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In this tutorial, we dive into the cutting edge of Agentic AI by building a “Zettelkasten” memory system, a “living” architecture that organizes information much like the human brain. We move beyond standard retrieval methods to construct a dynamic knowledge graph where an agent autonomously decomposes inputs into atomic facts, links them semantically, and even […]
In this tutorial, we build an advanced, fully autonomous logistics simulation in which multiple smart delivery trucks operate within a dynamic city-wide road network. We design the system so that each truck behaves as an agent capable of bidding on delivery orders, planning optimal routes, managing battery levels, seeking charging stations, and maximizing profit through
In this tutorial, we build a fully functional Pre-Emptive Churn Agent that proactively identifies at-risk users and drafts personalized re-engagement emails before they cancel. Rather than waiting for churn to occur, we design an agentic loop in which we observe user inactivity, analyze behavioral patterns, strategize incentives, and generate human-ready email drafts using Gemini. We
This is a collection of simple PyTorch implementations of neural networks and related algorithms. These implementations are documented with explanations, and the website renders these as side-by-side formatted notes. We believe these would help you understand these algorithms better.
In this tutorial, we walk through the process of creating a fully autonomous fleet-analysis agent using SmolAgents and a local Qwen model. We generate telemetry data, load it through a custom tool, and let our agent reason, analyze, and visualize maintenance risks without any external API calls. At each step of implementation, we see how
In this tutorial, we devise how to orchestrate a fully functional, tool-using medical prior-authorization agent powered by Gemini. We walk through each component step by step, from securely configuring the model to building realistic external tools and finally constructing an intelligent agent loop that reasons, acts, and responds entirely through structured JSON. As we progress,
In this tutorial, we build a fully functional event-driven workflow using Kombu, treating messaging as a core architectural capability. We walk through step by step the setup of exchanges, routing keys, background workers, and concurrent producers, allowing us to observe a real distributed system. As we implement each component, we see how clean message flow,
In this tutorial, we shift from traditional prompt crafting to a more systematic, programmable approach by treating prompts as tunable parameters rather than static text. Instead of guessing which instruction or example works best, we build an optimization loop around Gemini 2.0 Flash that experiments, evaluates, and automatically selects the strongest prompt configuration. In this
In this tutorial, we implement how we build a small but powerful two-agent CrewAI system that collaborates using the Gemini Flash model. We set up our environment, authenticate securely, define specialized agents, and orchestrate tasks that flow from research to structured writing. As we run the crew, we observe how each component works together in
In this tutorial, we explore how we design and run a full agentic AI orchestration pipeline powered by semantic routing, symbolic guardrails, and self-correction loops using Gemini. We walk through how we structure agents, dispatch tasks, enforce constraints, and refine outputs using a clean, modular architecture. As we progress through each snippet, we see how
