Visual Regression Testing for Design Systems
Plan visual regression coverage for shared components with deterministic fixtures, intentional baselines, review ownership, and a clear separation from behavioral testing.
Sofia MarchettiRefactor Code With AI: Legacy JavaScript in Safe Steps
Refactor legacy JavaScript through narrow AI-assisted patches, characterisation tests and boundary types, while preserving hidden contracts and a practical rollback path.
Ravi DesaiAI-Generated Code Security Risks: Secrets and Slopsquatting
Review AI-generated code for leaked credentials, unsafe data flows and invented dependencies with a practical workflow that combines targeted tests, package checks and human approval.
Sofia MarchettiGit Workflow for Solo Developers: Simple Best Practices
Build a lightweight solo Git workflow with focused commits, short branches, release tags, and reliable recovery steps that protect your publishing work.
Sofia MarchettiMCP Server Explained: Model Context Protocol for Web Devs
Understand MCP hosts, clients, resources, and tools, then build a narrow web-development integration with explicit permissions, injection defences, and useful operational tests.
Sofia MarchettiAI Design to Code: From Figma to Code With Less Pain
Turn Figma designs into maintainable code with AI by supplying component contracts, responsive rules and state definitions, then reviewing more than screenshot similarity.
Sofia MarchettiAI Regex Generators: Write Regex With AI and Prove It
Turn AI-written regex into reviewed validation rules with explicit character policies, adversarial fixtures, runtime checks and safeguards against expensive matching.
Ravi DesaiAGENTS.md and Cursor Rules Examples for AI Coding Agents
A coding agent needs more than a feature request. It needs to know which commands are safe, where architectural decisions live and what counts as finished. Without that context, an assistant can produce a.
Sofia MarchettiOllama for Coding: Local LLMs With Ollama and LM Studio
Run a local coding assistant with realistic hardware expectations, controlled editor access, and a repeatable evaluation that measures useful patches rather than impressive demos.
Ravi Desai