Building AI Agent Systems — Series
A ground-up series on designing and shipping artificial intelligence (AI) agent systems. Covers the agent fundamentals (pillars, components, spectrum, workflow patterns) through to agentic workflow modelling, prompt chaining (sequential LLM calls with validation gates), routing (classify and dispatch), parallelisation (split / run / merge), the evaluator-optimiser refinement loop, and orchestrator-workers for dynamic, runtime task splitting.
The GenAI Landscape — structured
Foundations, architectures, tooling, and production patterns across modern Generative AI — navigable as a structured mindmap.
→Scheduling with CP-SAT — A Hands-On Tutorial
From a single machine to RCPSP — how to model and solve real scheduling problems in Python using Google's CP-SAT solver. Working code, animated Gantt charts, and intuition at every step.
How much can you get from your CPU — and when do you need a GPU?
Most Python code uses a fraction of available CPU power. An interactive explainer on parallelism, OpenBLAS tiling, and where the CPU ceiling actually is.
Stock Market Series — A Guide I Made for My Son
Two-level interactive guide — from what a stock is all the way to financial statements, technical analysis, and building a real portfolio.
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