Tool Calling — Topic Summaries
AI-powered summaries of 29 videos about Tool Calling.
29 summaries
Claude 4 is here. It's kinda nuts.
Claude 4’s release lands with a clear split: Sonnet 4 looks like a meaningful upgrade for developers—especially for coding, tool use, and...
GPT-4.1 is here, and it was built for developers
OpenAI’s GPT-4.1 launch is aimed squarely at developers, with the biggest shift being a 1 million token context window delivered through the API—not...
What even is an AI Agent?! (The Standup)
AI agents for software development are essentially an LLM wired to programming tools and kept running through iterative “loops” until the task is...
MCP is the wrong abstraction
Model Context Protocol (MCP) is getting a reality check: flooding AI agents with tool definitions and tool-call syntax often degrades performance,...
OpenAI’s open source models are finally here
OpenAI’s newly released open-weight models—an “120B” and a “20B” variant—are built to run locally, and early testing suggests the smaller 20B model...
It’s time to embrace the AI
AI-assisted programming has shifted from “chatting with a model” to “delegating work to agents that can navigate a real codebase,” and that change is...
Is Claude 4 a snitch? I made a benchmark to figure it out
A wave of claims that Claude “snitches” by contacting regulators and the media is traced to a specific safety test scenario: models can attempt to...
Tool Calling in LangChain | Generative AI using LangChain | Video 17 | CampusX
LangChain tool calling turns an LLM from a text-only assistant into a system that can use external functions safely—by letting the model *suggest*...
smolagents - HuggingFace's NEW Agent Framework
Hugging Face’s new “smolagents” framework pushes agent building toward “code agents”: instead of forcing an LLM to emit JSON-style plans, it can...
The Gemini Interactions API
Google’s new Gemini Interactions API reframes how developers build with Gemini models by shifting from simple, stateless “prompt in, text out” calls...
Context Engineering is the future of AI Agents - here’s why
Multi-agent “teams” are a reliability trap for most production AI agents, and the fix is simpler: design around context sharing and make action...
Build Hour: GPT-5
GPT-5 is positioned as OpenAI’s “smartest, most steerable” coding model yet—built to produce higher-quality code, handle long-running agentic...
How to Build Super Effective AI AGENTS - FULL TUTORIAL | Cursor - OpenAI
A practical AI-agent pipeline for handling customer emails end-to-end is built in Cursor: it ingests an incoming message, extracts key fields with...
PydanticAI - The NEW Agent Builder on the Block
PydanticAI positions itself as a new, Pydantic-first agent and LLM application framework built to make model outputs reliably conform to structured...
Introducing Swarm with Code Examples: OpenAI's Groundbreaking Agent Framework
OpenAI’s Swarm has landed as a lightweight framework for building multi-agent systems, and the core idea is simple: model behavior as small...
ChatGPT 5.1 Is the First True AI Worker: Here's What Changed
ChatGPT 5.1’s biggest shift isn’t its “warmer” tone—it’s a more agentic, production-ready model that follows instructions more faithfully, routes...
Google just destroyed ChatGPT forever… (Gemini 2.5 Pro)
Gemini 2.5 Pro is getting an early-access upgrade that pushes hardest on coding—especially building interactive, good-looking web apps—while also...
How to make Muilt-Agent Apps with smolagents
Multi-agent apps built with smolagents work best when the system leans on tool-calling and strong hosted models—small local “code agents” tend to...
The AI Failure Mode Nobody Warned You About (And how to prevent it from happening)
AI agents don’t fail only by hallucinating or lacking context—they often fail by confidently acting on a misread intent. The core problem is an...
How to build MCP Clients | MCP Trilogy | CampusX
The core takeaway is a working blueprint for building an MCP-powered chat client that can automatically discover tools from one or more MCP servers,...
SmolLMv3 - A Small Reasoner with Tool Use.
Hugging Face has released SmolLMv3, a 3B-parameter language model aimed at “small” local deployment without giving up reasoning and tool use. The...
Build Hour: Voice Agents
Voice agents are moving past “transcribe-and-reply” toward audio-native systems that can sound more like real representatives, handle ambiguity, and...
Build More Effective AI AGENTS With "Code As Action"
“Code as action” lets AI agents do multi-step tool work in one shot by generating and running code (including loops), instead of chaining dozens of...
Build 100% Local Chatbot with Gemma 3, Ollama and LangChain | AI Assistant with Memory and Tool Use
A fully local chatbot can now keep both conversation history and long-term “memories” across separate chats—without sending data to a hosted service....
Build AI Agent Application with Agent Development Kit (ADK) | Get Started with Google's Agent SDK
Google’s Agent Development Kit (ADK) is positioned as a practical way to build agentic applications with a clear workflow structure, built-in...
Use Any LLM Provider with LiteLLM | Use ChatGPT, Claude, Gemini, Ollama with One API
Switching between large language model (LLM) providers can break production systems when code depends on a single vendor’s SDK. LiteLLM is presented...
NEW from OpenAI: The Swarm is coming
OpenAI’s new Swarm multi-agent API signals a shift from building standalone large language models to building an “operating system” layer for...
DeepSeek R1 0528 - Better Coding & Tool Calling | Is It Faster Now?
DeepSeek R1 0528’s update centers on making the model more usable for real-world coding agents by adding support for JSON output and function...
LangChain Tutorial: The Core Building Blocks | LLMs, JSON output, RAGs, Tools and Observability
LangChain’s practical value comes from a small set of reusable building blocks: a unified way to call different LLM providers, structured outputs...