The discipline of clarity
Where structure meets intelligence. The craft of designing prompts, curating context, and orchestrating AI systems that think the way you need them to.
Core tenets
Every token carries weight. Organize context hierarchically—what matters most goes first. Clarity emerges from intentional arrangement.
Vague prompts yield vague outputs. Specify format, tone, constraints, and examples. The model can only follow what you make explicit.
Context engineering is iterative. Test, observe, adjust. Each revision sharpens the signal. Treat prompts as living artifacts.
"The difference between a mediocre AI interaction and an exceptional one often comes down to a few hundred carefully chosen words."
— Context Engineering Manifesto
Methodology
Design prompts as systems—roles, constraints, output formats, few-shot examples. Build reusable templates that scale across use cases.
Every model has limits. Prioritize, compress, and sequence information. Know what to include—and what to leave out.
Measure what matters. A/B test prompts. Collect failure modes. Context engineering improves through systematic feedback.