OpenAI DevDay 2025: Apps Kill Assistant Competition

OpenAI just shifted from building a chatbot to creating the operating system for AI-first work. Agent Kit targets developers, but Apps SDK might be the stealth winner—turning ChatGPT into a context black hole that makes switching to competitors painful. With 800 million weekly users and seamless app integration, OpenAI isn't just competing with agent builders—they're rewriting how we interact with software entirely.

OpenAI DevDay 2025: The Real Agent Wars Just Began—Why Apps May Kill the Assistant Competition Before It Starts

October 5th marked a pivotal moment in AI platform strategy. At DevDay 2025, OpenAI unveiled two major announcements that signal its evolution from model provider to platform orchestrator. While the tech community fixated on whether Agent Kit would kill automation startups like Zapier and Lindy, the real disruption may come from an unexpected source: Apps in ChatGPT.

I'm Dr. Hernani Costa, founder of First AI Movers, where I help executives navigate the transformation to AI. Through my newsletter, which reaches over 5,000 professionals, and consulting work with dozens of companies, I've seen firsthand how platform shifts reshape entire industries. What happened at DevDay isn't just about new features—it's about OpenAI positioning ChatGPT as the universal interface layer for digital work.

This analysis cuts through the hype to reveal the strategic implications for business leaders, developers, and anyone building in the AI ecosystem. You'll discover why the real competition isn't happening where everyone's looking, and what this means for your AI strategy. The most fascinating insight? The app that you least expect to disrupt your workflow might already be running inside ChatGPT.

Did OpenAI Just Launch the Internet's New Operating System?

The numbers tell the story: 800 million weekly ChatGPT users, 4 million developers building with OpenAI, and 6 billion tokens processed per minute on their API platform. These aren't just usage metrics—they represent the scale at which OpenAI can introduce new interaction paradigms.

But here's what caught my attention: OpenAI explicitly stated they "never meant to build a chatbot; we meant to build a super assistant, and we got a little sidetracked". This admission reveals their strategic pivot isn't about adding features—it's about returning to their original vision of AI as the ultimate productivity layer.

The DevDay announcements cluster into four strategic categories, each targeting different aspects of the AI workflow:

Agent Kit represents the developer play: A visual canvas for creating multi-agent workflows, complete with evaluation tools and deployment infrastructure. The live demo showed an 8-minute build-and-ship cycle for a functional agent, highlighting OpenAI's focus on reducing development friction.

Apps SDK reveals the platform strategy: Native applications running directly inside ChatGPT, built on the Model Context Protocol (MCP) that keeps server, model, and UI synchronized. Early partners include Coursera, Canva, Zillow, Spotify, Figma, and major booking platforms.

The competitive implications are immediate. OpenAI might have just killed Zapier, Make, n8n, Lindy with their new agent builder. However, this analysis overlooks the more profound strategic shift underway.

The Agent Builder Arms Race: Why the "Killer" Narrative Misses the Point

The immediate reaction centered on whether Agent Kit poses a threat to established automation platforms. Lindy's founder struck a defiant tone, welcoming OpenAI to "the most exciting category in AI". Zapier emphasized their ecosystem advantage: 8,000 apps and 30,000 actions versus OpenAI's limited native integrations.

These responses reveal important competitive dynamics, but they also illustrate strategic misunderstanding. Agent Kit isn't designed to replace Zapier or n8n—it's targeting a different user base entirely.

Based on my analysis of the demos and documentation, the Agent Kit remains decidedly technical. Even the simplest workflows require coding knowledge, and the platform is explicitly positioned as "a tool for developers to integrate and build agents more quickly" rather than a consumer agent builder.

The competitive reality is more nuanced:

• Model flexibility remains a wedge: Enterprises prioritizing the ability to switch between different foundation models won't lock into OpenAI's ecosystem exclusively. This creates sustainable differentiation for platforms like n8n and Zapier that support multiple model providers.

• User experience intimidation persists: The visual workflow design paradigm—whether from Zapier, Lindy, or now OpenAI—remains niche and intimidating for non-technical users. OpenAI's entry might normalize this UX pattern, potentially expanding the overall market rather than just redistributing existing users.

• Distribution vs. flexibility trade-off: OpenAI's incredible distribution power comes with inherent platform lock-in. Companies that built their competitive advantage on avoiding vendor dependencies won't suddenly embrace single-provider solutions.

My take? The agent builder competition will likely follow the historical pattern of enterprise software: multiple viable solutions serving different customer segments, with OpenAI capturing the "OpenAI-first" development community while established platforms retain customers who prioritize flexibility and integration breadth.

Apps in ChatGPT: The Stealth Platform Play That Changes Everything

While everyone debated Agent Kit's competitive impact, OpenAI quietly launched what might be their most strategically significant feature: Apps in ChatGPT. This isn't GPTs 2.0—it's fundamentally different architecture that could reshape how we interact with digital tools.

The key distinction lies in deep integration: Unlike previous attempts at AI app stores, the Apps SDK enables what OpenAI calls "talking to apps"—meaning ChatGPT maintains context of what you're experiencing within each application and can interact meaningfully with that context.

Consider the Coursera example from the DevDay demo: A user watching an educational video can pause and ask ChatGPT to explain a complex concept, and ChatGPT has full context of the video content to provide relevant clarification. This isn't just convenience—it's a qualitatively different learning experience that can't be replicated by switching between Coursera and ChatGPT as separate applications.

The Zillow integration demonstrates similar contextual power: After browsing property listings, users can ask ChatGPT questions that Zillow's app can't answer directly—like proximity to dog parks or school district quality—while maintaining full context of the specific properties under consideration.

These examples reveal why Apps in ChatGPT represents a different category of integration than traditional app stores or plugin ecosystems. The Model Context Protocol creates bidirectional context sharing that enables genuinely new user experiences rather than just convenient access to existing functionality.

The Context Black Hole Strategy: Why Switching Costs Just Became Massive

Here's the strategic insight that most analysis has missed: Apps in ChatGPT might function as a context black hole—once users experience seamless AI assistance integrated with their workflows, the switching costs to competing platforms become enormous.

Let me explain through a concrete scenario. Imagine using Coursera's educational content with ChatGPT's tutoring capabilities for several weeks. Your learning conversations, progress insights, and personalized explanations all live within the ChatGPT context. Now imagine trying to switch to Claude or Gemini for your learning assistant.

You lose everything: All the contextual understanding of your learning style, your previous questions, your areas of struggle, and the accumulated knowledge of your educational journey. The switching cost isn't just about choosing a different AI model—it's about abandoning weeks or months of personalized context that makes the assistant truly useful.

This dynamic extends across all integrated applications. A real estate search assisted by ChatGPT accumulates context about your preferences, budget constraints, location priorities, and decision-making patterns. Switching to a different AI assistant means starting that entire context-building process from scratch.

From a competitive strategy perspective, this represents defensible differentiation through accumulated context rather than superior technology. Even if Anthropic or Google develops better foundational models, the friction of recreating established workflows and context within new platforms creates substantial user retention.

My prediction: Within 12 months, we'll see users who are technically aware that competitor models might perform better on specific tasks, but who remain locked into ChatGPT because their integrated workflows and accumulated context make switching prohibitively costly.

The Broader Platform Implications: From Model Wars to Interface Wars

The DevDay announcements signal a fundamental shift in AI competition. We're transitioning from the "model wars" focused on capabilities and benchmarks to "interface wars" focused on user experience and ecosystem lock-in.

This shift has immediate implications for AI strategy:

• For developers: The question is no longer just "which model is best?" but "which platform provides the most comprehensive development and deployment infrastructure?" OpenAI's Agent Kit, combined with their API ecosystem, creates a compelling answer for teams that don't need multi-model flexibility.

• For enterprises: The evaluation criteria expand beyond model performance to include integration depth, context persistence, and workflow continuity. Companies need to assess whether OpenAI's platform advantages outweigh the risks of single-vendor dependency.

• For competitors: The strategic response can't focus purely on model capability improvements. Anthropic, Google, and other foundation model companies need platform strategies that provide comparable workflow integration and context persistence—or they risk becoming infrastructure providers for OpenAI's platform.

The historical parallel is revealing: During the mobile platform wars, having a superior mobile operating system (like Windows Mobile's features) wasn't sufficient to compete with iOS and Android's ecosystem advantages and developer mindshare. The same dynamic may be emerging in AI platforms.

Bringing It All Together

OpenAI DevDay 2025 represents more than product announcements—it's the first clear articulation of platform strategy in the post-ChatGPT era. While the developer community debates whether Agent Kit poses a threat to existing automation platforms, a more significant disruption may come from Apps in ChatGPT, creating new interaction paradigms and incurring switching costs.

The strategic takeaway for business leaders: We're entering a phase where AI competitive advantage comes not just from model capabilities, but from platform integration depth and accumulated context. Organizations developing AI strategies must assess both the immediate functionality and the long-term platform lock-in implications.

For developers and founders, the agent building space remains competitive and viable, especially for teams that prioritize model flexibility and avoid vendor lock-in. However, the bar for user experience and integration depth has been raised significantly.

The broader industry trend: We're transitioning from AI as a capability to AI as an interface layer. The companies that win won't necessarily have the best models—they'll have the most seamless integration between AI intelligence and daily workflows.

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Hi, my name is Dr. Hernani Costa, Founder of First AI Movers. For inquiries and partnerships, contact me at info at firstaimovers dot com; or message me on LinkedIn.