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Didit is intentionally mirroring Stripe's strategy by creating a developer-first, API-driven infrastructure for the fragmented identity verification industry. The goal is to become the default, easy-to-integrate solution, just as Stripe did for payments, creating a new standard in a seemingly boring market.

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When building infrastructure for a nascent technology like AI agents, your core customers may not exist yet. This strategy, similar to Stripe's early days, involves betting on the future growth of an entire ecosystem. You are selling to the customers of tomorrow by building the foundational tools they will inevitably need.

To scale AI-driven purchases, Stripe and OpenAI developed an open standard for checkouts. The "Agentic Commerce Protocol" provides a standard API for businesses to express their checkout process, allowing AI agents to initiate transactions safely and programmatically, moving beyond brittle methods like web scraping.

AI agents prefer to interact with services via APIs and CLIs, not UIs. Companies like Stripe, which focused on a great developer experience from day one, are now perfectly positioned to serve this new, rapidly growing class of non-human users who demand programmatic access.

The founder predicts that making identity verification easy and frictionless will dramatically increase its use cases, from daily social media interactions to voting. This expands the market far beyond its current scope of compliance, much like Airbnb grew the overall travel accommodation market.

Horizontal developer tools struggle in fragmented markets. Their success is often tied to the emergence of a new, widely adopted standard (e.g., SAML 2.0 for Auth0). This creates a universal, complex problem that many developers are happy to outsource, providing a clear value proposition for the tool.

The user of developer infrastructure is no longer just a human engineer but also AI agents and coding assistants. Stripe has seen LLM traffic to its documentation grow 10x year-over-year, signaling a fundamental shift toward building products and documentation for machine-to-machine interaction.

Stripe's most successful ventures, like Atlas (incorporation), were not born from market-sizing spreadsheets. John Collison explains they originate from a relentless focus on solving acute, specific problems founders face. This philosophy prioritizes addressing tangible pain points over abstract market analysis, trusting that a large market will emerge.

Stripe intentionally designed its Agentic Commerce Protocol (ACP) to be provider-agnostic, working with any payments processor and any AI agent. This strategic decision to build an open standard, rather than a proprietary product, aims to grow the entire agentic commerce ecosystem instead of creating a walled garden.

The market is shifting to platforms, but best-in-class point solutions (like Plaid for bank verification) remain critical. The winning strategy isn't to build everything, but to package these specialized services into a cohesive platform, leveraging their focused excellence for distribution and governance.

Emily Sands advises startups against building their own databases to mirror Stripe's financial data. Instead, they should treat Stripe's highly reliable APIs (six nines uptime) as their system of record. This eliminates complex reconciliation work, freeing up scarce engineering resources for core product development.