A recent article claiming that AI coding tools have created an unprecedented red ocean of software competition is facing significant pushback from the developer community. The original piece argued that AI-assisted development has made it so easy to build and copy software that traditional differentiation strategies no longer work.
The article suggested that AI tools like Claude and other coding assistants have accelerated software development by 5x, leading to hundreds of competitors appearing in spaces that previously had only 5-10 players. However, many experienced developers are questioning whether this supposed explosion of AI-generated software actually exists.
The Complexity Cliff Reality
Seasoned developers point to what they call a complexity cliff in software development. While AI tools can help with basic applications, they struggle with sophisticated systems that require deep technical expertise. One developer noted that once you move beyond simple CRUD (Create, Read, Update, Delete) applications, AI assistance becomes far less effective.
This complexity barrier means that truly competitive software still requires significant human expertise, especially for systems involving intricate integrations, real-time collaboration features, or specialized domain knowledge. Products like Figma, with its advanced collaborative editing and custom rendering capabilities, remain far beyond what can be vibe coded using AI prompts.
CRUD applications are basic software programs that primarily handle data storage and retrieval operations - creating, reading, updating, and deleting information in databases.
Key Barriers to AI-Generated Software Competition:
• Complexity Cliff: Advanced software requiring deep technical expertise remains beyond AI capabilities • Integration Challenges: Complex, per-company integrations and hundreds of integration points • Regulatory Requirements: FDA, SEC, and other regulatory approvals create barriers • Network Effects: Products that improve significantly with more users • Domain Expertise: Specialized knowledge in complex niches (e.g., agricultural veterinary claims) • Corporate Limitations: Bureaucracy, risk aversion, and coordination issues unchanged by AI tools
Missing Evidence of the AI Explosion
Community members are questioning the fundamental premise of increased competition. Despite claims of a Cambrian explosion of software launches, developers report not seeing this flood of new competitors in established markets. Major platforms like Microsoft Office, Gmail, and Salesforce continue to dominate their spaces without facing the predicted wave of AI-generated alternatives.
Some pointed to previous analysis showing that app store submissions and other metrics haven't actually increased significantly in recent years, contradicting claims of an AI-driven software boom. The iOS App Store, which would be an obvious target for AI-generated applications, hasn't seen the expected flood of new competitors in various niches.
Evidence Against AI Software Explosion:
• No measurable increase in App Store submissions in recent years
• Major software markets (Office, Gmail, Salesforce) remain dominated by incumbents
• iOS App Store not seeing predicted flood of AI-generated competitors
• Complex software products like Figma remain beyond "vibe coding" capabilities
• 10% of new websites built with tools like Lovable, but mostly described as "broken shovelware"
Corporate Speed Myths
The article's claim that big companies can now move faster thanks to AI tools is drawing particular skepticism. Developers argue that corporate slowness was never about coding speed - it stems from bureaucracy, risk management, coordination across teams, and internal politics. Adding AI to the development process doesn't address these fundamental organizational barriers.
Big companies are going faster now? Where? Which ones? AI coding allows you to build prototypes quickly. All the reasons big companies are slow haven't budged.
The Real Differentiation Factors
While the original article suggested that traditional differentiation no longer works, community discussion reveals that meaningful competitive advantages remain intact. Complex integrations, regulatory compliance, network effects, and deep domain expertise continue to create substantial barriers to entry.
Developers working on specialized systems - from traffic monitoring to agricultural software - report that their work remains largely immune to AI disruption. These applications require understanding of specific industries, complex problem-solving, and integration with existing systems that go far beyond what current AI tools can handle.
The debate highlights a broader question about AI's current capabilities versus the hype surrounding them. While AI coding assistants have certainly improved developer productivity in certain areas, the community consensus suggests that reports of their disruptive impact on software competition may be greatly exaggerated.
Reference: Be Different doesn't work for building products anymore