Learn practical tactics to spot and stop bullshit in meetings, data, and AI outputs, so leaders can make evidence-based decisions and protect their teams from wasted effort.
Bullshit spreads because it's cheap to produce and expensive to refute, and leaders who let it flourish waste huge amounts of energy on defending empty claims. The essay starts by quantifying that waste and then shows why a disciplined filter is a leadership imperative. It frames BS as a cultural toxin that erodes psychological safety and decision quality.
The piece breaks down six flavors of nonsense-philosophical, linguistic, analytical, technological, organizational, and professional-illustrating each with vivid examples like "quantum-ready blockchain solutions" and AI hallucinations that cite bogus accuracy rates. It explains how cognitive biases, the chimp brain, and power dynamics make even smart engineers vulnerable, turning hype into hidden costs.
Practical habits follow: treat every claim as a hypothesis, apply the SIFT method (stop, investigate source, find alternatives, trace context), build data literacy to read numbers critically, and embed friction in decision processes. Leaders are urged to cultivate psychological safety so dissent can surface, replace buzzwords with measurable outcomes, and keep explanations simple enough to fit on a two-page memo. The goal is a team that catches BS early, asks "why," and backs decisions with real evidence rather than glossy jargon.
Check out the full stdlib collection for more frameworks, templates, and guides to accelerate your technical leadership journey.