Executive Summary
When OpenAI CEO Sam Altman took the stage at DevDay 2025, he wasn't just announcing new features—he was declaring war on the traditional app ecosystem. ChatGPT users can now book homes on Zillow, design presentations in Canva, and stream Coursera lessons without ever leaving the chat window [3]. The Apps SDK, available in preview today, transforms ChatGPT from a conversational AI into what Altman calls 'a new generation of apps that are interactive, adaptive and personalized, that you can chat with' [3]. But as OpenAI makes its boldest platform play yet—complete with a reported multi-billion dollar AMD chip deal [5] and new agent-building tools [6]—cracks are appearing in the AI hype cycle. MrBeast, YouTube's biggest creator, publicly warned that AI poses an existential threat to creator livelihoods, calling them 'scary times' for the industry [4]. Even Taylor Swift fans revolted when promotional videos appeared AI-generated, highlighting growing public skepticism about synthetic content [1]. The question isn't whether OpenAI can build a platform—it's whether developers and users will trust it enough to abandon their existing app ecosystems.
Key Developments
- OpenAI Platform Strategy: Launched Apps SDK enabling third-party apps to run entirely within ChatGPT conversations, with integrations from Zillow, Canva, Coursera, Spotify, and others—positioning ChatGPT as an AI-first operating system [3][7]
- Infrastructure Investment: Secured major AMD chip deal for US data center expansion, betting on near-limitless AI demand even as skeptics warn of a bubble [5]
- Developer Tools: Released AgentKit for building production-ready AI agents and made Codex code assistant generally available with Slack integration and admin tools [6][13]
- Creator Backlash: MrBeast voiced concerns about AI threatening creator livelihoods while Taylor Swift fans criticized apparent AI use in promotional content, signaling growing public resistance [1][4]
- Security Initiatives: Google launched CodeMender, an AI agent for patching software vulnerabilities and securing existing code, addressing critical security concerns in AI-assisted development [12]
Technical Analysis
OpenAI's Apps SDK represents a fundamental architectural shift in how users interact with software. Built on Anthropic's open-source Model Context Protocol (MCP), the SDK allows developers to create apps that 'appear inline in chat as lightweight cards or carousels, expand to fullscreen for immersive tasks like maps, menus, or slides, or use picture-in-picture for live sessions such as video, games, or quizzes' [3]. During the DevDay demo, OpenAI engineer Alexi Christakis showed Coursera videos playing in picture-in-picture mode while ChatGPT answered questions about the lecture content in real-time—the underlying model received server-side updates from Coursera, enabling contextual responses without explicit user prompting [3].
The technical execution is impressive, but the business model raises immediate red flags. OpenAI announced an 'Agentic Commerce Protocol' (ACP) allowing developers to charge users for apps within ChatGPT, yet provided no details on revenue sharing, data access, or what happens to the much-hyped GPT Store launched just months ago [3]. When a platform controls both the distribution channel and the underlying AI that recommends apps, conflicts of interest become inevitable. Google faced similar scrutiny with Android and Chrome; OpenAI is walking into the same regulatory minefield with far less preparation.
The infrastructure bet tells a different story about OpenAI's confidence. The AMD chip deal, described as 'blockbuster' in scale, commits OpenAI to massive US data center expansion [5]. This isn't the behavior of a company hedging its bets—it's doubling down on sustained exponential growth. Yet the timing is curious: as OpenAI builds for unlimited demand, creators like MrBeast (with 394 million YouTube subscribers) are publicly questioning whether AI will destroy their business models [4]. When the world's most successful digital creator calls AI 'scary times,' it's worth asking whether the demand OpenAI anticipates will materialize—or whether we're watching the infrastructure for a market that doesn't exist yet.
Operational Impact
- For builders:
- The Apps SDK is available in preview today, but OpenAI won't accept new apps or enable payments until 'later this year'—use this window to prototype integrations and understand MCP before the platform floods with competitors [3]. Build with the assumption that OpenAI will eventually compete with successful third-party apps; focus on deep vertical integration rather than broad horizontal features.
- Google's CodeMender offers a practical near-term application: automated vulnerability patching and code security rewriting [12]. For teams managing legacy codebases, this addresses a real pain point—but verify all AI-suggested patches in staging environments before production deployment. The tool is most valuable for routine security updates, not architectural security decisions.
- If you're building agents, AgentKit provides production-ready infrastructure including deployment tools and optimization workflows [6]. However, the lack of pricing details for the 'complete set of building blocks' means you're committing to an ecosystem without knowing the long-term cost structure. Prototype with AgentKit but maintain architecture that allows migration to alternative frameworks.
- For businesses:
- The ChatGPT platform play creates a strategic dilemma: integrate early for access to 800 million users [3], or wait to see if OpenAI can avoid the platform governance failures that plagued Facebook's app ecosystem. Companies like Zillow and Coursera are betting on early-mover advantage, but remember that platform dependence is a liability when the platform owner can change terms unilaterally.
- For content-dependent businesses, the creator backlash signals a PR minefield. Taylor Swift fans immediately spotted and criticized AI-generated promotional content [1], while MrBeast's concerns about livelihood threats [4] reflect broader creator anxiety. If your business model depends on creator goodwill or authentic content, be transparent about AI usage—the trust cost of being caught using undisclosed AI may exceed any efficiency gains.
- The infrastructure investment [5] suggests OpenAI expects sustained growth, but 'near-limitless demand' claims should be treated skeptically. Businesses planning AI adoption should budget for price volatility as the market matures and competition intensifies. The current compute shortage won't last forever, and when supply catches up, the economics of AI services will shift dramatically.
Looking Ahead
OpenAI's platform strategy succeeds or fails on a single question: will developers trust a platform where the operating system, the AI recommending apps, and the commerce layer are all controlled by the same entity? Apple and Google spent decades building developer trust through (relatively) stable terms and clear revenue sharing. OpenAI is attempting to compress that timeline into months while simultaneously training models on unclear data sources and providing vague answers about the fate of existing developer programs like the GPT Store [3]. The creator economy backlash [1][4] points to a broader reckoning: as AI-generated content becomes indistinguishable from human-created work, authenticity becomes a premium product. Businesses that can credibly certify human creation—whether through blockchain verification, transparent attribution, or premium 'AI-free' tiers—may find unexpected market opportunities. The irony is that AI's success in mimicking human output may create demand for verifiably human alternatives. Google's security focus with CodeMender [12] and its broader AI security strategy [11] reveals where the next bottleneck will emerge: not in model capabilities, but in trust and safety infrastructure. As AI agents gain the ability to execute code, transfer money, and modify data autonomously, the security and liability frameworks become critical. The companies that solve AI security and auditability will capture more value than those racing to add features to already-capable models.