For years managers have been encouraged to candidly praise and criticize just about everything workers do. But it turns out that feedback does not help employees thrive. First, research shows that people can’t reliably rate the performance of others: More than 50% of your rating of someone reflects your characteristics, not hers. Second, neuroscience reveals that criticism provokes the brain’s “fight or flight” response and inhibits learning. Last, excellence looks different for each individual, so it can’t be defined in advance and transferred from one person to another. It’s also not the opposite of failure. Managers will never produce great performance by identifying what they think is failure and telling people how to correct it. Instead, when managers see a great outcome, they should turn to the person who created it, say, “Yes! That!,” and share their impression of why it was a success. Neuroscience shows that we grow most when people focus on our strengths. Learning rests on our grasp of what we’re doing well, not what we’re doing poorly, and certainly not on someone else’s sense of what we’re doing poorly.
Leadership fails, leadership failures, leaders fail
Leadership fails because leaders fail to connect with each team member in a meaningful way. Leadership failures can have a profound effect on the company.
When benchmarks go bad - what I learned from measuring performance wrong - Holly Cummins
The world of performance analysis is littered with flawed claims, cognitive biases, dangerous intuitions, and beguiling fallacies. Sadly…
(PDF) Leadership Failure in the Eyes of Subordinates: Perception, Antecedents, and Consequences *
PDF | Effective leaders and leadership behaviors and practices are well-researched areas in the domain of leadership and management. However,... | Find, read and cite all the research you need on ResearchGate
Michael Baym on Twitter / X
Remember that you, by definition, cannot distinguish between a good idea and a failure of your own knowledge, judgement, or taste. This is why external (ideally expert) feedback is crucial— Michael Baym (@baym) March 25, 2026
Why Good Managers Are So Rare
Gallup data shows they have a combination of hard-to-teach traits.
Top Performers Have a Superpower: Happiness
Employee well-being and happiness are surprisingly powerful predictors of performance.
I work, I think? - Annotated
How AI may quietly dismantle the feedback loop that turns inexperienced people into competent ones, and why my work matters to me.
Eliciting Advice Instead of Feedback Improves Developmental Input
Most organizations encourage employees to provide feedback to one another to support learning, personal growth, and career advancement. However, employee feedback often fails to improve performance because it lacks concrete, specific guidance. We provide a temporal explanation for why workplace input processes routinely fail to produce valuable and concrete developmental insights: they are insufficiently focused on the future. In this paper, we theorize and demonstrate that encouraging input providers to think about the future leads them to produce more concrete developmental input. Across a large scale, preregistered field experiment (n = 27,432 comments) and two laboratory studies (n = 806), people provide more concrete and actionable developmental input when they are prompted to provide future-looking “advice” rather than “feedback,” a common method of soliciting input in organizations. The effect of soliciting advice on input concreteness was mediated by providers’ future focus. Moreover, in a follow-up study, such concrete input was assessed by independent raters as more useful. These findings highlight the role of temporal orientation in driving the content of developmental input. In doing so, our data suggest that individuals and organizations have the potential to promote higher-quality developmental input by attending to the temporal orientation that their input systems encourage. This paper was accepted by Isabel Fernandez-Mateo, organizations. Funding: Funding for the laboratory experiments was provided by Harvard Business School. Supplemental Material: The supplementary appendix and data files are available at https://doi.org/10.1287/mnsc.2022.03207 .
What Not to Do When You’re Trying to Motivate Your Team
People ultimately choose to be motivated — when to give their best, go the extra mile, and offer radical ideas. The only thing leaders can do is shape the conditions under which others do, or don’t, choose to be motivated. Unfortunately, too few managers understand this, and so there is a gap between managers’ efforts and the results they’re getting. Three of the most offensive forms of “motivating” — drive-by praise, making stuff up, and guilt gratitude — can actually make employees feel less appreciated and erode their trust in a leader. The common shortfall among these approaches is that they all serve the leader giving the praise, not the recipient. If you want to direct your good intentions into more-meaningful expressions of recognition, consider these alternatives: Ask your employee how they accomplished their goal, explain how their efforts are contributing to the broader organization, and acknowledge the challenges they overcame to make such a valuable contribution.
Human learning is an understudied but promising lever for boosting human–AI synergy
Humans collaborating with AI hold the promise of achieving superior outcomes compared to either acting alone (i.e., human–AI synergy). However, the conditions that facilitate such synergy when humans are advised by AI are not well understood. A recent meta-analysis showed that, on average, human–AI combinations do not outperform the better individual agent. We argue that this pessimistic conclusion arises from insufficient attention to human learning in experimental designs. To substantiate this claim, we reanalyzed all 74 studies included in the original meta-analysis and found that most previous research overlooked design features that foster human learning (e.g., outcome feedback to participants). Our reanalysis further revealed that studies providing outcome feedback show tentatively higher synergy than those without outcome feedback. Crucially, feedback paired with AI explanations was associated with positive synergy, while explanations without feedback were associated with negative synergy—suggesting that explanations improve synergy mainly when humans can learn to verify the AI’s reliability through feedback. Our reanalysis suggests that the current literature underestimates the potential of human–AI collaboration because it predominantly relies on paradigms that do not facilitate human learning, thus hindering humans from effectively adapting their collaboration strategies. However, experiments directly varying learning opportunities are needed for stronger, causal conclusions. We advocate for a paradigm shift in human–AI interaction research that explicitly addresses human learning and thus enhances our understanding of and support for successful human–AI collaboration.
AI-Generated “Workslop” Is Destroying Productivity
Despite a surge in generative AI use across workplaces, most companies are seeing little measurable ROI. One possible reason is because AI tools are being used to produce “workslop”—content that appears polished but lacks real substance, offloading cognitive labor onto coworkers. Research from BetterUp Labs and Stanford found that 41% of workers have encountered such AI-generated output, costing nearly two hours of rework per instance and creating downstream productivity, trust, and collaboration issues. Leaders need to consider how they may be encouraging indiscriminate organizational mandates and offering too little guidance on quality standards. To counteract workslop, leaders should model purposeful AI use, establish clear norms, and encourage a “pilot mindset” that combines high agency with optimism—promoting AI as a collaborative tool, not a shortcut.
Appearing Productive in The Workplace — No One's Happy
AI can produce work that looks expert without being expert. The failure arrives in two shapes, and both are reshaping the workplace.
Appearing Productive in The Workplace — No One's Happy
AI can produce work that looks expert without being expert. The failure arrives in two shapes, and both are reshaping the workplace.
Someone’s underperforming. Now what?
14 questions to ask an employee who’s struggling during your next one-on-one meeting so you can figure out how to best help. Someone’s slipping. You see it. You feel it. You’re not on the same page…
Influence without authority — Gabriel Valdivia
Some of the most influential designers I’ve worked with had no direct reports. They didn't spend their days assigning work, running performance reviews, or deciding who got promoted. Yet they could change the direction of a project, raise the quality bar of a team, and sometimes change the strategy for the entire company. Individual contributors can develop influence by giving people reasons to trust their judgment, then finding ways for that judgment to travel beyond the things they personally make.
Why Your Brain Needs More Downtime
Research on naps, meditation, nature walks and the habits of exceptional artists and athletes reveals how mental breaks increase productivity, replenish attention, solidify memories and encourage creativity
