AI Strategy
AI strategy is the plan for how an organization will use artificial intelligence to achieve specific business outcomes—and equally, what it will not use AI for. A real AI strategy answers concrete questions: which workflows get automated first, where human judgment stays in the loop, how you measure ROI, what infrastructure you need, and who owns the results. Most of what passes for AI strategy in 2025 is vendor selection dressed up as vision. Choosing between OpenAI and Anthropic is a procurement decision, not a strategy. Strategy is deciding that your competitive advantage depends on proprietary data assets and therefore you will invest in custom models over SaaS tools—or deciding the opposite and moving fast with off-the-shelf solutions because speed to market matters more than differentiation. The hard part is not identifying where AI could help. It is sequencing investments so early wins fund later bets.
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Gravity Wells
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Fine-Tuning
Fine-tuning continues training a pretrained language model on a smaller, task-specific dataset so it internalizes particular behaviors, styles, or domain...
Zero-Shot Prompting
Zero-shot prompting is the most basic form of AI interaction where questions are posed without any examples or guidance, relying entirely on the model’s...