Gamed System

I caught up with my friend M a couple of days ago. She left her FAANG job a few months ago and is now working for a large, messy company with some of the same problems she escaped from, except the culture is not nearly as toxic. Over the years, I've heard a lot of stories from M about the teams she'd been part of and the insufferable culture defined by top-down rot. Yet, people stay through their vesting schedule to make the most of a deeply miserable employment situation. Such was the case with M as well, and she was desperate to leave as soon as her vesting clock ran out. As luck would have it, she could not find a place to land for another two years after that. She often talked about how her sole accomplishment was not allowing her job to make her physically and emotionally unwell.

She'd read a post doing the rounds on LinkedIn about how leadership games the system to build and grow their territory, and the unexpected benefits to those who further that leader's cause. Her former boss was a VP as well; we'll call him C. This guy made it a point not to promote anyone at all, ever. So if you landed on his team, that was the end of the line for you. However, he made your job layoff-proof, and miraculously, that did not require that you work hard to deliver anything of value. Instead, everyone in his chain of command needed to pantomime performance to his precise direction. There had to be the appearance of slow but incremental progress, immovable obstacles that made delivery impossible, and a cadence of highly advertised miracles when this team had apparently done the humanly impossible. 

C was a master storyteller, and he did not abide people who had trouble playing their part in his precise theatrical production. M was one of those overzealous individuals who wanted to do the job they were hired and paid to do. She was not happy with the elaborate performance theater that she had to participate in every day. So she went around actually doing things, and C was deeply unhappy about it because she was actively undermining his finely tuned brinksmanship that had saved his team from a dozen rounds of layoffs over the years. M was refusing to be a team player. She was asked to stand down. The conversations were surreal and she was accused of not doing the real work of bringing the cross-functional teams along and maintaining alignment with his peer VPs. Her actions had actively undermined the complexity storyline C has been meticulosuly framing. According to M, what C had done successfully through his two-decade tenure at the company was not that different from the VP in that LinkedIn post. They were each gaming the system to optimize for their personal outcome.

Assumption Audit

After losing a large deal, the default reaction is speed involving more discovery meetings, faster prototyping, visible activity. My friend M is pushing in the opposite direction in her organization. She was concerned that the team was to scale assumptions that were never made explicit. Instead of compressing thinking into meetings, she's expanding discovery: asking all members of the cross-functional team to fully articulate their win-back plan in writing and answer a structured set of questions derived from their own proposal. She does not think their plan is going to work but wants to them to be responsible and accountable for it and not pass the blame on to the team that act on their directiont. She hopes there will be some truths uncovered in the process without it wasting a ton of her team's time.

Tools powered by AI have made it trivial to generate prototypes, content, and workflows in hours. The bottleneck is clarity and this team has none from M's vantage point. Many organizations are accelerating the wrong layer, producing high-quality artifacts built on poorly understood problems. The cost of being wrong is faster, more convincing failure. She had predicted the last loss and is confident this time will not be any different. 

I thought this was an interesting way to navigate politics in a large organization. M proposed to use the discovery responses to score against the RFP that they had previously lost and give the team a chance to course correct. If they refuse, we will use their discovery response to stand up a product prototype using AI and see what the the customer with the actual buying authority has to say so. So far M has never seen or heard from this indivual and has to rely on the intelligence and understanding of the team that failed to win in the first place. Given the cards that she's been dealt, this seems like a reasonable plan.

Strain Metabolism

At a happy hour recently, a few women including me got chatting about the most toxic managers they've ever had. Some of us had pretty visceral emotional reactions simply recounting events from decades ago. One woman started to tear up but insisted on sharing. Clearly this is something we all needed as unpleasant as it was, there was some catharsis in the end. This McKinsey article argues that one of the most overlooked challenges in modern organizations is not the presence of stress, but the accumulation of unprocessed stress over time. In fast-changing environments that are driven by restructuring, AI adoption, cost pressure, and continuous transformation, organizations rarely get clean “reset moments.” Strain builds up across teams, decisions, and relationships, quietly degrading performance even when workloads appear manageable.

The central idea is that leaders should help organizations “metabolize strain,” meaning they actively process and integrate the emotional and cognitive residue of change rather than letting it linger. Without this, stress doesn’t disappear; it shows up indirectly as resistance, disengagement, over-analysis, conflict avoidance, or decision paralysis. What looks like performance issues is often accumulated pressure expressing itself in distorted ways.

The article frames this through three levels: the individual, the relational, and the system. At the individual level, leaders need to regulate their own stress responses so they don’t amplify pressure in decision-making. At the relational level, teams need psychological safety so disagreement doesn’t collapse into defensiveness. At the system level, organizations need structures such as rituals, forums, and leadership practices, that allow people to process endings, transitions, and uncertainty rather than silently absorbing them.

A practical implication is that high performance in volatile environments depends less on eliminating strain and more on creating mechanisms to absorb and integrate it. Leaders who build these “processing layers” (structured reflection, clear communication of change, and explicit acknowledgment of what is being lost or deprioritized) enable teams to stay cognitively flexible under pressure. Without them, organizations become brittle: they continue operating, but with reduced adaptability and increasing internal friction. We had all been in environments where leadership had allowed toxicity to accumulate, actively contributed to it and demanded high performance notwithstanding. No wonder the pain was still so raw for many of us. 

Entry Shift

This story about how the New Work Foundation came to exist was a good read. It was founded by a former Meta and Salesforce executive as a nonprofit focused on Gen Z. She aims to solve for the entry lebel job disruption caused by AI and is among other senior tech leaders who stepping out of direct product roles to address the downstream effects of the systems they helped scale. Her vantage point inside companies already deploying AI agents at scale shaped a very consequential realization. AI is no longer just augmenting work, it is actively replacing large categories of entry-level and operational labor.

At Salesforce and Meta, she saw how quickly AI agents began absorbing tasks once reserved for junior employees: customer support workflows, basic analysis, content drafting, and coordination-heavy work. These are precisely the roles that have historically served as the entry point into major firms. As those layers compress, the traditional “first job” ladder is thinning, and the distance between education and meaningful employment is widening.

Her nonprofit response treats this not as a temporary labour cycle, but as a structural transition. If companies can scale output without scaling headcount, then Gen Z is entering a job market where learning-by-doing inside large firms is no longer guaranteed. The focus shifts from preparing for specific job titles to building adaptability in environments where roles themselves are unstable and frequently redefined by AI systems.

This is a model worth emulating across industries facing the same shrinking of opportunity of entry level professionals. Instead of assuming individuals will independently navigate disruption, it builds infrastructure for adaptation by helping young workers understand AI-augmented environments, identify transferable skills, and redesign career paths that do not rely on disappearing entry points. It is the much-meeded shift from participating in acceleration to building the tools that help others keep pace with it.

Corporate Betrayal

The corporate world has long been tried to build a constructed facade of pseudo family where companies invest millions in culture and people developmen supposedly aimed and deepening emotional ties with their staff. During prosperous years these organizations promote a narrative of mutual loyalty and shared values and purpose using language that mirrors the bonds of a household to encourage extra labor and commitment. The insinuation is the employer is a partner who will provide support through thick and thin. However as economic conditions shift these organizations reveal their true colors by dismantling the very benefits that define their purported care for the collective.

The recent actions of Deloitte serve as a stark example of this shift in character during a period of perceived crisis. Despite reporting billions in revenue the firm moved to slash essential benefits for a specific tier of its workforce including halving parental leave and eliminating significant reimbursements for IVF and adoption. Much like a partner who suddenly withdraws financial and emotional support for a shared future when conditions get tough, this move signals exooses thd family rhetoric for the lie it always was.

This betrayal is compounded by the use of falsehoods to mask the harsh reality of these reductions. By framing the removal of vacation time and parental support as a modernization of talent architecture these companies engage in a form of professional gaslighting. This behavior does not square with any prior activities for culture development because it fundamentally undermines the trust required for a community to exist. When a partner rebrands a lack of support as a necessary evolution for your own good the relationship turns null and void.

Zoom offers another clear instance of a brand showing its true colors after building its identity on the concept of human connection and happiness. After becoming a household name by facilitating relationships during global isolation the company began scaling back the perks and cultural initiatives that it once touted as its competitive advantage. This reveals a hierarchy of worth where the employees who built the brand are treated as expendable line items once the initial growth phase slows. I hope the current tide turns in a way that big companies become a relic of the past.

Saying No

Read a LinkedIn post recently where a PM coach broke down how to say no, four scenarios, four scripts, each carefully matched to who's asking. I have seen PMs do exactly as he prescribes and have very mixed feelings about this approach. The reason PMs are saying no constantly is that nobody has been clear enough about what the product is actually for.

I worked with a woman once who ran product at a mid-size logistics company. She could say no beautifully to anyone who came between her and her roadmap. Her product reviews were clean and defensible and features accumulated in the way a dorm room collects furniture from people who move out: nothing fit together, nothing was ever removed. What she was doing, very skillfully, was managing the symptom of not knowing clearly enough what the product was meant to do and specifically not meant to do. A scalpel manufacturer that adds a bottle opener because engineering freed up capacity hasn't gotten better and faster at losing the thread. This is not product management is about.

The AI question changes the terms here. When building something took six weeks and three engineers, friction enforced discipline. Now you can prototype in a day and run a feature behind a flag to see if it moves anything. The cost of yes has dropped considerably. Which means the PM still practicing "no" as a primary skill, with scripts calibrated to audience, is optimizing for a constraint that's loosening. If the thesis is sharp enough, most of the triage happens before the ask arrives. The VP's request doesn't need to be responded to with why it pulls the product away from what it's actually trying to be, not "it doesn't rank against our top three objectives," which is process language for the same lack of clarity.

The harder version of the job the post doesn't get to: what happens when the thesis itself is wrong. When the scalpel market is collapsing and the task isn't holding the line but making the case, clearly enough that the organization can actually move, that this is the wrong direction and here is what might be right instead. The post's version of hard is telling the VP no without damaging the relationship whereas the actual hard thing is being the person who says, when everyone has been pulling in the same direction for two years, that the direction was wrong, specially that the person is not the senior-most person in the room and yet it is their job to call these things out.

Systematic Sabotage

Interesting reading about Gen Z's propensity to intentionally degradee the corporate machine learning systems. From my observation some of what is being said about Gen Z in this story is generation agnotic. The behavior comes from misunderstanding of how modern data pipelines actually function. While the impulse to protect one's professional value through resistance is a logical response to the threat of displacement it fails to account for the sheer scale of the datasets involved.

Most enterprise models are trained on trillions of tokens of information gathered over decades, meaning that localized attempts to inject noise or refuse feedback are effectively diluted by a vast ocean of established high-quality data. In the mathematical reality of a neural network, a single cohort’s rebellion is often indistinguishable from a statistical outlier that is automatically identified and discarded by the system’s own quality-assurance filters. So these protests are mostly in vain and don't end up serving the protestor well.

There is always the risk that this strategy will create a visibility paradox where the primary victim of the sabotage is the worker’s own performance record. Most modern workplace software is integrated with telemetry that tracks output and efficiency in real time. This will include monitoring the very friction that "sabotage" is designed to create transforming political and a fundamental rights statement into a metric of underperformance. When an employee spends more time circumventing an automated workflow than utilizing it, the resulting drop in productivity is rarely attributed to the technology’s failure but is instead cited as a justification for further automation or staff restructuring. The logic of the corporation prioritizes the optimization of the system above the nuance of the human agent, and resistance that manifests as inefficiency only accelerates the drive toward more autonomous solutions.

The act of withholding expertise or providing poor feedback inadvertently cedes the future of the tool to those are are willing to do what's needed but may lack the the context the protestor has. By refusing participate in the reinforcement learning process where human nuance is translated into algorithmic weights, companies simply pivot to third-party data labeling firms to fill the gap or find people within their organization who are not as keen on protesting the machine. In either event, the model continues to evolve. The act of sitting out ensures that the resulting tool is trained by people who do not understand the specific intricacies or ethical demands of the local environment. By opting out, workers lose their last remaining lever of influence over how the technology will eventually dictate their daily tasks and professional standards.

There is the broader competitive pressures that govern the survival of a firm in a globalized economy. If a workforce successfully halts the adoption of efficiency-gaining technology within their own organization, they effectively create a competitive vacuum that will be filled by more compliant rivals. Economic history suggests that firms which fail to integrate transformative tools eventually lose market share to those that do, leading to a scenario where the jobs are not just automated but are permanently relocated to more technologically agile competitors. The defensive posture of the individual worker, while emotionally resonant, fails to address the macro-economic reality that capital will always migrate toward the path of least resistance and highest output.

The attempt to "break" the AI from within assumes a level of transparency in the system that rarely exists for the end user. Because many of these models operate as black boxes, it is nearly impossible for a single user to know whether their intentional error is causing a malfunction or is being used as a valuable edge case to make the system more resilient. Every mistake fed into the machine is still a data point. It servers as a lesson in what not to do, which perversely helps the algorithm map the boundaries of human error more accurately. True agency in the age of automation likely lies not in the corruption of the data, but in the mastery of the systemic structures that define how that data is used to shape our physical and digital worlds.

Quiet Takeovers

My young friend, P was sharing about the extraordinary level of stress at his job where performing miracles and heroics is the order of the day if you don't want to get fired. It got me thinking about the story of how Tippi Hedren helped a group of Vietnamese refugees enter the nail trade after the Fall of Saigon. It has been told so often that it now feels like a parable about chance. Twenty women notice an interesting detail, someone pays really close attention, and out of the blue a whole new industry appears. It is a compelling image because it zooms into moment that moment of recognition. What followed from that instant was the slow construction of an economic machine built on necessity, trust, and repetition.

Skills spread through informal apprenticeship chains that moved faster than any formal training system. Capital came from within the community through rotating credit systems that replaced banks. Information moved through dense social networks where opportunity traveled quickly. What looked like coincidence at the start became scaled coordination over time.

The decisive move was economic, not cultural. Vietnamese salon owners transformed nail care from a luxury into a routine service by lowering prices and increasing volume. That shift expanded the market itself rather than just competing within it. Once customers began to expect affordability and speed, the old model could not easily reassert itself. The community did not just participate in the industry, it rewrote its logic and then spread that across the country.

This pattern is repeating in modern markets shaped by software and artificial intelligence. In areas like AI data labeling, automation services for small businesses, vertical SaaS for trades, and niche marketplaces, the same conditions exist. Barriers to entry are low, demand is fragmented, and incumbents are either too expensive or too slow. Small, coordinated groups can learn quickly, share knowledge internally, pool resources, and deliver services at a price point that expands the market. The advantage does not come from a single breakthrough but from tight feedback loops and collective execution.

The opportunity today is to recognize that industries are still vulnerable to this kind of takeover when they are overpriced, undersupplied, or poorly served. The next version of the nail salon story will not start with a celebrity or a single training session. It will start with a group that identifies a narrow, practical way in, builds its own infrastructure for learning and funding, and scales before anyone notices the pattern. By the time it becomes visible, the market will already belong to them. I hope P will find inspiration from my telling of the nail salon story and how there maybe something to learn from there.

False Sabbatical

Reading this story reminded me of people I've known over the years who had the luxury of taking extended breaks from work to comfortably rejoin the workforce. I was envious of them but did not have the courage to take such risks in my own life. Being a single-mother for a many years conditioned me to value safety over all other considerations but it was not just that. I was always pretty risk-averse.

It seems like those days are now gone. Many young people who recently quit their stable careers to travel and find purpose are now returning to a brutal reality. After a wave of twentysomethings ditched the nine to five for what some called a mini retirement, the tide has turned toward a difficult job market characterized by high unemployment and stagnant wages. This shift has led many to describe the current climate as a jobapocalypse where securing a new role is no longer a simple task.

In this environment, those who took extended breaks are finding that their previous experience is often overlooked by hiring managers or filtered out by automated screening tools. The rise of rejection spreadsheets on social media highlights a growing trend of job seekers reframing constant setbacks as part of a collective struggle. For many, the dream of freedom and adventure has been replaced by the stress of long term unemployment and the realization that a steady income is now a luxury.

Experts suggest that the decision to walk away from a job without a clear return plan is becoming increasingly risky. While some leave to escape toxic environments, others may be better off attempting to negotiate for better boundaries or more flexibility within their current roles. In a market where dozens of candidates compete for every opening, personal networks and connections have become far more valuable than standard online applications. Even for those who do not regret their travels, the current economic landscape serves as a stark reminder that the grass is not always greener on the other side.

The silver lining to the situation may be that people are forced to consider conventional options to earn a living and that may open opportunities and the door to experiences that could exceed anything they experienced on their travels. 

Lily Padding

Learned the phrase lily-padding from a news story I read recently. The phenomenon represents a significant departure from the traditional linear career path where employees climbed a single corporate ladder for decades. Instead, Gen Z professionals are adopting a strategy of jumping between different roles and companies to gain a diverse array of skills and experiences. This approach treats each job as a temporary platform for growth rather than a final destination. By prioritizing lateral moves and skill acquisition over long-term tenure, these workers aim to build a versatile portfolio that makes them more resilient in an unpredictable economy. This shift reflects a move away from institutional loyalty toward a model of personal career ownership and continuous learning.

From a psychological and developmental perspective, this trend offers both unique advantages and potential drawbacks. Moving across different environments helps young professionals build adaptability and the ability to learn quickly in new settings, which are highly valued traits in today's fast-paced market. However, experts like Gurleen Baruah warn that frequent jumping can lead to a sense of restlessness and may prevent individuals from developing the deep, specialized knowledge that only comes with time and persistence. The key to successful lily padding lies in intentionality, ensuring that each move is a strategic step forward rather than a reactive escape from workplace discomfort. I can see why a young person would rather keep their option open than latch onto something to acquire depth only to realize they made the wrong bet and are now in a defunct line of work.

This movement is not an isolated occurrence but is instead a verified global trend seen across major international markets. In the United States and the United Kingdom, younger workers are increasingly rejecting the notion of the lifetime employee in favor of the office frog model to combat rising costs of living and the threat of automation. Similar patterns are emerging in India’s rapidly evolving tech and startup sectors, where frequent transitions are often the most effective way to secure significant salary increases and bypass slow internal promotion cycles. Organizations worldwide are now being forced to rethink their retention strategies to accommodate a workforce that values mobility and rapid upskilling.

It seems to be an entirely rational response to a global job market characterized by rapid technological shifts and economic volatility. As artificial intelligence and automation change the nature of work, the ability to pivot and acquire new competencies has become a form of job security. While employers may find this high turnover challenging, the trend suggests that the future of work will be defined by agility and the stacking of varied professional experiences. For the modern professional, staying relevant and adaptable on a series of lily pads has replaced the stability of the traditional corporate climb.

Reaching Balance

In the new year, I'd love for everyone I care about to care about what they do for a living but not at the cost of caring for themselves. I happen to know a disproportionate share of workaholics and over-achievers and am glad to say I am neither. That allows me to observe these folks from afar and nudge them sometimes. It turns out that Gen Z and I are on the same page on this. We are aligned that skipping breakfast and scarfing down a bag of Goldfish crackers for lunch is not the way to live or work.

In today’s changing workplace, Generation Z is challenging the obsession with urgency that once defined corporate culture. As Rainesford Stauffer reports in The Washington Post, many young workers who entered the job market amid the pandemic’s uncertainty are now rejecting constant crisis mode—the Slack pings after hours, the sudden projects framed as emergencies. For some, the stress has become physical: one young writer developed a rash during her first corporate job before realizing she didn’t want to live in “fight-or-flight” mode for ordinary tasks.

The shift reflects both generational priorities and economic disillusionment. Earlier workers were taught that loyalty and long hours led to advancement; Gen Z sees employers cutting staff, raising workloads, and rarely rewarding overextension. Career coach Phoebe Gavin says younger workers are pushing back against expectations that serve companies more than people. Their new motto, “It’s PR, not the ER”, captures a refusal to treat routine office work as life‑or‑death drama.

The pandemic further accelerated this change. As life’s fragility became impossible to ignore, many workers reevaluated what truly counts as urgent. Professionals like Erica Marrison describe redefining emergencies not in corporate terms but human ones—family, health, and purpose—while others, such as marketer Chanyce LeDay, have learned to communicate openly with managers about priorities instead of automatically saying yes. By advocating for clear workloads, they’re reframing productivity as precision, not panic.

Of course, not everyone has the same freedom to resist the “false emergency” mentality. Structural inequities mean lower‑wage employees, workers of color, or those without flexibility still risk backlash if they assert boundaries. Advocates like Nia West‑Bey note that true change requires broader cultural recognition that worth isn’t tied to burnout and that constant busyness can undermine, not prove, performance.

For Gen Z, the movement is less rebellion than realism: a recalibration of what work should cost. As one worker’s mother bluntly reminded her, “If you die, they’ll just post your job and say you were nice.” The new mantra, then, isn’t about doing less, it’s about doing enough, doing it well, and refusing to confuse urgency with importance.

I shared a very similar wisdom with a former co-worker who was that close to burnout but did not seem to notice. As a friend, I felt some straight-talk might shake her out of it. I remember telling her that if she dropped dead, they would backfill in in two weeks, her family would mourn her forever and yet she hardly stayed in touch with them because work was so consuming. I don't know if anything changed for her but I hope others will tell her the same thing in their own ways and there will some outcome from our collective efforts.

Building Flywheel

This story about Amazon employees caught my eye because of how the dots connected over time. While its about one company, it may be an universal thing that employees are less afraid of AI itself than of what management is using AI to justify.

In this instance workers perceive three developments happening simultaneously: layoffs or flatter org structures, stricter return-to-office enforcement, and increasing deployment of AI tools into daily workflows. On paper, Amazon frames these as separate efficiency initiatives. Employees appear to experience them as one integrated system. AI becomes the explanation for why fewer people are supposedly needed. RTO increases visibility and managerial control over the remaining workforce. Performance metrics tighten because AI systems make more work measurable. The Amazon flywheel in full force doing what it does best.

The strongest emotional reaction goes beyond the fear of replacement : it is the collapse of predictability. Many tech workers entered companies like Amazon during a period when growth itself acted as a buffer. Teams expanded rapidly, inefficiencies were tolerated, and career progression often came through organizational scale. Employees now feel the company is optimizing for permanent operational tightness instead. In that environment, AI no longer feels like a productivity assistant. It feels like a benchmark against which human labor is constantly being reevaluated.

The return-to-office component intensifies that perception because it changes the social meaning of work. During remote periods, output mattered more than visibility. Under tighter office policies, employees increasingly feel both observed and quantified. The psychological effect is significant. Workers may tolerate uncertainty when they believe leadership is investing in them long-term. They react differently when they suspect every workflow is being audited for future headcount reduction. If you come into office, you become more observable and therefore expendable. There might be a benefit to jumping through the hoops to keep that remote exception and fly under the radar, rest and vest while you can.

The workforce trying to answer a question management has not fully answered publicly: if AI materially increases productivity, who captures the gains. Employees worry the answer may primarily be shareholders and operating margins rather than reduced workloads, shorter hours, or better compensation.

Shared Light

I’ve always felt that the people we choose to surround ourselves with act as a mirror to our own ambitions, but I hadn't considered how much they act as a silent engine for our careers. Who we end up being surrounded by is ultimately a reflection of our internal energy and what it attracts. Recently, I came across the "FISK" criteria coined by former Vanity Fair editor Graydon Carter, the idea that a partner should be Funny, Interesting, Smart, and Kind. It’s a charming list, but as it turns out, these traits are more than just social assets; they are vital, under-appreciated professional tools. Research suggests that having an emotionally competent spouse can boost a worker’s desirable traits in the eyes of a boss by as much as 26%.

I see this play out in my own circle. My friend D is married to S, who is definitely FISK. D is wonderful in her own right, but S makes her shine perfectly. He is like a professional photographer who knows exactly which angles and settings will illuminate her best. This kind of partnership is the "secret sauce" that the corporate world rarely acknowledges. For high-ambition women especially, the stakes of this choice are significantly higher. The evidence is increasingly blunt: a supportive partner isn't just a bonus; it’s a requirement. Without a spouse who actively shares the "double bind" of domestic and parental labor, career advancement often becomes a casualty of overload.

Interestingly, even the mere perception of potential partners matters. Studies of elite MBA students found that single women often dial down their professional displays of ambition if they believe they are being observed by single men, fearing that high-flying career goals might make them less "marketable" in the marriage lottery. It’s a sobering thought that we might shrink our professional selves before we’ve even met the person we’re shrinking for. A partner’s true value lies in their ability to regulate emotion and provide a stable home environment, acting as a buffer against the volatility of the workplace. When a spouse has the emotional bandwidth to bolster your confidence, you show up to the office as a more capable version of yourself.

However, this emotional support is a finite resource. If that partner is themselves burdened with a disproportionate share of domestic chores because their spouse is "prioritizing the career," their ability to provide that professional tailwind evaporates. In the case of D and S, the magic happens in large part because D is exceptionally patient, generous, and has boundless energy. This is what feeds the marriage and gives S what he needs to be able to shine the light on her with such finesse when they are out in the world together. Success, it appears, is a team sport played at the kitchen table long before it reaches the boardroom, a cycle of mutual support that ensures neither person has to dim their light to keep the home fire burning.

Glue Employee

Reading this WSJ article about "glue employees" brought D immediately to mind. In a modern workplace often obsessed with individual "rockstars," behavioral scientist Jon Levy highlights a more critical asset: the "glue player." These are the employees who hold teams together through high emotional intelligence and quiet leadership. Rather than seeking the spotlight, glue players focus on "leading from behind." They are adept at anticipating needs, drawing out quieter voices, and resolving friction before it stalls a project. They act as force multipliers, making everyone around them more effective without demanding individual credit. D checked every single box and then some, even though you’d rarely hear from her in meetings.

Spotting these individuals requires looking beyond standard metrics like sales figures or lines of code. Levy suggests that glue players leave "clues" in their history, often appearing as mentors, cross-departmental coordinators, or the people who naturally organize community and volunteer efforts. Within an organization, they are easily identified by asking colleagues who they rely on most or who helps the team function smoothly. They are the ones who bridge the gap between silos, ensuring that different departments are aligned and that new hires feel integrated into the culture. I learned about D right as I started the job, and in time, she became my favorite coworker. She either knew the answer or knew exactly who did. If you came in via a warm referral through D, all kinds of doors magically opened. I realized that quickly, and I can’t imagine how much harder it would have been for me to get ramped up without her.

Despite their essential role, glue players are frequently overlooked by traditional corporate reward systems. Most evaluation frameworks measure obvious, individual wins, which effectively ignores the invisible labor of maintaining team cohesion. Levy warns that when companies only reward the top 10% of performers, they accidentally incentivize internal competition and resource hoarding. When a glue player feels undervalued and eventually leaves, the impact is often a "stealth" disaster. Management may not realize why the team’s productivity has tanked until the person who quietly solved everyone else's problems is gone. I was fortunate to leave well before D did, so I didn’t have to experience the complete descent into chaos that followed her departure.

To leverage this "underrated power," Levy argues that leaders must evolve their compensation and recognition models. By introducing peer-nominated awards or tying bonuses to collective team outcomes rather than just individual milestones, companies can signal that collaboration is a core value. Shifting the culture to recognize those who help others succeed not only retains vital talent but also creates a more sustainable environment where "collective genius" can thrive. The article makes the case that the most successful organizations aren't those with the most stars, but those with the strongest glue. I’d say the truth is less binary: You need a few stars who raise the bar and inspire others to try harder, but you need at least one "D" to keep the organization humane.

Silent Echoes

The landscape of professional life has shifted into something nearly unrecognizable. A former colleague of mine, laid off not long ago, immediately pivoted to the modern survival kit: "thought leadership" posts on LinkedIn and a self-published book on Kindle. It was clear the content was generated by AI, lacking any personal touch or human warmth. She has since transitioned into attempted fractional consulting without any takers. She is still diligently engaging with her network and following the prescribed digital playbook to the letter. Yet, despite her efforts, it seems she is merely screaming into a void. She is not alone in this; many others in her position feel the same profound disconnection.

I often contemplate the day I might find myself without work, searching in vain for a new path. While I would likely ignore the standard advice, I suspect my own efforts might prove just as futile as this woman's. Success in this environment feels less like the result of strategy and more like a stroke of luck or a random happenstance. Until that moment arrives, one simply maintains whatever rituals are necessary to stay grounded. My former colleague is doing exactly that, holding on in hopes of an eventual breakthrough.

There was a time when effort and outcome were closely correlated, and the path forward felt logical. It certainly did not require standing on a digital soapbox to shout for attention. I recently heard an interview with the author of Platonic, who noted that people are generally more liked and accepted than they believe. She argued that embracing vulnerability and accepting that not every outreach will succeed is essential. However, when individuals are met with a wall of professional indifference, it becomes difficult to trust that personal interactions will be any different. A fractured job market carries consequences that extend far beyond financial stability; it fundamentally alters a person’s sense of self and their belief in the possibility of connection.

Signal Tradeoff

I have hated my résumé with a steadfast intensity for as long as I can remember. Nearly a decade ago, a kind coworker took pity on me and my very pitiable résumé and spent hours over a couple of weekends helping me workshop it. I hated the final version less, mostly because I did not have to fully own it. Even after all that effort, I do not think I would have spent more than a minute on it if it had come across my desk for a role I was hiring for. I always knew exactly what I disliked about it, but never what it would take to make it feel even remotely likeable.

So it is strange and a little satisfying to watch Elon Musk try to get rid of the résumé and cover letter in one fell swoop. I cannot tell if it helps or hurts. The three things in my career I am most proud of are tied up in deeply personal reasons. They probably would not qualify as great examples of professional excellence. And yet, if I were to write them down and tell the story behind them, that would be the most honest version of my professional self I could offer.

I am just not convinced that honesty is what closes the deal anymore. Employers seem completely unsure how much they need a human, what they need that human for, and which parts of that human can eventually be absorbed into the AI they hope will make most roles unnecessary. In that kind of environment, handing over your three strongest proof points upfront feels less like clarity and more like giving everything away before you even have a chance to be rejected.

It almost feels like a trojan horse, a move that might end up hurting candidates more than helping them. There will be a few winners, of course, but that is true even in the current system where AI generates endless variations of résumés for job postings that were also written by AI, only to be screened out by more AI. Something more fundamental is broken here. The résumé, the cover letter, even these three proof points are just surface symptoms of a deeper malaise, not the cause of it.

Leading Machines

The dreaded status report is dead, and I, for one, am not mourning its passing. As we move into 2026, the "wasteful cycle" of repeating the news up the food chain is being replaced by automated intelligence, finally allowing managers to stop acting as message relays and start acting as leaders. If you are or want to be a servant leader, these are the best of times. Most of our teams' obstacles can be traced to broken systems and lossy data that hinder good decision-making, and these problems are more solvable now than ever. As AI moves from experimental pilots to full-scale implementation, we can finally build tools to automate mundane tasks and let the base data of work progress speak for itself.

This reduction of routine administrative "noise" is intended to liberate us, reclaiming hours each week for coaching and strategy. However, this does not necessarily mean a lighter workload. The nature of management is becoming more sophisticated, requiring a "human-in-the-loop" approach where leaders must supervise AI performance and validate its output. We are finding ourselves in a position of "dual management," figuring out how to balance the demands of human teams alongside these new automated agents on the fly. While the technical hurdles are largely cleared, the primary challenge now lies in navigating the human and organizational shifts required to become a truly data-driven workplace.

There is, however, a cost to this efficiency. The machine has become the elephant in the room, mediating nearly every interaction. I’ve found that the essential human connection between a manager and their team can easily become clouded by the presence and relentless output of the machine. It takes a significant, conscious effort to trudge through that digital layer to keep personal relationships vital. As we redesign workflows, we must be intentional about identifying which human skills, like context-setting and empathy, become more valuable as the AI handles the operational heavy lifting.

Time Off

Read this report from Inc. Magazine that highlights a troubling workplace trend: one in four U.S. employees didn’t take a single day of paid time off last year, despite most companies offering it. According to FlexJobs’ survey of over 3,000 workers, 23 percent skipped vacations entirely in 2024–2025. The reasons reveal a culture of overwork: 43 percent cited excessive workloads, 30 percent feared falling behind, and nearly 30 percent said they’d feel guilty or appear lazy for taking time away. Even more concerning, 19 percent said their workplaces clearly discouraged them from using PTO at all.

I went a decade without any actual vacation because I was paid hourly and and it did not make sense to skip the hours being a single-income family. Coming out of that decade, I got into a more regular job where there were holidays and vacation days. The later, I had to use because they did not roll-over endlessly. It helped straighten out my unhealthy habit on not taking time to disconnect. The first few years were tough because I was so unused to taking time-off. I can see why people would consider catching up on sleep to be a good use of their PTO.

The United States famously remains the only advanced economy that doesn’t guarantee paid vacation by law, yet most companies voluntarily offer 10 to 14 days per year, still far below global standards like 42 in France or 36 in Spain. However, policies only help when employees feel empowered to use them. FlexJobs’ career expert Toni Frana explained that without a culture that genuinely supports rest, PTO benefits become symbolic. Workers internalize guilt, fearing career damage if they actually disconnect, even when managers insist time off exists. Managers must lead by example. They need to take time off and not be available while they are out to it sets the bar for everyone in the team.


Workload pressure wasn’t the only factor discouraging rest. A quarter of respondents said managers discouraged taking full weeks off, leaving 42 percent using just 1 to 10 days of PTO annually.  Corporate environments, rewarding constant connectivity, often cause employees to equate busyness with dedication. The lingering impact of layoffs, staffing shortages, and hybrid work expectations has deepened this “work while you rest” cycle. According to the article, employees who stay online during vacations to monitor emails or messages often return no more recovered than when they left. This one I don't fully agree with. I do keep an eye on things but don't engage while I am out. I see it as no different than keeping up with my personal email while I am out.

Still, not all organizations foster burnout. About 18 percent of U.S. workers took more than 15 days off last year, showing that supportive cultures exist. But strikingly, a growing share of vacationers are using that precious time not for travel or adventure—but simply to sleep. Amerisleep’s research found 37 percent of employees used vacation for rest and recovery at home. Millennials were the most likely “sleepcationers,” followed by Gen X and Gen Z. Soaring travel costs make recharging at home appealing, but it also underscores how exhaustion and not leisure is driving PTO decisions.

The findings reveal a stark contradiction: companies encourage well‑being yet sustain systems that punish real downtime. The result is a workforce more fatigued than fulfilled, treating time off as a risk, not a right. Until leadership normalizes true disconnection, by reducing guilt, balancing workloads, and modeling rest, employees will continue leaving paid vacations unused, ironically sacrificing the very productivity such overwork aims to protect.

Chat Fish

A new form of deception is creeping into modern romance, and it doesn’t involve fake photos or stolen identities. It’s called chatfishing, when people use AI tools like ChatGPT to craft their dating-app messages, making themselves sound wittier, more thoughtful, or more emotionally intelligent than they really are. In The Guardian’s recent feature, writer Alexandra Jones explores how the line between human charm and algorithmic assistance is blurring, leaving daters unsure whether they’re falling for a person or a prompt. I have seen this happen in at work trying to interview candidates. Most get screened out by the recruiter and don't even make it to the job interview because too much AI is involved in every step of the process. But those over-perfect responses put me in high alert and I've had many such experiences by now. It's some variant of chatfishing I guess.

Many singles now admit to outsourcing parts of their conversations to AI. Some justify it as a way to overcome shyness or writer’s block; others see it as a competitive advantage in a marketplace flooded with matches. But for those on the receiving end, the result can be uncanny. Several people interviewed in the piece described realizing, often only after meeting in person—that the charisma and insight they’d been drawn to online simply weren’t real. The witty banter that built intimacy had been generated, not genuine.

This shift represents more than digital deceit, it highlights a deeper authenticity crisis in online dating. Text-based connection already invites performance, but when AI gets involved, the persona becomes even more curated. A chatfisher can build an idealized self without having to live up to it. As Jones notes, today’s dating apps already treat love like a marketplace of personal brands; AI merely supercharges that logic, turning conversations into marketing copy and affection into engagement metrics.

Experts quoted in the article warn that this new layer of artificial intimacy could erode the foundations of real connection. Genuine relationships rely on vulnerability, imperfection, and reciprocity—qualities that algorithms can mimic but never embody. When we delegate our emotional labor to machines, we risk hollowing out the messy, unpredictable process that makes human chemistry meaningful in the first place.

The takeaway is simple but sobering: AI might help you craft a perfect opener, but it can’t sustain a real relationship. If the conversation feels too polished or the compliments sound copy-and-pasted, they probably are. The antidote to chatfishing isn’t technological, it’s human. Meet in person sooner, speak imperfectly, and remember that love isn’t found in flawless messages but in the unfiltered moments that follow. Many hiring managers are asking for in-person interviews all of the same reasons. No one is looking for a perfect hire, people want someone they feel is good enough for the job and has a good attitude which will help them learn what they don't know and get along with the team. No AI is needed for any of that.

Keeping Tenure

The stories of America’s from the WSJ article on the longest-tenured employees read differently today, in a moment when entire professions are being reorganized by AI. Their careers, once emblematic of stability and linear growth, now serve as mirrors for a workforce bracing for great disruption and discontinuity. What strikes you first is how accidental their longevity was. They entered companies young, often through a single conversation, and stayed because the institutions around them evolved slowly enough for them to keep up. Today, no one confuses institutional evolution with stability. AI is compressing decades of change into quarters. What was once a gentle slope of technological progress is now a cliff face.

And yet the people who thrived for fifty or sixty years inside the same organization weren’t insulated from change; they were defined by their ability to metabolize it. They embraced new tools, unfamiliar workflows, and younger colleagues who saw the world differently. They kept learning because they sensed that learning was the only reliable defense against irrelevance. This feels newly urgent now. The workers who will survive AI’s disruptive surge are not the ones who can claim mastery, but the ones who treat mastery as temporary, a snapshot in an ongoing adaptation cycle. That is a critical survival skill in today's workforce no matter what age you are and how many years of experience you have. 

The nature of the change confronting us is not merely about tools becoming digital or jobs becoming faster. AI doesn’t just accelerate work; it rewires its meaning. The engraver at Tiffany continues to hone and perfect a craft that machines still cannot authentically replicate. Many such enclaves of human distinctiveness will remain, but they will shrink. It would be wise to find that enclave based on our individual skills and passions. The truth is everyone will not have success in such quest. So for the rest of the workforce, the challenge will be deciding which parts of their identity can coexist with automation and which must be released. The longest-tenured employees lived through waves of technological intrusion, but the core of their roles remained human. Today, the core itself is negotiable.

Their stories also remind us that loyalty has always flowed through human bonds, not corporate strategy bombast. Even in the age of automation, they stayed because their colleagues made the work bearable, sometimes joyous. That too feels precarious now. Remote work, fluid staffing models, and AI-driven productivity systems can erode the interpersonal tissue that made longevity possible. If the future of work becomes increasingly atomized, the question becomes whether people can still feel rooted enough to grow inside a single institution, or whether the concept of “institutional belonging” will dissolve entirely. I have heard young people say that there is a penalty to being present in the office everyday when not everyone in the organization is there or even expected to be. It shines the light on the person in ways that sometimes does not help. I believe there is truth to this observation and it suggests that the notion of institutional belonging will be much harder to come by.

There’s also something revealing about the way these long-serving employees kept themselves physically and mentally active, as if motion were a shield against obsolescence. They climbed stairs, learned new systems, and refused to become sedimentary. That instinct feels almost prophetic in an AI era. Survival may depend less on job titles than on metabolic flexibility, your ability to re-skill, reframe, and reorient without treating any version of yourself as final.

Looking at them now, you realize they were not relics of a slower age so much as early prototypes for what resilience could look like. The difference is that they had decades to practice, while today’s workers are being asked to acquire similar adaptability on an accelerated timeline. The promise and peril of AI is that it demands from everyone the mindset that only a select few ever needed before: the refusal to be finished, the ability to reinvent without resentment, and the willingness to let work become unfamiliar without letting yourself become small.