YAYe Alleninvectronodeai.hashnode.dev00Designing Model Access for AI Workflows21h ago · 2 min read · AI products usually begin with one simple workflow. A developer connects one model, sends a request, receives a response, and builds the first useful version of the product. That is a good way to starJoin discussion
YAYe Alleninvectronodeai.hashnode.dev00Designing a Model Access Layer for AI Products1d ago · 2 min read · AI products often begin with a simple model integration. A developer connects one model, builds one feature, and ships a working prototype. That is usually the right way to start. But as the product gJoin discussion
YAYe Alleninvectronodeai.hashnode.dev00A Practical Way to Compare AI Models Across Product Workflows3d ago · 3 min read · AI model evaluation is often discussed as if there is one universal winner. In real products, that is rarely true. A model that performs well for chat may not be the best model for structured data extJoin discussion
YAYe Alleninvectronodeai.hashnode.dev00Designing a Model Access Layer for AI Apps and Automation4d ago · 3 min read · AI applications often begin with a simple integration. A developer chooses one model, writes a prompt, sends an API request, and builds the first version of the product. For prototypes, this is usuallJoin discussion
YAYe Alleninvectronodeai.hashnode.dev10How to Design a Model-Agnostic AI Application5d ago · 3 min read · AI applications often begin with one model. A developer connects an API, writes a prompt, tests a simple workflow, and ships the first version. For a prototype, this is usually the right approach. ButJoin discussion