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I had just landed my first real (non-HR) job at an international company, fresh out of university, full of ambition, and eager to prove myself. I loved the work, worked hard, stayed late, and genuinely believed I was making my mark. So when I was called into a meeting with HR one sunny Wednesday morning, I came in smiling, half-expecting praise. Surely, my efforts had been noticed. Maybe even a promotion was coming. I walked into a glass-walled meeting room to find Susan from HR sitting alone, visibly uncomfortable behind her laptop. After a few awkward pleasantries, she launched into a stream of corporate jargon about shifting priorities and evolving strategies. I nodded along, trying to connect the dots. Then it hit me. Susan . . . are you firing me? She nodded and hurriedly mumbled something about exit services. It wasnt just the layoffit was the series of faux pas that came with it. No manager present. No warning. No privacy. Just a rehearsed speech, a bad PowerPoint, and zero empathy. At the time, I didnt know better. But years later, working in HR myself, I looked back and saw it clearly: a masterclass in how not to handle people. Why are we so bad at layoffs? You could argue that this was two decades ago, and things must have improved since then. But have they? Consider the CEO of Better.com firing 900 employees (almost 15% of the workforce) over Zoom in 2021. Or Tesla’s 2024 mass layoffs, announced via a Sunday-night email revoking system access immediately. For all our talk about employee experience, empathy, and psychological safety, we still fail the most basic test: treating people like people. We know that business change is inevitable. Strategies must evolve. Restructuring is often necessary. Agility is a business imperative. But if layoffs are going to happen, and they will, there are better ways to handle them. More human ways. Heres how: 1. Minimize Uncertainty Employees dont need perfect certainty. They need honest, consistent communication. No one can work efficiently in the dark, and uncertainty breeds anxiety, rumors, and disengagement. One former colleague described his layoff experience as well-executed, empathetic, and matter-of fact. Why? Because employees were kept in the loop. The level of uncertainty was reduced right from the start. No surprises. No corridor gossip. Just timely, transparent updates from leadership and direct managers. 2. Communicate, Again, and Again In too many companies, strategic changes are discussed only at the top, never cascading down. This leads to confused employees who feel blindsided when change hits. A 2024 survey by PwC found that over half of employees feel theres too much change at work happening at once, and 44% dont understand why change is happening at all. Explain the why. Share the rationale. Communicate clearly, regularly, and with authenticity. A well-executed change management plan is key for an organization in transformation. Transparency, even when it means delivering bad news, is better than silence. Trust is built not by pretending everything is fine, but by communicating honestly and early. 3. Make Managers Accountable It often seems that HR gets blamed for delivering bad news. But layoffs are business decisions, not HR ones. So, where are the managers? Managers should be active participants in staffing decisions and responsible for how they are communicated. They know their teams best. They should be trained and empowered to lead through these moments, not hide behind HR. 4. Invest in Skills, Even During Uncertainty Ironically, companies tend to cut learning and development budgets when they need them most: during transformations. But investing in employee development during times of change builds trust and signals long-term commitment. Even if roles change (or disappear), the skills remain. Todays workforce is eager to grow. PwCs survey shows that workers want to upskill, and many are open to using tools like generative AI to work smarter. Companies should meet them halfway, with upskilling, internal talent marketplaces, and support for career mobility. 5. Address Employee Stress Proactively Restructuring and transformation efforts create emotional fallout. Left unaddressed, this stress turns into burnout, turnover, and long-term reputational damage. Leaders must create safe spaces where employees can speak openly without fear of negative consequences. Listening and feedback loops must be real. At Netflix, for example, a People over Process culture means daily, constructive feedback is encouraged and acted on. That only works when leadership is visible, responsive, and truly engaged. 6. Build Resilience Resilience isnt about powering through, its about giving people tools to adapt. That means helping managers lead through change and equipping teams with emotional agility, psychological safety, and the ability to thrive in ambiguity. 7. Support the Survivors, Too Layoffs dont end with the people who are let go. The employees who remain are left navigating a mix of relief, guilt, and fear. And they keep on wondering, Am I next? Whats really going on? Can I trust anything I hear? Typically, what is left behind is a stressed-out workforce, a collapsing sense of loyalty, and a culture of fear. To avoid this, companies must address the emotional toll on those who stay. Leaders should overcommunicate, set expectations clearly, and offer both honesty and reassurance. Let people know theres a plan and where they fit into it. In a world where constant change is the norm, how we change matters just as much as why we change. The goal should not be just speed. Agility without empathy is chaos. But when done right, paced, thoughtful, and human centered, it can actually build trust, not destroy it. There are more compassionate ways to run a business. We just have to choose them.
Category:
E-Commerce
The most successful leaders arent necessarily the loudest, the most visionary, or the ones with all the answers. Instead, they know what drives their actions and what triggers their reactions. They understand themselves and can read what others need with precision. Furthermore, they dont treat each person the same way. Instead, they tailor their approach to meet the needs of each individual or situation. These leaders go beyond possessing highly developed emotional intelligence. They become their best selves and help others do the same. Their skill is based on harnessing personality to promote personal and organizational success. But before we explore the power of personality intelligence, lets introduce the four styles every leader needs to understand. The Styles We will use birds as a simple way to help explain, remember, and apply the four styles. Eagles are confident, direct, and results-focused. Parrots are social, optimistic, and energizing. Doves are supportive, empathetic, and harmonious. Owls are logical, questioning, and precise. We all possess a mix of styles, but one or two typically stand out. Once you recognize these styles, you’ll start noticing them everywhere, from emails and meetings to how you lead with others. What Is Personality Intelligence? Think of personality intelligence (PIQ) as the development of self-awareness. Its not just knowing yourself. Its understanding how your natural style appears, interacts with others, and contributes to your success. Unlike emotional intelligence, which focuses on reading and managing emotions, personality intelligence shows how people with your style think, decide, communicate, and act. Your style forms a pattern of behavior, and that pattern affects the quality of your relationships and the results you achieve. Four Stages of Personality Intelligence Effective leaders progress through various stages on their journey to excellence. Understanding where you are today guides you in choosing what to focus on next. Level 1: The Unevolved StateThis is the starting point. At this stage, people react on autopilot, driven by their default style rather than the needs of the moment. Eagles charge ahead, but may bulldoze others in the name of efficiency. Parrots chase every new idea and can easily get off track. Doves seek harmony, but their desire to avoid conflict can prevent them from having difficult and crucial conversations. Owls focus on quality, but may get stuck in analysis paralysis and miss the moment to act. In this level, the style is in control, but its working against them, not for them. Level 2: The Typical StateThis is where most people live. At this stage in a leaders development, they understand their style and concentrate on their strengths. They are no longer on full autopilot, but pressure can still trip them up. At their best, eagles lead confidently. Parrots energize the team. Doves are nurturing, and Owls are meticulous. However, under stress, they revert to the Unevolved State of Level 1 where their strengths work against them. Level 3: The Master StateAt this stage, leaders master their style. They do so by balancing their strengths with traits opposite of their natural tendencies. Eagles temper confidence with humility. Parrots couple optimism with discernment. Doves pair kindness with candor. Owls blend logic with a dash of spontaneity. In the Master State, a leaders style becomes their professional superpower. They bring their best to every encounter and make the people around them better. Level 4: The Chameleon StateFew reach this level, but when they do, it becomes a game changer. At this stage, leaders dont just master their own style; they master all of them. When they need to rally the team, they energize their inner parrot. The eagle takes over when facing a tight deadline. The owl tunes in when tasks require precision. And when the moment calls for empathy, the dove is ready. And when they adapt, they do so with authenticity that fits the moment or the individual. This is the art of leading with personality intelligence. Why This Matters Now In todays world of hybrid workplaces, a multi-generational workforce, and rapidly changing technology, personality intelligence is more essential than ever. When leaders have highly developed personality intelligence, they can effectively lead anyone in any environment. If you want to retain your people, you need to know how to lead all of them, not just those who are similar to you. Leaders with strong personality intelligence dont just create an environment where they will succeed; they create one where everyone can thrive. They foster a fast-paced, goal-oriented space for eagles, an engaging and exciting culture for parrots, a supportive and helpful environment for doves, and a process-driven, quality-focused world for owls. Weve all heard it: People dont quit their company; they quit their boss. Lets flip that and say, people stay because of their boss. If youve ever reported to a self-aware leader who respects the style of their direct reports, Id bet you would have followed that leader anywhere. Thats the power of personality intelligence in action. Five Ways to Boost Your Personality Intelligence Heres your starting point for leveling up your leadership. 1. Own your styleDont just take a personality test and move on. Learn how your style influences your success, how you interact with others, and how you handle stress. Ask your team how they experience you when you’re at your bestand when you’re not. 2. Get fluent in all four stylesTrain yourself to recognize the styles in action. Does someone need time to reflect before making a decision? Youre likely dealing with an owl. Do they prioritize harmony within the team? You probably have a dove. Are they quick, confident, and competitive? Thats the eagle. Do they use stories, an excessive amount of exclamation points, and anecdotes in every staff meeting? Youre working with a parrot. 3. Practice conscious adaptationStyle-flexing isnt about being inauthentic. Its about choosing to speak someones language and meet them where they are. If youre an eagle presenting to owls, bring data. If you’re a parrot leading doves, slow down and check in. The more you adapt, the stronger the connection. 4. Build style-diverse teamsGreat teams aret made of clones of the leader. They are well-rounded, and their diverse styles create a balanced team. 5. Model personality intelligenceDiscuss the styles openly. Share what youre working on. When leaders demonstrate their personality intelligence, others follow. It creates a tone of trust, respect, and growth. The Bottom Line Personality intelligence gives leaders the edge they didnt realize they were missing. It boosts self-awareness and provides the tools to bring out the best in everyone they lead. It shifts communication from reactive to intentional, turns conflict into collaboration, and creates an environment where anyone, regardless of their style, can thrive. In a world where people are the true competitive advantage, personality intelligence is essential for leaders.
Category:
E-Commerce
Although AI is changing the media, how much it’s changing journalism is unclear. Most editorial policies forbid using AI to help write stories, and journalists typically don’t want the help anyway. But when consulting with editorial teams, I often point out that, even if you never publish a single word of AI-generated text, it still has a lot to offer as a research assistant. Well, that assertion might be a bit more questionable now that the Columbia Journalism Review has gone and published its own study about how AI tools performed in that role for some specific journalistic use cases. The result, according to CJR: AI can be a surprisingly uninformed researcher, and it might not even be a great summarizer, at least in some cases. Let me stress: CJR tested AI models in journalistic use cases, not generic ones. For summarization in particular, the toolsincluding ChatGPT, Claude, Perplexity, and Geminiwere asked to summarize transcripts and minutes from local government meetings, not articles or PowerPoints. So some of the results may go against intuition, but I also think it makes them much more useful: For artificial intelligence to be the force for workplace transformation as it’s often hyped to be, it needs to give helpful output in workplace-specific use cases. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}} The CJR report reveals some interesting things about those use cases and how journalists approach AI in general. But mostly it shows how badly we need more of this: systemic testing of AI that goes beyond the ad hoc experimentation that has too long been the default for many organizations. If the study shows nothing else, it’s that you don’t need to be an engineer or a product designer to judge how well AI can help in your job. Putting AI to the newsroom test To test AI’s summarization abilities, the evaluatorswhich included academics, journalists, and research assistantscreated multiple prompts to create short and long summaries from each tool, then ran them several times. A weakness of the report is that it doesn’t reveal the outputs so we can see for ourselves how well it did. But it does say it quantified factual errors to evaluate accuracy, comparing them with human-written summaries. Without seeing the outputs, it’s hard to know how to improve the prompts to get better results. The study says it got good results for short (200-word) summaries but saw inaccuracies and missed facts in longer ones. One surprising outcome was that the simplest prompt, Give me a short summary of this document,” produced the most consistently good results, but only for short summaries. The study also looked at research tools, specifically for science reporting. I love the specificity here: The CJR researchers were very particular about the use case: giving the tool a paper and then asking it to perform a literature review (finding related papers, citing them, and extracting the overall consensus). They also chose their targets deliberately, evaluating AI-powered research services like Consensus and Semantic Scholar instead of the usual general chatbots. On this, the results were arguably even worse. The tools typically would find and cite papers that were completely different from what a human picked for a manually created literature review, and even different from the other tools. And when they ran the same prompts a few days later, the results would change again. Getting closer to the metal I think the study is instructive beyond the straightforward takeaways, such as using AI only for short summaries and thinking twice before using AI research apps for literature review. Prompt engineering matters: I get that the three different prompts for summaries were probably designed to simulate casual usethe kinds of natural language text a busy journalist might dash off. And maybe AI should ultimately produce good results when you do that. But for out-of-the-box tools (which is what they used), I would recommend more thoughtful prompting. This doesn’t have to be a big exercise. Simply going over your prompt to make vague language (“short summary”) more precise (“200-word summary”) would help. The researchers did ask for more detail in two of the three prompts, but the study criticizes the longer summaries for not being comprehensive when the language in the prompts doesn’t specifically mention comprehensiveness. Asking the AI to check its own work sometimes helps too. The app layer struggles: Reading the part about the various research apps not producing good results had me nodding along. I don’t want to read too much into this since the study was narrowly focused on research apps with a very specific use case, but I’m currently living through something similar while experimenting with AI content platforms for my plans at The Media Copilot. When you use a third-party tool, you’re an extra step removed from the foundation model, and you miss having the flexibility of being “closer to the metal.” I think this points to a fundamental misunderstanding of the so-called “app layer.” Most AI apps will put a veil over system prompts and model pickers in the name of simplification, but it isn’t the UX win that many think it is. Yes, more controls might confuse AI newbies, but power users want them, and it turns out the gap between the two groups might not be very large.I think this same misunderstanding is what stymied the GPT-5 launch. Removing the model pickerwhere you could pick between GPT-4o, o4-mini, o3, etc.seemed like a smart, simplifying idea, but it turned out ChatGPT users were more sophisticated than anyone had thought. The average ChatGPT Plus subscriber might not have understood what every model does, but they knew which ones worked for them. Iterate, iterate, iterate: The study’s results are helpful, but they’re also incomplete. Testing outputs from models is only the beginning of the process of building an AIworkflow. Once you’ve got them, you iterate: Adjust your prompts, refine your model choice, and try again. And again. Producing consistent results that save time isn’t something you’ll get perfect on the first try. Once you’ve found the right combination of prompting, model, and context, then you’ll have something repeatable. Coming halfway Where does this leave newsrooms? This might sound self-serving since I train editorial teams for a living, but after reading this report, I’m more convinced than ever that, despite predictions that apps and software design will abstract away prompting, AI literacy still matters. Getting the most out of these tools means equipping journalists with the skills they need to craft effective prompts, evaluate results, and iterate when necessary. Also, the CJR study is an excellent template for testing tools internally. Get a team together (they don’t need to be technical), craft prompts methodically, and then evaluate thembut then iterate. Keep experimenting. Find what consistently gets good resultsnot just quality outputs, but a process that actually saves time. Just doing “vibe checks” won’t get you very far. Because there is one more thing the study is off-target about. When a journalist considers how to complete a task, the choice usually isn’t between a machine output and a human one. It’s the machine output or nothing at all. Some might say that’s lowering the bar, but it’s also putting a bar in more places. And with some training, experimentation, and iteration, raising it inch by inch. {"blockType":"creator-network-promo","data":{"mediaUrl":"https:\/\/images.fastcompany.com\/image\/upload\/f_webp,q_auto,c_fit\/wp-cms-2\/2025\/03\/mediacopilot-logo-ss.png","headline":"Media CoPilot","description":"Want more about how AI is changing media? Never miss an update from Pete Pachal by signing up for Media CoPilot. To learn more visit mediacopilot.substack.com","substackDomain":"https:\/\/mediacopilot.substack.com\/","colorTheme":"blue","redirectUrl":""}}
Category:
E-Commerce
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