five training examples
A recommendation engine starts as:
– One product category
– Basic collaborative filtering
– Manual oversight
– Weekly refinements
This approach isn’t just easier—it’s smarter.
Small pieces mean:
– Faster feedback
– Lower risk
– Clearer metrics
– Easier adjustments
– Earlier wins
The giants of AI—Google, OpenAI, DeepMind—all started with pieces. They mastered the small before tackling the big.
Your next AI project isn’t a mountain to climb. It’s a series of steps to take.
What’s your first piece?
