For years, the world of Machine Learning and Generative AI has been synonymous with Python. And rightly so, its data science roots, scientific computing libraries, and extensive ecosystem have made it the undisputed champion for training models and managing data pipelines. But with the shift in recent years, AI has been moving from the data lab to the hands of end-users and product developers, and those people rarely use Python. Fortunately, a significant shift is taking place: TypeScript is stepping up to the plate. 🚀
This isn’t a dig at Python by any means; I’m using Python a lot at work, and I enjoy it in many ways. That said, I’m simply excited that more and more AI tooling is emerging in a language that is intuitive for the vast majority of web developers who build customer-facing applications and developer-facing SDKs. This means building compelling AI experiences becomes more accessible to the web development community, and, as a result, to our products’ users as well.
If you know me, you probably know I usually post about WordPress, and more recently about AI in WordPress. If you’re wondering about why I suddenly post about TypeScript, it’s simply a language I have been exploring more and more – both in the context of WordPress and outside. In particular, I’ve been keeping a close eye on some of the more recent TypeScript ecosystem developments that make me increasingly excited about what the future holds for AI on the web. And this TypeScript revolution truly moves the needle in that regard.
The Developer-First Shift in the AI Ecosystem
The AI landscape is rapidly evolving from a domain primarily focused on data scientists to one driven by application developers. As AI features are integrated into every corner of the web and mobile experience, the need for a familiar and robust language for frontend and full-stack development becomes paramount.
TypeScript, with its static typing and seamless integration with modern web stacks, is proving to be the perfect fit. It allows developers to catch errors at compile time, reducing bugs and boosting confidence in complex AI application logic. The latter is a crucial benefit when dealing with the unpredictable nature of Large Language Models (LLMs). And worth noting, AI models are getting pretty good at writing TypeScript code themselves. Obviously, proficiency in AI is becoming more and more of a core skill, and TypeScript is positioning itself to be a preferred tool for this new reality.
It’s Not Just React and Next.js: Why TypeScript Matters Across Stacks
While the rise of Node.js has naturally positioned TypeScript at the center of full-stack development, its true power lies in its universality. For almost every modern application, regardless of the backend programming language – be it Go, Java, or our beloved PHP in the WordPress world – the frontend remains JavaScript. This ensures that expertise in TypeScript is a key skill for a massive majority of developers. If you’re developing for the web and have been hesitant – I’ve said it before and I’ll say it again: Learn TypeScript deeply.
The biggest innovation in AI application development is currently happening in the TypeScript ecosystem. And even if you’re not building on Node.js servers, or aren’t using React or Next.js, you can benefit from it as well, and you can get involved. Obviously, you shouldn’t call AI model provider APIs directly from client-side code, as that would leak your API credentials. But by implementing a simple custom connector on your non-JS backend to handle the model communication, your frontend application can fully benefit from the powers of this emerging ecosystem. That way, even if your production AI calls are handled by e.g. a PHP or Go backend, you don’t need to reinvent the wheel for the AI-driven user experience.
The Core Standard: The AI SDK and Provider Agnosticism
Every great ecosystem needs a unifying centerpiece, and in the TypeScript AI world, that is unequivocally the AI SDK by Vercel (GitHub repository). Over the past year, it went from 400k weekly downloads to over 3M weekly downloads. But the growth is just a testament to the important problems it is solving and that it is solving them well. There’s an entire ecosystem of tools forming around this open-source TypeScript toolkit, built by many different developers from many different companies.
A key reason that the AI SDK is a game-changer is because it standardizes the most fundamental piece of the AI application stack: the communication layer with different models, including from different providers.
Ending Vendor Lock-in
Historically, too many AI SDKs have been tightly coupled to a single provider (like Anthropic, Google, or OpenAI). This creates friction, leads to vendor lock-in, and forces organizations to duplicate effort if they want to leverage different models for cost, performance, or strategic reasons.
The AI SDK solves this with a unified, provider-agnostic API. It acts as a model router, allowing you to switch between models from probably any decently popular provider you can think of, simply by changing a single line of code. This flexibility is essential for:
- Cost Control: Directing routine work to more efficient, lower-cost models.
- Faster Innovation: Trying new models and features without a complete rewrite.
- Evaluation: Comparing different models in how well they perform against specific prompts or in an agentic setting becomes a breeze.
This model-agnostic approach is why the AI SDK is so inspirational and has led to an entire ecosystem of tools around it. Quick side note, its philosophy is precisely what we are aiming to adopt for the PHP ecosystem as we build the PHP AI Client SDK as part of the WordPress AI Team, ensuring the core of our AI infrastructure is flexible and provider-agnostic.
The Flourishing Tooling Ecosystem
As mentioned, the success of the AI SDK has triggered an exponential growth of new tooling, demonstrating that the TypeScript community is here to build a complete AI ecosystem.
Some examples:
- Mastra is a powerful AI agent framework for building autonomous systems, with a graph-based workflow engine to orchestrate complex multi-step processes.
- ai-sdk-tools is a collection of essential utilities for building production-ready AI applications, such as multi-agent orchestration or AI-specific dev tools.
- Evalite is an eval-first testing framework for LLM-powered applications, built on top of Vitest for familiar DX.
The power of all these TypeScript libraries is multiplied by their ability to integrate with the wider ecosystem of specialized AI platforms. While the frameworks above handle the logic and structure of your application, you’ll often need external services for specialized tasks:
- Code execution sandboxes like E2B or Vercel Sandbox are critical for agents that need to write and run code, providing a secure, isolated environment where LLM-generated code can be executed safely.
- AI observability platforms like Arize Phoenix help with shipping reliable AI features, by providing deep visibility into what the models are doing via tracing and evaluation.
The robust combination of dedicated TypeScript SDKs and powerful external tooling is growing rapidly, demonstrating how quickly the web development community is maturing the tools required to build and maintain sophisticated, production-ready AI applications.
The Road Ahead: Generative UI, and a TypeScript AI Conference
Beyond enhancing traditional user experiences with AI, the entire wave is leading to a revolution in how we think about user interfaces. The idea of “Generative UI”, where an agent generates the actual UI components or widgets needed to complete a task, rather than just returning a block of text, is transforming application development. It’s not an entirely new concept – early explorations go back a few years – but it’s been taking some time to sink in. Understandably, as it’s a major UX paradigm shift. I believe this is the future though, and the TypeScript SDKs are at the forefront of making the development of such experiences seamless and delightful. Generative UI is the true convergence of the modern web stack and AI, a space where TypeScript is uniquely positioned to lead.
As you can probably tell from reading this post, I’m enthusiastic about these trends. Needless to say that I got I excited when I learned that we’ll soon have the very first TypeScript AI conference, focused entirely on the intersection of TypeScript and AI, happening November 6. It’s a fantastic validation of this rapidly accelerating movement, and I’m looking forward to attending. Side note: I love the spicy tagline of the event: “Python trains, TypeScript ships.”
The TypeScript ecosystem isn’t just catching up to AI – it’s helping to redefine what AI development looks like for application builders. I’m super excited for what’s ahead.
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