Tool Use — Topic Summaries
AI-powered summaries of 17 videos about Tool Use.
17 summaries
Build Anything with AI Agents, Here's How
AI agents are positioned as the practical route to the next wave of general-purpose intelligence—because they can do work toward a goal instead of...
Apple’s ‘AI Can’t Reason’ Claim Seen By 13M+, What You Need to Know
A widely circulated claim that Apple’s latest AI work shows large language models can’t “reason” is met with a blunt counterpoint: these systems...
Claude 4 System Prompt
Anthropic’s published Claude 4 system prompts for Claude Opus 4 and Claude Sonnet 4 read like an operating manual: they tightly define how Claude...
Stop using ChatGPT, build Agents instead - Maya Akim
AI agents are framed as the next practical step beyond chatbots—because they can act, use tools, and iterate at scale—yet the biggest obstacle...
Function Calling with Local Models & LangChain - Ollama, Llama3 & Phi-3
Running function calling and structured JSON outputs locally is practical with smaller open models—especially Llama 3 8B on Ollama—and it enables...
Let's Talk THAT Apple AI Paper—Here's the Takeaway Everyone is Ignoring
Apple’s research paper on “reasoning” language models sparked a wave of memes claiming AI is fake or that reasoning has been disproven. The more...
LangChain Agents: Build Personal Assistants For Your Data (Q&A with Harrison Chase and Mayo Oshin)
LangChain agents are built around a simple but powerful idea: use a language model as a reasoning engine, then let it reliably choose and run...
Build Genius AI Agents with Prompt Engineering
Prompt engineering sits at the center of building capable AI agents because every agent’s “brain” is a large language model that predicts the next...
The 4 Stacks of LLM Apps & Agents
Building useful LLM apps and agents comes down to assembling four distinct “stacks” in the right places: the model itself, the data/search/memory...
The King is Back. o3 & o4-mini are ELECTRIC! Can Google Compete?
OpenAI’s new o3 and o4-mini models are being positioned as a major leap in “agentic” AI—systems that can plan, use tools (web search, Python,...
AI AGENTS Updates From Google, OpenAI and Anthropic
AI agents are increasingly defined less by raw language ability and more by their ability to pursue goals through a loop of tool use—an approach...
Cohere's Command-R a Strong New Model for RAG
Cohere’s Command-R arrives as a purpose-built model for retrieval-augmented generation (RAG) and tool/function calling, not as a bid to replace top...
ChatGPT Agent is NEXT LEVEL Autonomy
ChatGPT Agent is being positioned as a “human-in-the-loop” style AI system that can complete multi-step tasks inside a virtual computer—searching the...
LLM Function Calling (Tool Use) with Llama 3 | Tool Choice, Argument Mapping, Groq Llama 3 Tool Use
Function calling with Llama 3 is no longer a niche capability: a Groq-tuned “Llama 3 tool use” model can reliably translate natural-language requests...
OpenAI DevDay 2024 | Community Spotlight | Sierra
Sierra’s TAU-bench reframes how AI agents are evaluated by combining realistic user conversations with tool-using task execution—and, crucially, by...
Build Smarter AI Apps: Memory, Tools, Retrieval & Structured Output with Python, Pydantic & Ollama
AI apps become meaningfully more useful when they’re given four upgrades beyond plain text prompting: memory, structured outputs, tool use, and...
Livecoding: ICE and the Factored Cognition Primer by Ought
High-reliability language-model apps increasingly come from breaking tasks into smaller, testable steps—then using execution traces to pinpoint...