“best-practices”
COPY vs ADD in a Dockerfile: When Each One Is Right
COPY and ADD look interchangeable but are not. The exact behavioral differences - URL fetching, tar extraction, --chown, --from, cache invalidation - and why the guidance is to prefer COPY.
Anatomy of a Dockerfile: Instructions from Top to Bottom
FROM, WORKDIR, COPY, RUN, CMD, ENTRYPOINT, USER, HEALTHCHECK — what each instruction does, the order they run in, and how they shape your image layers.
Feature-Based Folder Structure for Flutter Projects
Organize your Flutter codebase by feature, not by type. Learn how feature-based folder structures scale better and make navigation intuitive.
Flutter Clean Architecture: The Application Layer Explained
Understand the optional Application layer in Flutter Clean Architecture and how it coordinates repositories to orchestrate complex business workflows.
Clean Architecture in Flutter: The Four-Layer Pattern for Scalable Apps
A practical guide to implementing Clean Architecture with four layers in Flutter, featuring Riverpod integration and feature-based folder structure.
Clean Architecture with Four Layers for Flutter Apps
Implement Clean Architecture in Flutter with four distinct layers: Domain, Data, Presentation, and Application. Scale your Flutter apps without the spaghetti code.
A Year of Agents: What We Learned Building Production Agent Systems
Hard-won lessons from deploying AI agents in production environments at scale, covering reliability, cost management, evaluation, and the patterns that actually work.
Prompting for Reliable Agents: The Four-Part Specification
Master the art of prompting for agentic coding with the four-part specification structure: Goal, Context, Constraints, and Done-When.
Supervising Agents Like a Team: The Contractor Model
Apply engineering management discipline to agentic work with the Contractor Model: scope, equip, run, review, gate on CI, and audit afterward.
Documentation Best Practices for AI Codebases: Beyond the Docstring
Explore modern documentation strategies for AI-driven projects, including prompt versioning, llms.txt, model dependency tracking, and agentic architecture diagrams.
Agent Skill Design Best Practices
Learn how to design effective, maintainable, and scalable AI agent skills with these industry best practices and common anti-patterns to avoid.
Creating Effective File-Based Skills
A comprehensive guide on creating file-based skills for AI agents, covering the structure of SKILL.md and best practices for writing custom scripts.
Advanced Agent Skill Patterns for Pydantic AI
A deep dive into advanced design patterns for creating robust, scalable, and maintainable AI agent skills with Pydantic.
Mastering Agent Skills: Patterns and Best Practices for Robust AI
Go beyond basic security. Learn the design patterns and best practices—like idempotency, the Single Responsibility Principle, and versioning—that turn simple skills into robust, enterprise-grade components.
Unlocking Agent Skills: A Guide to Secure Implementation
Agent Skills are the building blocks of powerful AI, but they can also be a source of risk. Learn how to implement them securely using input schemas, user confirmation, and diligent auditing.
Securing AI Agents: Tackling the Trust Crisis in OpenClaw
Autonomous AI agents built with frameworks like OpenClaw are powerful, but they introduce a crisis of trust. Learn how to address the core security concerns of authorization, authenticity, and accountability.