The majority of questions in mission-critical industries are subjective, challenging the notion that they only require factual answers.

Candidates who answer questions easily tend to be better engineers, but there are also false negatives where great engineers may struggle with questions.

If your answers to foundational startup questions are complicated, it may indicate a lack of focus; clarity in these areas is essential for progress.

In a crisis, you must make principle-based decisions rather than data-driven ones, as the situation often lacks clear data.

The technical interview process is flawed; it focuses on memorizing riddles rather than assessing real job skills.

Asking easier interview questions can be more predictive of a candidate's success than harder questions, as it reveals both the correctness of the answer and the candidate's problem-solving process.

The unique human ability to determine objectives and ask the right questions remains essential, even as AI takes on more tasks.

The challenge of achieving truth with large language models is a contentious topic in the industry, especially in domains where definitive answers exist, like math and coding.

Founders should seek ground truth answers from customers rather than relying on authority figures for validation of their ideas. Investors often misunderstand that founders need ground truth to validate their ideas, rather than just applying solutions from one context to another.