The Developer Honeymoon
It’s easy to see why developers are thrilled. OpenAI’s recent announcements were a feast of new capabilities. The introduction of GPT-6.1 Sol promises near-top-tier intelligence at a fraction of the previous cost, making complex AI workflows more affordable.
The launch of persistent, always-on agents, nicknamed 'Dots', alongside an Agents API, offers a new paradigm for building services that can handle ongoing tasks. Add to that a suite of developer-focused upgrades—from a voice-enabled Codex CLI to new ways to integrate apps directly inside ChatGPT—and it feels like a golden age for building AI-powered products. For many startups and engineers, these tools aren't just incremental updates; they unlock entirely new possibilities that were once prohibitively expensive or complex.
The Platform Risk Reality Check
Here’s the catch: when you build your house on someone else’s land, you’re always subject to their rules. In tech, this is called platform risk. It's the danger that a platform you depend on—like OpenAI—will make a change that hurts your business. This isn't just about API outages. It’s about sudden price hikes that wreck your margins, or the deprecation of a model your product relies on. It's the risk that a policy change or new regulation could upend your entire service. Relying on a single, closed-source provider for a core part of your business is a strategic gamble. That 'secret sauce' in your app might just be a service that the platform owner is happy to sell to your direct competitors, too.
Beware of Being 'Sherlocked'
The most terrifying flavor of platform risk has a name: getting 'Sherlocked'. The term originates from when Apple launched a feature called Sherlock that replicated the functionality of a popular third-party app called Watson, effectively making it obsolete overnight. Every OpenAI DevDay brings a fresh wave of this fear, summed up by the meme: 'Every time OpenAI has a Dev Day, a thousand startups die'. When OpenAI demonstrates new agent capabilities or native PDF-reading functions, it's directly entering territory previously occupied by innovative startups. Because the platform owner has access to usage data and controls the underlying technology, it's uniquely positioned to identify popular use cases and build its own native, often free, versions, leaving third-party developers out in the cold.
Building a Moat in the Age of AI
So what’s a forward-thinking developer to do? The answer isn't to shun OpenAI's powerful tools, but to use them intelligently. The key is to avoid building a business that is merely a thin wrapper around a GPT API call. Your value must come from somewhere else. Build a unique user experience, cultivate a strong brand, and own the relationship with your customer. Create a 'moat' by solving a specific customer problem in a way OpenAI's more generic tools can't. Strategically, this could mean designing your systems to be model-agnostic, allowing you to switch between providers like OpenAI, Anthropic, or open-source alternatives as needed. The goal is to treat the AI model as a powerful, but replaceable, component in your engine—not the entire vehicle.
