The primary value of custom GPTs is creating a consistent, pre-trained context for recurring tasks. This eliminates the need to re-prompt with the same background information and allows for the "productization" of a specific function to be shared with a team or the public.
While using a second LLM for verification is a preliminary step, it does not replace human responsibility. Leaders must enforce a culture of slowing down for manual verification and critical thinking to avoid publishing low-quality, AI-generated "slop".
To determine if an employee critically engaged with AI-generated content, bypass reading the lengthy document. Instead, directly question them on its substance. Their ability to confidently defend, elaborate on, and explain the material is the true test of their understanding and ownership of the work.
While AI is capable of disrupting most knowledge work now, large enterprises move too slowly to implement it. Widespread job disruption will be delayed by organizational friction and slow adoption, not technological limitations, even if AGI were achieved today.
Agencies can no longer rely on a single, lasting competitive advantage. AI commoditizes services on a rapid cycle. The only viable strategy is to operate on the leading edge, constantly seeking the next temporary advantage, with the understanding that it will likely be obsolete within 12-18 months.
The primary source of employee burnout in the AI transition isn't just an increased workload. It's the friction created when a small group of highly-skilled AI adopters dramatically outpaces their colleagues, leading to resentment and an unsustainable workload for the high-performers.
The most durable skills in the AI era are emotional intelligence, interpersonal communication, and critical thinking. It boils down to knowing what questions to ask the AI, what to do with the answers it provides, and how to learn from it, effectively framing problems for the machine to solve.
The most impactful "superpower" for a leader isn't a tool, but a profound understanding of AI's current capabilities and near-term trajectory. This awareness is the true catalyst for urgency, inspiring the necessary vision, investment, and change management to navigate the AI transition effectively.
While detailed prompts are useful, starting with simple, open-ended prompts can unlock more creative and strategic responses from AI models. Experimenting with different levels of prompt detail across various models often yields surprising and superior results.
When AI labs release new models, they may de-prioritize certain skills like writing to focus on others like agentic capabilities. This causes noticeable shifts in tone and quality, forcing users to re-evaluate and adjust their custom instructions for GPTs and other AI tools.
The traditional wisdom to "build what's core" to your business is becoming obsolete for AI. The immense cost and rapid advancement of foundational models by major labs mean most companies are better off buying or partnering for core AI capabilities rather than attempting to build them in-house.