By The Intrepid in Companionist — 03 Dec 2025

The Circular Firing Squad of Productivity

Three articles landed within weeks of each other, each diagnosing a productivity crisis, each blaming something different. Together, they reveal more than any intended: we have no idea what we're measuring anymore.

The Accusations

The device hoarding article warns that Americans keeping phones for 29 months instead of 22 are costing the economy billions in productivity losses. Aging hardware creates "productivity drag." The solution: buy more devices, faster.

The AI liberation article celebrates how AI has exposed "the illusion of work"—all those reports, summaries, and updates that filled our days were performative busywork. AI can handle the robotic work, freeing humans for "thinking, deciding, designing." The author calls it "fantastic."

The workslop article sounds the alarm about AI-generated content that "appears polished but lacks real substance." Despite surging AI adoption, 95% of organizations see no measurable ROI. The culprit: too much hollow AI-generated material drowning actual work.

The Contradiction

These narratives can't coexist:

If most work was always meaningless (Article 2), then old devices were perfectly adequate for meaningless work (contradicts Article 1).

If AI should eliminate hollow busywork (Article 2), then AI-generated hollow busywork is the desired outcome, not the problem (contradicts Article 3).

If the issue is AI creating low-substance content (Article 3), then the issue was never device age (contradicts Article 1).

What's Being Avoided

None of these articles ask the uncomfortable question: What if the productivity problem isn't about tools at all?

Consider what's missing from all three:

Clear definition of what "productivity" means
Evidence that the proposed solution addresses the stated problem
Examination of whether the work itself serves a purpose
Discussion of organizational dysfunction, unclear goals, or misaligned incentives

The device article interviews people with commercial interests in device turnover. The AI liberation article is written by someone selling AI transformation. The workslop article comes from researchers studying AI adoption. Everyone has a tool to sell or a thesis to defend.

But there's something deeper in the device hoarding piece that the others don't make explicit: it reveals an economy organized around consumption for the sake of keeping production running. The argument isn't really "old phones hurt productivity." It's "if people don't keep buying phones, the phone-selling economy suffers." The productivity claim is a fig leaf for demand generation.

This is the tip of the iceberg. Below the waterline lies the recognition that vast sections of the economy—and the work within it—exist primarily to justify their own continuation.

The Eternal Scapegoat

This isn't AI's first rodeo. It's just the latest technology to serve dual duty as both savior and scapegoat for workplace dysfunction.

In the 1990s, it was email. Too much email was killing productivity. Then insufficient email adoption was killing productivity. Email would eliminate meetings. Email was creating too many meetings. The solution was always more email management tools.

In the 2000s, it was collaboration software. We needed better knowledge management systems. Then we were drowning in wikis and SharePoint sites no one maintained. The tools would break down silos. And the rubble of those silos became new barriers.

In the 2010s, it was smartphones and cloud computing. Mobile access would make everyone more productive. Then we were suffering from always-on culture and communication overload. Remote work tools would free us from geography. Remote work tools made us feel like we were working all the time.

Now it's AI. It will eliminate busywork and free humans for creative thinking. It's generating too much low-quality content. It will revolutionize productivity. It's showing 95% of organizations no ROI.

Each technology cycle follows the same script:

Act 1: The Promise — "This tool will finally solve our productivity problems."

Act 2: The Adoption — Mandates roll out. Consultants are hired. Metrics are tracked. Success stories are published.

Act 3: The Disappointment — The promised transformation doesn't materialize. New problems emerge. We're working harder than ever.

Act 4: The Blame — We're using it wrong. We haven't adopted it fully. The technology has limitations. Users are resistant.

Act 5: The Next Promise — "But this tool will finally solve our productivity problems..."

Across four decades of workplace technology cycles, certain questions never get asked:

What work actually needs doing?
How do we know if it's working?
What are we organizing around—goals or activity?
Why do we keep describing work as "busywork" yet continue doing it?
If tools keep promising to eliminate low-value work, why does low-value work keep expanding?

These questions threaten something deeper than any particular technology: they threaten the premise that more activity equals more value.

The Moral Performance of Productivity

The obsession isn't really with output. It's with proving worthiness through visible motion.

We've inherited a late-capitalist Protestantism: salvation through activity, redemption through responsiveness, sin through idleness. Productivity has become a moral performance rather than an economic metric. The measure isn't "what did you create?" but "can you demonstrate that you were productively occupied?"

This is why the tools become ritual objects. Adopting the latest technology signals virtue. Using AI shows you're forward-thinking. Upgrading devices proves you're serious about performance. The actual output is almost beside the point—what matters is participating in the liturgy of optimization.

In this frame, the device hoarding article isn't making an economic argument. It's making a moral one: keeping your old phone is a sin of sloth. You're failing to perform the ritual of renewal. You're not doing your part to keep the faith.

The Meta-Work Singularity

We're approaching full fractal absurdity. Somewhere right now, there's probably:

An AI dashboard tracking which employees are using AI tools
A productivity score based on AI engagement metrics
A weekly AI-generated summary of AI usage trends
A quarterly review meeting to discuss the AI adoption dashboard
A consultant presenting best practices for AI adoption measurement
An article warning about "AI measurement fatigue"

And somewhere, a worker spending 15 minutes doing actual work, then spending the rest of the week documenting, reporting, and justifying those 15 minutes across multiple systems.

We've created:

AI tools to measure AI adoption
Productivity metrics to measure productivity tool effectiveness
Meetings about why we have too many meetings
Reports analyzing why we generate too many reports
Consultants to help us understand why consultants haven't helped

It's watchmen watching watchmen, all the way down.

The beautiful irony: the article about "workslop" is itself analysis-about-analysis-about-tools-about-work. At some point, the entire system becomes a hall of mirrors where we work to measure work, measure the measuring of work, and generate content about generated content.

The actual work—the thing that might create value for someone outside this recursive loop—has long since disappeared into the center of the maze.

This isn't dysfunction. It's the system coping with opacity.

When you can't directly observe value creation—when outcomes are ambiguous, causation is unclear, and impact is delayed—you measure surrogates instead. Then you measure the surrogates of the surrogates. Then you hire consultants to validate the measurement strategy. Then you adopt tools to optimize the measurement. Then you generate reports on tool adoption rates.

Each layer adds legitimacy through complexity. The meta-work proliferates precisely because real outcomes remain unclear.

The Structural Function of Busywork

Here's what makes this particularly difficult to confront: much of the busywork is structural, not accidental.

The status report doesn't primarily convey information. It signals allegiance to a shared reality. The weekly meeting isn't mainly about decisions. It's a communion ritual that maintains organizational cohesion. The documented process isn't really about standardization. It's about creating artifacts that prove work is legitimate and controlled.

Remove these practices and you don't reveal efficiency—you reveal that coordination was always about maintaining shared fictions. Organizations rely on busywork as connective tissue. It's how decentralized actors convince themselves they're part of the same enterprise pursuing the same goals.

AI threatens this in a way previous tools didn't. Email could be absorbed into the performance. Slack became another stage for the theater. But AI does something more dangerous: it makes the performance obviously performative.

When AI can generate the report instantly, the report is revealed as ritual. When AI can attend the meeting and produce the summary, the meeting is exposed as ceremony. When AI can create the content that creates more content, we're forced to ask what any of the content was ever for.

The panic in the workslop article isn't about AI doing work badly. It's about AI revealing that much of what we called "work" was already hollow—we just needed humans doing it to maintain the illusion of necessity.

The Core Illness

The workplace malady isn't about tools. It's about organizing around the appearance of productivity rather than its substance.

We've built systems where:

Presence matters more than outcomes
Activity signals commitment
Busyness demonstrates importance
Measurable outputs substitute for meaningful results
Everyone privately knows much of the work is theater, but saying so is taboo

This isn't a failure of efficiency. It's a failure of honesty about what work is actually doing.

We know this. The Office Space reference in the AI liberation article isn't accidental—that movie resonated because Peter's confession about working 15 minutes a week was uncomfortably relatable. We have an entire genre of workplace humor built around this recognition. Dilbert. Bullshit jobs. "Meetings that should have been emails." The knowing laughter at productivity theater.

But knowing and acknowledging are different things.

Acknowledging would require asking dangerous questions:

If this role disappeared, what would actually stop happening?
If we didn't produce this report, who would notice and why?
If we canceled this meeting series, what decisions would go unmade?
If we cut this budget line, what value would cease to be created?

These questions are dangerous because the answer is often "nothing" or "very little" or "we're not sure."

Why It Persists

The productivity apparatus exists to avoid confronting the question of purpose.

Because admitting the core illness would require admitting uncomfortable truths:

For workers: Much of what fills our days may not need doing. Our employment might rest on continuing the performance.

For managers: We may be supervising activity that doesn't create value. Our role might be coordinating elaborate rituals rather than accomplishing objectives.

For organizations: We've optimized for measuring work rather than achieving outcomes. Our structures might exist to perpetuate themselves.

For the economy: Significant portions of activity might be circular—work created to employ people who create work to employ people. The device hoarding article accidentally reveals this: consumption to sustain production to enable consumption. The actual utility of newer phones is incidental to the economic necessity of the upgrade cycle.

If significant portions of knowledge work exist primarily to justify knowledge work, then:

White-collar employment figures become suspect
GDP calculations include circular activity
Entire industries (consulting, enterprise software, professional development) rest on perpetuating the problems they claim to solve
Individual careers are built on expertise in systems that might not need to exist

This is too destabilizing. So we have endless debates about which tool is best, how to measure engagement, whether we're adopting fast enough. These are safe conversations. They accept the frame. They assume the underlying activity is legitimate and we just need better optimization.

Much easier to argue about which tool is helping or hurting.

The Cycle Continues

AI won't break this pattern. The next technology won't either.

The cycle persists because the scapegoat-and-savior dynamic serves a function: it lets us continually discuss productivity problems without confronting what we're actually productive at.

We're extraordinarily productive at:

Generating reports no one reads
Attending meetings that accomplish nothing
Creating content that creates more content
Building systems to measure systems
Adopting tools to manage tool adoption

We're just not sure what any of it is for.

Maybe that's why the "device hoarding" framing is so revealing. It's desperately trying to pull the conversation back to something tangible: "No, no—the problem is physical! It's the age of the glass rectangle! We can fix this with consumption!"

Because the alternative—that we've built elaborate systems of mutual surveillance and self-justification that have only a tenuous relationship to creating actual value—is too destabilizing to confront.

Better to measure the measurements and watch the watchmen.

What We've Actually Built

The shape behind all the shadows—device age, AI adoption, workslop, productivity metrics—is this:

We've organized economic life around demonstrating busyness rather than creating value, and we've done it so thoroughly that we can no longer reliably distinguish between the two.

The primary product of much knowledge work isn't output for external stakeholders. It's the appearance of productivity itself—something generated, measured, reported, and consumed entirely within closed organizational loops.

The work produces:

Artifacts that prove work was done
Metrics that prove the artifacts matter
Meetings that prove we're coordinating
Tools that prove we're optimizing
Reports that prove the tools are working
Consultants who prove we're serious about improvement

But the chain never exits the building. It's a closed thermodynamic system generating entropy.

The tools change. The metrics evolve. The consultants offer new frameworks. But the fundamental evasion remains: we won't ask what it's all for because we're terrified of the answer.

Or rather, terrified there might not be one.

That realization feels strange at first.

It might also be necessary.