Practical guides on AI-assisted software engineering, AI agents, and upskilling. Articles link technical terms to the glossary— hover for a preview, or open in a new tab from the article.
A step-by-step walkthrough for building your first AI agent — from defining its purpose and choosing a model to wiring tools, memory, testing, and deployment.
Your agent demos beautifully. Whether it survives real work — and returns an ROI instead of burning tokens — comes down to five things the demo hid.
Why traditional monitoring is blind to AI failures — and how to build the observability stack that actually catches hallucinations, drift, and cost blowouts.
AI can spot an O(n²) loop in milliseconds, but that loop might not be your bottleneck. Learn to measure first, optimize second, and let AI amplify — not replace — engineering judgment.
Deep dive into planning algorithms that power AI agents — from classical search and MCTS to LLM-based reasoning, ReAct loops, and hierarchical task decomposition.
How AI agents maintain, update, and reason about state — patterns from simple key-value stores to complex belief systems, memory architectures, and state machines.
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