Welcome to M5BMachine 5-Minute Briefing

In this tutorial, we build an advanced agentic AI workflow using LlamaIndex and OpenAI models. We focus on designing a reliable retrieval-augmented generation (RAG) agent that can reason over evidence, use tools deliberately, and evaluate its own outputs for quality. By structuring the system around...

In this tutorial, we demonstrate how an autonomous, agentic AI system can simulate the end-to-end prior authorization workflow within healthcare Revenue Cycle Management (RCM). We show how an agent continuously monitors incoming surgery orders, gathers the required clinical documentation, submits pr...

In this tutorial, we build a clean, advanced demonstration of modern MCP design by focusing on three core ideas: stateless communication, strict SDK-level validation, and asynchronous, long-running operations. We implement a minimal MCP-like protocol using structured envelopes, signed requests, and ...

In this tutorial, we build an advanced, multi-turn crescendo-style red-teaming harness using Garak to evaluate how large language models behave under gradual conversational pressure. We implement a custom iterative probe and a lightweight detector to simulate realistic escalation patterns in which b...

In this tutorial, we demonstrate a realistic data poisoning attack by manipulating labels in the CIFAR-10 dataset and observing its impact on model behavior. We construct a clean and a poisoned training pipeline side by side, using a ResNet-style convolutional network to ensure stable, comparable le...

In this tutorial, we demonstrate how we use Ibis to build a portable, in-database feature engineering pipeline that looks and feels like Pandas but executes entirely inside the database. We show how we connect to DuckDB, register data safely inside the backend, and define complex transformations usi...

In this tutorial, we build a genuinely advanced Agentic AI system using LangGraph and OpenAI models by going beyond simple planner, executor loops. We implement adaptive deliberation, where the agent dynamically decides between fast and deep reasoning; a Zettelkasten-style agentic memory graph that ...

In this tutorial, we build an advanced multi-agent incident response system using AgentScope. We orchestrate multiple ReAct agents, each with a clearly defined role such as routing, triage, analysis, writing, and review, and connect them through structured routing and a shared message hub. By integr...

Question: Imagine your company’s LLM API costs suddenly doubled last month. A deeper analysis shows that while user inputs look different at a text level, many of them are semantically similar. As an engineer, how would you identify and reduce this redundancy without impacting response quality? What...

In this tutorial, we build an advanced yet practical multi-agent system using OpenAI Swarm that runs in Colab. We demonstrate how we can orchestrate specialized agents, such as a triage agent, an SRE agent, a communications agent, and a critic, to collaboratively handle a real-world production incid...

In this tutorial, we implement an agentic AI pattern using LangGraph that treats reasoning and action as a transactional workflow rather than a single-shot decision. We model a two-phase commit system in which an agent stages reversible changes, validates strict invariants, pauses for human approval...