Search Results for "make"

...Instead of treating AI models as black boxes behind simple prompts, Vibekit encourages developers to define declarative behaviors, reactive rules, and data flows that make the outputs of models part of living application logic. This can include things like dynamic content generation, live adaptation based on user interaction, and connectors to external APIs for enriched grounding. The toolkit also supports testing and local iteration, with utilities that simulate event streams and mock model responses to make development predictable.

Oh My OpenCode Slim is a lightweight, optimized fork of the broader oh-my-opencode ecosystem, designed to deliver high-performance multi-agent coding workflows while significantly reducing token consumption and system overhead. It retains the core concept of orchestrating multiple specialized AI agents but streamlines their configuration, execution, and communication to make the system more efficient and practical for everyday use. The framework introduces a structured “pantheon” of agents, each with a defined role such as orchestration, exploration, and execution, allowing tasks to be automatically delegated and completed through coordinated workflows. It supports multiple AI providers and models, enabling users to mix and match capabilities depending on cost, speed, and performance requirements.

Claude Code Architecture Study is an educational and experimental repository designed to teach developers how to build, configure, and understand AI coding agents from first principles. The project focuses on breaking down the architecture of agentic systems, including how models perceive context, make decisions, and execute actions in a coding environment. It likely provides step-by-step examples, conceptual explanations, and practical implementations that guide users through creating their own agents. The framework emphasizes learning by doing, allowing users to experiment with agent behavior, prompt design, and workflow structuring. ...

Agentation is a visual annotation and feedback tool designed to make interacting with AI coding agents more intuitive and precise by letting developers visually click on frontend elements in a browser and annotate them with context before sending structured feedback to an agent. Instead of describing UI elements in text — like “the blue button in the sidebar” — users click directly on elements to automatically capture selectors, positions, and contextual metadata that can be consumed by AI agents to locate exact code references. ...