AI Tutorials
A Backend Engineer's Guide to RAG Architecture
Discover how to design, implement, and optimize a production-grade Retrieval-Augmented Generation (RAG) pipeline using your existing backend engineering skills.
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AI Tutorials
Explore our entire collection of insights, tutorials, and industry news.
- AI Tutorials
Why Valid JSON from LLMs Can Still Trigger Parser Syntax Errors
Learn how to debug and resolve invisible characters, byte order marks (BOM), and markdown code blocks that break Python's JSON parser when processing LLM outputs.Read more → - AI Tutorials
Why My LLM Agent Engine Resisted Prompt Injection Attacks
An in-depth analysis of how structural isolation, deterministic gates, and a Dual LLM architecture protected the PlannerCritic agent engine against direct prompt injection and adversarial attacks across three releases.Read more → - AI Tutorials
Getting Started with Superpowers: Installation, Workflow, and Practical Guide
Learn how to install and configure Superpowers, an opinionated spec-driven development framework for Claude Code, Cursor, and other agentic CLI tools, to enforce strict TDD and structured workflows.Read more → - AI Tutorials
Guide to Writing an AGENTS.md File for a Python Project
Learn how to write a lean, highly effective AGENTS.md file to guide AI coding assistants in Python projects. This guide includes a complete template, design patterns, and an interactive quiz.Read more → - AI Tutorials
How Invisible AI Text Watermarking Works and What It Means for Developers
An in-depth technical analysis of Claude's new SynthID-based text watermarking, the rise of sovereign AI hardware, and practical strategies for developers to avoid cognitive debt while using LLM APIs.Read more → - AI Tutorials
Fine-Tuning Vision-Language Models with Reinforcement Learning and Verifiable Rewards
Deep dive into the practical challenges, integration bugs, and reinforcement learning pitfalls when fine-tuning 9B to 35B vision-language models using GRPO.Read more → - AI Tutorials
Optimizing RAG for Tables: Implementing Row-Level Chunking
Learn how to improve Retrieval-Augmented Generation (RAG) performance on tabular data by splitting tables into row-level chunks with injected headers, reducing noise and token usage.Read more → - AI Tutorials
Building a Self-Correcting AI Agent with Reflection Loops in Python
Learn how to build a self-correcting AI agent in Python using reflection loops to catch and fix LLM errors programmatically, complete with schema validation and budget guardrails.Read more → - AI Tutorials
Benchmarking Agent Skill Scanners Against Malware and Prompt Injection
An in-depth evaluation of leading LLM agent-skill scanners against 8,000 malware samples, featuring a hybrid static-semantic detection pipeline and real-time quarantine implementation.Read more → - AI Tutorials
Implementing Safe Autonomy in LLM Agents with Action Gating
Learn how to design safe autonomous AI agents by gating high-risk actions at the executor level rather than the reasoning loop, featuring Claude Agent SDK and MCP implementations.Read more → - AI Tutorials
Evaluating LLM Performance with Real Production Traffic Replays
Discover why synthetic benchmarks fail for LLM migrations and learn how to build a production traffic replay harness in Node.js to safely test models like DeepSeek-V3 and Claude 3.5 Sonnet.Read more →