Thinking Claude is an approach to interact with Claude that highlights the depth of his reasoning process. It focuses on experiencing Claude's fascinating inner thought process during daily tasks and conversations. Unlike other methods that emphasize benchmarks or mathematical breakthroughs, this approach encourages detailed thought processes and exploration, making AI interaction more insightful and engaging. The goal is to enhance the quality of daily interactions by revealing how Claude thinks through problems step by step.

Dokko is a no-code conversational AI platform designed to transform your organization's documents into a centralized, actionable knowledge base. It allows for easy data upload, creates an instantly accessible AI-ready knowledge base, and deploys multilingual chatbots within minutes. Dokko ensures reliable responses with safeguards against AI hallucinations and supports various use cases including customer support, research assistance, and compliance training.

The Dialogflow Fulfillment Python Library is an open-source framework that handles HTTP requests from Dialogflow, maps intents to Python handler functions, manages session and output contexts, and builds structured responses including text, cards, suggestion chips, and custom payloads. It abstracts the JSON structure of Dialogflow’s webhook API into convenient Python classes and methods, accelerating the creation of conversational backends and reducing boilerplate code when integrating with databases, CRM systems, or external APIs.

Imbue is a conversational AI agent that enables users to engage in meaningful dialogues, providing them with insights and recommendations based on contextually relevant information. Its features include automated responses, content generation, and collaborative brainstorming, making it an invaluable tool for teams and individuals. By enhancing communication, Imbue helps users save time and drive productivity, whether for brainstorming sessions, project discussions, or casual conversations.

Langchainrb is an open-source Ruby library designed to streamline the development of AI-driven applications by offering a modular framework for agents, chains, and tools. Developers can define prompt templates, assemble chains of LLM calls, integrate memory components to preserve context, and connect custom tools such as document loaders or search APIs. It supports embedding generation for semantic search, built-in error handling, and flexible configuration of models. With agent abstractions, you can implement conversational assistants that decide which tools or chain to invoke based on user input. Langchainrb's extensible architecture allows easy customization, enabling rapid prototyping of chatbots, automated summarization pipelines, QA systems, and complex workflow automation.