Three different philosophies for building AI apps
LangChain, the OpenAI Assistants API, and the Vercel AI SDK all help you build applications on top of large language models, but they sit at very different points on the abstraction spectrum. Choosing well depends less on which is “best” and more on what you are building, which language you work in, and how much control you want to keep.
LangChain: the maximal framework
LangChain is a large, provider-agnostic framework available in Python and JavaScript. It offers high-level abstractions for chains, agents, tools, memory, and retrieval-augmented generation, plus integrations with dozens of model providers and vector stores. Its strength is breadth: if you need a documented pattern for an agent that calls tools, queries a vector database, and remembers conversation state, LangChain probably has it.
The cost is complexity. The layers of abstraction can make behaviour harder to trace, and the library evolves quickly, so code can break between versions. LangChain suits teams building complex, multi-step pipelines who value pre-built components over a minimal surface area, and who are comfortable reading through abstractions when something goes wrong.
OpenAI Assistants API: managed and server-side
The Assistants API is OpenAI’s managed service for building assistant-style apps. Instead of orchestrating conversation state, tool calls, and document search yourself, you create an assistant, attach tools and files, and let OpenAI manage persistent threads and the tool- calling loop on its servers. This removes a lot of infrastructure work — you do not run your own state store or retrieval pipeline.
The tradeoff is lock-in and control. Everything runs on OpenAI with OpenAI models only, so you cannot swap in Claude or an open-weight model, and you depend on OpenAI’s feature set, latency, and pricing. It is a good fit when you are committed to OpenAI and want to ship quickly without building orchestration yourself.
Vercel AI SDK: lightweight and streaming-first
The Vercel AI SDK is a TypeScript-first library focused on the things web apps actually need: a unified interface across many providers (OpenAI, Anthropic, Google, and others), first-class streaming, tool calling, and React hooks for building chat and generative UIs. It is deliberately thin — it does not impose a heavy agent framework on you, so the code you write stays close to the underlying API calls.
This makes it easy to reason about and debug, and easy to switch providers by changing a few lines. The flip side is that for very elaborate agent workflows you may end up writing more orchestration yourself than LangChain would require. For most web and product teams, that explicitness is a feature rather than a limitation.
How to choose
Pick the Vercel AI SDK for TypeScript web apps that need streaming UIs and provider flexibility with minimal abstraction. Pick the OpenAI Assistants API when you are happy to stay on OpenAI and want a managed service that handles threads, tools, and file search for you. Pick LangChain when you need a rich toolkit of pre-built agent, memory, and retrieval components and are building complex, multi-step pipelines. Many teams even combine them — using the AI SDK for the UI layer while reaching for heavier orchestration only where it genuinely earns its keep.