Powerful platform. Impossible expectations. Companies want veterans of a technology that hasn't been around long enough to have veterans.
Powerful tool. Impossible expectation. Companies want veterans of a technology that hasn't been around long enough to have veterans.
The experience paradox: Companies want veterans of a technology that hasn't been around long enough to have veterans.
Behind every impressive AI demo is a much harder question: Is there a real business underneath the technology?
The biggest challenge in Data Science isn’t building the model. It’s convincing the business that the model matters.
The biggest challenge in analytics isn’t building dashboards. It’s building confidence, clarity, and action.
Most stakeholders won’t criticize your dashboard. They’ll simply stop using it.
Most investors won’t say these things out loud. But they’re often the difference between getting funded and getting forgotten.
The next winners in AI may not be the companies with the smartest models. They may be the ones with the most compute.
The moment a company becomes “the next OpenAI” or “the next SpaceX,” it risks becoming forgettable.
Many organizations launch transformation initiatives to move faster. Ironically, that’s often what slows them down.
The market rarely rewards the company that looks safest. It rewards the company that stands for something specific.
