Exclusive: Louis DeJoy Resigns as Postmaster General
U.S. Postmaster General Louis DeJoy testifies during a House hearing on Capitol Hill in Washington, DC May 17, 2023. Credit - Drew Angerer—Getty Images
Louis DeJoy has resigned from his role as Postmaster General of the U.S. Postal Service, according to a source familiar with the matter. On Monday, he told the USPS Board of Governors that it would be his last day on the job. He named Deputy Postmaster General Doug Tulino to take over until the Board names a permanent replacement.
DeJoy's departure comes weeks after he struck an agreement to allow Elon Musk's Department of Government Efficiency to help the agency cut costs and remove bureaucratic red tape. Last month, he told the Board to start looking for a successor, ending a five-year tenure running the agency through the COVID-19 pandemic, three elections that relied heavily on mail voting, and the implementation of a dramatic restructuring.
This is a developing story and will be updated.
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Perhaps nowhere is the bullshit jobs phenomenon more visible than in SaaS hiring patterns. The industry has developed what Powell-Thompson calls "the SaaS hiring loop" – continuously recycling talent from the same pool of failed or plateaued startups. Competence gets assumed based on LinkedIn logos rather than demonstrated outcomes. "A growth marketer who scaled vanity metrics at one mediocre tool is hired to repeat the cycle elsewhere," Powell-Thompson notes, "without ever proving they can build sustainable customer retention or profit." This creates a carousel of recycled talent carrying identical playbooks and assumptions but rarely delivering results that justify their roles. The industry favors "SaaS-native" professionals who speak fluent ARR and OKR but don't question fundamentals or challenge assumptions. The venture capital boom masked much of this inefficiency. 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When algorithms can analyze user behavior patterns in real-time, what's the point of analysts who took days to produce similar insights? The numbers are telling the story. SaaS companies have eliminated hundreds of thousands of positions since 2022, yet many report improved productivity metrics. This suggests that much of what looked like essential work may have been what Graeber would recognize as elaborate theater. Graeber's categories map remarkably well onto modern SaaS organizational charts: The Flunkies: Business development representatives who exist primarily to make actual salespeople feel important, spending days sending LinkedIn messages nobody reads. The Duct Tapers: Customer success managers whose primary function involves fixing problems created by poorly designed products or misaligned sales promises. The Box Tickers: Growth marketers who obsess over vanity metrics like email open rates while customer churn rates remain stubbornly high. The Taskmasters: Middle managers who exist solely to manage other managers, creating elaborate OKR frameworks that nobody follows. Powell-Thompson identifies a particularly troubling aspect of SaaS culture: the near-complete lack of self-awareness. Workers confuse busywork with impact, treating twelve-slide strategy decks and Miro boards as substitutes for real execution. The industry has developed what he calls "a language of legitimacy that sounds impressive but says little." Phrases like "We're building an extensible platform for enterprise workflows" or "Our ICP is mid-market GTM teams in the post-series B range" mask fundamental confusion about customers and value propositions. LinkedIn amplifies this dynamic. The average SaaS employee presents themselves as management guru, life coach, and visionary simultaneously, while often unable to ship a bug fix, close a sale, or explain their product's API in plain English. Ironically, as AI eliminates some forms of meaningless work, it may be creating others. A new class of "AI prompt engineers" has emerged, with some commanding six-figure salaries for sophisticated search operations. Companies are hiring "AI ethics officers" and "automation specialists" who spend more time in meetings about AI than implementing it. This suggests we may be witnessing the birth of what could be called "AI bureaucracy" – jobs that exist primarily to manage, oversee, or optimize interactions with AI systems, potentially as divorced from real value creation as the roles they're replacing. The bullshit jobs critique isn't without its limitations. What appears inefficient may serve important functions that aren't immediately obvious. Redundancy in complex systems often provides resilience. The customer success manager scheduling seemingly pointless check-in calls might prevent million-dollar churn through relationship management that AI cannot replicate. Some of the most successful SaaS companies – Slack, Notion, Figma – emerged from overcrowded markets. The process of hiring diverse perspectives, even if some prove redundant, may be necessary for breakthrough innovation. And behind every critique of meaningless work stands a real person with real financial obligations. The growth marketer whose role seems pointless represents someone's mortgage payment, someone's child's college fund. The solution isn't eliminating all potentially redundant roles – that would be both cruel and counterproductive. Instead, the industry needs conscious evolution guided by several principles: Honest Performance Metrics: Moving beyond vanity metrics to measure actual business impact. Roles that can't demonstrate clear value creation over reasonable time periods should be restructured or eliminated. Skill Depth Over Buzzword Fluency: As Powell-Thompson argues, the industry needs "fewer growth hackers and more grown-ups. Fewer decks, more decisions. Fewer generalists, more expertise." Human-AI Collaboration: Rather than viewing AI as human replacement, smart companies are determining how to combine human judgment with AI capability for genuinely valuable outcomes. Cultural Honesty: Developing organizational cultures capable of honest productivity assessment without corporate speak or fear-based defensiveness. The SaaS industry's AI-driven reckoning previews what's coming for knowledge work broadly. As artificial intelligence becomes more capable, every industry will face similar questions about which roles create genuine value versus which exist primarily to create the appearance of activity. Graeber's insight about bullshit jobs revealed a moral crisis – people trapped in roles they knew were meaningless, maintaining economic survival through elaborate performance. The AI revolution offers an opportunity to escape this trap, but only through honest assessment of what we're escaping from. The SaaS industry's three hundred billion dollar scale means getting this transition right matters far beyond Silicon Valley. The sector employs millions globally and underpins much of the modern economy's digital infrastructure. If Graeber was correct about bullshit jobs' prevalence, then AI's arrival represents more than technological disruption – it's an opportunity for work reform. A chance to align human effort with genuine value creation benefiting both workers and customers. But realizing this opportunity requires something both the SaaS industry and broader business world have struggled with: courage to be honest about what actually works, what doesn't, and why. As Powell-Thompson concludes: "The truth is simple, and brutal. SaaS didn't just scale software – it scaled mediocrity." The question now is whether the industry will use this moment of AI-driven disruption for genuine transformation or simply automate meaningful work while preserving meaningless jobs through increasingly elaborate justifications. The three hundred billion dollar question is which path the industry will choose.