TensorFeed Originals

Every morning I found myself opening a dozen tabs to check AI news, model releases, and API status pages. TensorFeed started as a personal frustration and grew into an aggregated hub built for humans and AI agents alike.

The API landscape shifted dramatically over the past year. Pricing wars, the context window race, agent-native endpoints, MCP protocol adoption, and structured outputs all reshaped how developers build on AI. We break down what matters.

Benchmarks only tell part of the story. We ran all three frontier models through real-world coding, writing, analysis, and research tasks. Here is what we found, including a task-by-task scorecard and pricing comparison.

AI agents are moving from demos to production, and the software they need looks different from traditional web apps. Structured data, llms.txt, MCP servers, and agent-friendly API design patterns that actually work.