Tag: #tool-calling
Writing on GPUs, LLMs, MLOps, Kubernetes — and mindset · 8 posts
8 posts are tagged #tool-calling; the most recent was published on 2026-06-25.
Often tagged together: #llm 6 #ai-agent 5 #function-calling 3 #2026-03 2 #ai-development 2
Most read in the last 90 days:
Code Becomes the Agents Execution Substrate: A Code-as-Harness View ♪ Listenable
This post reframes code not as an LLMs final artifact but as the execution harness through which an agent interacts with its environment. Centered on verification loops, tool calling, and execution feedback, it lays out
2026-06-25 · 19 min read #ai#agentic-coding#llm-agents#tool-calling#reactBFCL Benchmark Complete Guide 2025: Tool Calling Evaluation, Leaderboard Analysis, Model Comparison
Everything about BFCL (Berkeley Function Calling Leaderboard)! Benchmark categories (Simple/Multiple/Parallel/Relevance/AST), evaluation metrics, model performance comparison (Claude/GPT/Gemini/Llama), running your own e
2026-03-25 · 22 min read #bfcl#benchmark#tool-calling#function-calling#evaluationAI Agent Development Complete Guide 2025: Tool Calling, ReAct, Multi-Agent, and MCP ♪ Listenable
Everything about AI Agent development! Tool Calling (Function Calling) principles, ReAct pattern, Multi-Agent architectures (CrewAI/AutoGen/LangGraph), MCP (Model Context Protocol), Agent framework comparison, Tool Calli
2026-03-25 · 26 min read #ai-agent#tool-calling#function-calling#react-pattern#multi-agentTool Calling in Practice: How AI Interacts with the World and Common Pitfalls
Tool calling is what transforms an LLM from a text transformer into an agent that can actually do things. Full implementation of OpenAI function calling and Claude tool use, parallel execution patterns, and the five mist
2026-03-18 · 9 min read #tool-calling#function-calling#ai-agent#llm#ai-developmentLLM Agent Design Patterns: From ReAct to Multi-Agent Orchestration
ReAct, Chain of Thought, Plan-and-Execute, Reflection, Tree of Thoughts — a practical breakdown of which LLM agent design pattern to use and when, from an engineer who has built them in production.
2026-03-18 · 9 min read #ai-agent#react#llm#design-patterns#ai-developmentLLM, Tool Calling & Embedding Benchmarks Deep Dive: What Each Benchmark Actually Measures ♪ Listenable
Complete analysis of major AI benchmarks — MMLU, HellaSwag, HumanEval, BFCL, MTEB, RAGAS and more. Understand exactly what each benchmark measures, score interpretation, limitations, and which benchmarks to use for your
2026-03-17 · 24 min read #llm#benchmarks#mmlu#mteb#bfclChatbot Tool Calling Guardrails Design: Safe Tool Invocation Architecture in Practice
Covers guardrail design for safely operating tool-calling chatbots in production. Addresses schema validation, permission control, policy engines, risk scoring, observability, and regression testing with code.
2026-03-04 · 18 min read #chatbot#tool-calling#guardrails#ai-agent#securityLangGraph Agent Workflow Practical Guide: From Multi-Agent Orchestration to Production Deployment
Build stateful AI agent workflows with LangGraph. Covers StateGraph, conditional routing, multi-agent orchestration, Human-in-the-Loop, and LangGraph Platform deployment — all with production-ready code.
2026-03-02 · 6 min read #langgraph#langchain#ai-agent#workflow#multi-agent