Search results for "Exa"

Public Prompts is a community-driven, free library of AI prompts, models, and embeddings designed for image generation tools like Stable Diffusion. The platform features carefully selected high-quality examples categorized by style, providing detailed parameter "recipes" to help users efficiently generate high-quality AI images. No registration is required; it's completely free.

2026-07-09

Exa is an infrastructure company providing search APIs for AI agents. Unlike traditional search engines, it uses neurosemantic search technology to enable AI to truly "understand" query intent, rather than simply matching keywords. Its self-built search engine covers over 500 billion URLs, offering multi-layered APIs ranging from ultra-fast searches (less than 200 milliseconds) to in-depth research. It has been adopted by over 5,000 companies, including Cursor, Cognition, and HubSpot, and by 400,000 developers. In 2026, it completed a $250 million Series C funding round, valuing the company at $2.2 billion.

2026-07-14

The "Vibe Coding" wave is here: ordinary people can now independently create websites and utility software using AI—simply by describing their requirements in natural language—without needing to master any actual code. This article explains the underlying principles, available tools, and real-world implementation examples.

OpenClaw Refactor Docs is a skill designed for the source-audit-driven refactoring of existing OpenClaw documentation pages. Building upon the `openclaw-docs` skill—which handles style, page types, examples, and validation—it introduces a refactoring workflow that mandates the preservation and verification of all behavioral facts during rewriting, restructuring, splitting, or streamlining; this ensures that accurate descriptions of system behavior are not lost in the process. It requires source-based verification (against source code, tests, or schemas) for all behavior-sensitive information—such as configuration fields, commands, default values, and permission rules—rather than relying on inferences based on names or intent.