The Collaboration Tax: How AI Tools Punish Small Teams

A curious thing happens when you try to collaborate on a Claude Project. Despite paying $100 monthly for the premium tier, you discover that sharing your work requires jumping to a team plan with a five-person minimum—$150 per month, whether you need five seats or just one extra.

This isn't merely inconvenient pricing. It represents something more troubling: the systematic exclusion of small teams from the tools reshaping how we work and think.

The Arithmetic of Exclusion

The mathematics reveal the problem starkly. A high-value individual customer contributes $1,200 annually to Anthropic's revenue. That same customer wants to add a single collaborator—perhaps a business partner, co-founder, or close colleague—and would happily pay an additional $240 yearly for the privilege.

Instead, the platform demands they quintuple their commitment or remain isolated. The message is clear: small teams don't matter enough to accommodate with flexible pricing.

This pattern extends far beyond Claude. Apple and Google have optimized their app stores for large development teams while creating increasingly hostile environments for independent creators. Platforms that once celebrated garage inventors now squeeze out anyone who can't navigate enterprise-grade bureaucracy.

The Cursor Paradox

Recent industry movements add delicious irony to this story. Cursor, now generating over $500 million in annual recurring revenue, just executed one of tech's boldest talent acquisitions: hiring Boris Cherny and Cat Wu, the lead developer and product manager of Claude Code, directly from Anthropic.

The audacity is breathtaking. Cursor built their success on Anthropic's models, becoming one of their largest customers. Now they're poaching the very people who built competing products, while continuing to rely on Claude's underlying intelligence.

This represents a new form of platform parasitism—companies that simultaneously depend on and compete with their suppliers, extracting talent while maintaining commercial relationships. Anthropic finds itself in the peculiar position of powering a competitor that just gutted their product development team.

When Mediocrity Becomes Multiplicative

Perhaps the most fascinating aspect of AI-democratized development is how it transforms "mediocre" programmers into juggling acts. With AI assistance, developers who previously struggled with complex frameworks now manage five or six projects simultaneously.

Each project becomes a learning laboratory. Techniques discovered while building a customer database inform approaches to content management systems. Patterns learned from e-commerce implementations enhance project management tools. The compound effect accelerates rapidly.

Traditional gatekeeping mechanisms—deep framework knowledge, syntax mastery, architectural expertise—dissolve when AI handles implementation details. The bottleneck shifts from technical execution to idea validation and AI collaboration skills.

This democratization terrifies established players who built moats around specialized knowledge. When anyone can spin up sophisticated applications, the value of coding credentials diminishes while the premium on creative vision increases.

The Enshittification Spiral

Cory Doctorow's concept of "enshittification" perfectly describes the trajectory we're witnessing. Platforms begin by delighting users, then abuse users to attract business customers, finally abusing business customers to appease shareholders.

GitHub exemplifies this pattern. Microsoft's acquisition initially seemed benevolent—more resources, better infrastructure, enhanced features. But the fundamental dynamic remains: a single corporation controls the primary collaboration platform for global software development.

The irony cuts deep. Linus Torvalds created Git specifically to escape proprietary version control systems after BitKeeper betrayed the Linux community. Yet GitHub successfully re-centralized what Git was designed to distribute, creating precisely the dependency lock-in that Git was meant to prevent.

The Training Data Irony

The deepest irony emerges from AI training itself. These systems learned to articulate arguments against corporate power by consuming the copyrighted works of critics like Doctorow without permission or compensation.

AI can now eloquently discuss platform monopolization, creator exploitation, and digital feudalism—using knowledge extracted from the very writers who identified these problems. The critics' work trains the systems that perpetuate their critiques.

This represents a perfect closed loop of extraction. Creators produce insights about corporate overreach. Corporations scrape those insights to build commercial products. The resulting AI systems can reproduce the original arguments while generating profit for the companies being criticized.

The Collaboration Opportunity

Yet market gaps create opportunities. The demand for small team collaboration in AI tools is obvious and underserved. Someone will eventually build platforms that treat two-person partnerships as seriously as fifty-person enterprises.

The technical barriers are minimal—collaboration features don't require massive scale to implement effectively. The real barriers are philosophical: most platform companies optimize for enterprise revenue rather than user experience.

This creates openings for competitors who understand that serving small teams well can build larger customer bases than forcing artificial minimums. Cursor's success demonstrates how quickly positions can shift when someone addresses real user needs.

Defending the Open Web

Despite corporate consolidation, the fundamental internet protocols remain surprisingly open. Email still works across providers. Websites can bypass app store gatekeepers. Open source software continues thriving despite billions spent trying to control it.

The web platform itself represents humanity's greatest escape route from platform tyranny. As long as browsers can render HTML and JavaScript executes freely, independent creators retain the ability to reach audiences directly.

This openness feels fragile, dependent on the continued goodwill of companies that profit from controlling access. But it persists, offering hope that innovation can still emerge from garages rather than corporate campuses.

The Path Forward

The collaboration tax imposed by AI tools reflects broader tensions between technological possibility and corporate control. When platforms punish small teams, they reveal priorities that favor revenue concentration over innovation distribution.

Smart companies will recognize that serving creators and small teams builds stronger foundations than extracting maximum value from enterprise customers. The most successful platforms historically became indispensable by solving real problems elegantly, not by creating artificial scarcities.

The current moment offers a choice: accept the collaboration tax as inevitable, or demand tools that serve human creativity rather than corporate convenience. The companies that choose users over shareholders may find themselves inheriting the future.

After all, today's garage projects become tomorrow's platform disruptions. The question is whether current platforms will enable that transformation or become the obsolete infrastructure it replaces.