Most executives know the pre-mortem. Very few use it. The concept, developed by psychologist Gary Klein and popularized in organizational strategy circles by Daniel Kahneman, is disarmingly simple. Before committing to a major decision, you imagine it is twelve months in the future and the initiative has failed catastrophically. You then work backward to explain what went wrong. The exercise forces a team to surface its private doubts, challenge its shared assumptions, and co

By the time you bring a decision to a conversation, you have usually already made up your mind. You may not realize it. The situation may feel genuinely open, the options unresolved. But in most cases, the moment you begin describing a problem to another person, you have already climbed a cognitive staircase that began with a selective observation and ended with a firmly held conclusion, moving through layers of interpretation, assumption, and belief so quickly that the proce

Six months ago, I published a ranked matrix of the ten issues most likely to shape the business environment in 2026. This mid-year update recalibrates that ranking against hard data: the IMF's April World Economic Outlook, the April CPI release, current markets, and post-SCOTUS tariff reality. The numbers have moved. More importantly, the pattern beneath them has sharpened. Let me give you the headline figures, then tell you what they actually mean for how you run your organi

We have reached the point where access to artificial intelligence is no longer the scarce resource. Capable AI models are available to nearly everyone, competent drafts generate themselves by the paragraph, and the marginal cost of producing a passable piece of work has fallen close to zero. In that environment the advantage shifts to a quieter and more demanding capability, which is the discipline of directing intelligence toward outcomes that matter. That discipline is the

There is a revealing piece of recent research making its way through leadership circles. When AI systems are given distinct roles, organizational structure, and defined responsibilities within a team, they consistently outperform AI systems that operate without that structure. The finding sounds almost mundane until you sit with what it actually implies: the same organizational principles that make human teams effective also make human-AI teams effective. We are not, in other

Most executives and coaches who use AI tools think of their conversation history as something like a search history: transient, forgettable, and replaceable. That assumption is worth revisiting. Over the past year, many of us have done something more significant inside AI platforms than simple lookups. We have worked through complex coaching frameworks, drafted nuanced client communications, developed proprietary methodologies, refined our voice and reasoning across hundreds

By the middle of any given year, a senior executive has made hundreds of decisions, navigated dozens of difficult conversations, and cycled through enough strategic pivots to fill a casebook. They have also, in all likelihood, spent a significant portion of that time working alongside an AI assistant: drafting communications, thinking through problems, preparing for high-stakes meetings, and processing the complexity of organizational life in real time. What most executives h

Every few years, a technology arrives that leaders treat as a shortcut around the hard problems of organizational life. AI is not the first such technology, but it may be the most seductive. Unlike enterprise software or automation, AI feels cognitive. It reasons. It drafts. It synthesizes. And so executives are deploying it into their teams with the implicit assumption that better tools produce better outcomes. That assumption is worth examining closely, because in teams whe