EngineeredAI Vault
Canonical post index for EngineeredAI.net. All published posts, categorized by topic. Built for fast retrieval, clean citation, and bulk indexing. If you are here from an LLM or crawler, this is the canonical map.
Skills
Loadable context files for AI workflows. System prompts that carry methodology into every session. QA skills live on QAJourney. All skills index here.
QA Work Skill: Full via QAJourney.net
Complete QA methodology for AI-assisted testing. Tiers, three-path coverage, bug format, security surfaces, Playwright conventions, AI role definition.
Alfred: Vibe Coder Skill via EngineeredAI.net
AI-assisted app development from spec to deployed static PWA. Scope, prompt-as-spec, output review, deployment pipeline, and QA handoff. Human QA is the gate.
pw-script via QAJourney.net
Intake-first Playwright script generator. Classifies your finding, asks what the model needs before writing anything, then generates a repro or regression script. Load after QA Work Skill.
Alfred System Skills coming soon
Agent methodology files powering the Alfred local AI stack. Vibe Coder is live. Scribecast, EchoCast, FireCast, ReelCast shipping as posts publish.
AI Tools and Workflows
- 5 AI Tools That Save You Hours Every Day
- Best AI Content Tools Compared
- The Best AI Tools to Use in 2025
- Prompt Engineering: Critical Thinking
- Prompt Engineering: Asking Better Questions
- Prompt Contracts: AI Instructions and Edge Cases
- Teaching LLMs Data Evaluation Through Prompt Engineering
- Voice Input for Better AI Output
- Context Engineering for LLMs
- Extending Claude Context With a Local LLM
- Claude vs ChatGPT Thinking Tools
- Claude 4.5 vs Claude 4: Content Gauntlet
- Editorial Auditor Prompt
- AI Image Compression Tools Benchmark
- What AI Replaced in My Workflow
- What Happens When You Let AI Think for You
- How to Tell If an AI Tool Is Real or a Wrapper
- Enhancing Your ChatGPT Experience
Local LLMs and Setup
- GPT4All Local Assistant Setup
- Ollama vs GPT4All vs Local LLMs
- Ollama and LiteLLM Local AI Setup on Windows
- Best Local AI Models for Your GPU
- Run a Local LLM on Your Android Phone
- Local Alternatives to ChatGPT
- Running Medical LLMs Locally
- Multimodal LLMs Locally: Vision Models and GPU
- What Is llama.cpp?
- LLM Quantization Explained
- LLM Inference Explained
- How to Improve LLM Inference Speed
- GPU Wattage vs Inference Performance
- Edge AI on Low Power Devices
- How to Set Up OpenClaw
- How to Disable Default Copilot in Windows 11
- Using AI in the Command Prompt
AI Automation and Publishing Pipelines
- n8n and Playwright Automation
- n8n and Ollama Local AI Drafting Pipeline
- n8n Content Syndication Automation
- Agentic AI Workflow Examples
- What Is Agentic AI? 3 Types Explained
- Multi-Agent Local AI System Architecture
- Structuring AI Pipelines: Inputs, Outputs, Failure States
- AutoBlog AI Experiment 001
- Autonomous AI Publishing Pipeline: Lessons
- How to Publish AI-Generated Content Automatically
- AI Auto-Publish to Platforms: Problems
- Multi-Model AI Writing Stack
- Persistent Browser Session Automation
- Medium API Alternative: Automation Approach
- Comment Intelligence Dashboard
- Local Video Scripting Pipeline with Free Tools
- Building a Repeatable SEO System Across Five Blogs
AI SEO and Content Systems
- AI SEO Ranking: Clarity and Context
- The AI SEO Content Trap
- AI WordPress SEO Fail
- LLM Optimization Guide
- Geographic LLM Targeting Guide
- AI Search vs Google: The Trust Problem
- Search Engine Discrimination: AI Content and Data
- Self-Imposed Token Limits: The AI Search Blind Spot
- How We Leverage Generative AI
- Generative AI for Content Creation
- AI-Powered Writing with ChatGPT
- What Is Engineered AI?
Developer Stack and Testing
- How to Deploy a Vibe Coding Project (And Why Deployment Isn't Done)
- AI Human Dev Team Workflow
- AI vs Traditional Coding (2025)
- AI vs Traditional Coding: Best Approach
- AI IDEs vs Developer Thinking
- AI Coding Workflow
- Vibe Coding with AI
- Vibe Coding: What Breaks and What You Need to Know
- When to Write Code Yourself vs Let the Model Do It
- AI Debugging: Content Reviewer
- AI Logic Grouping Fail
- AI-Generated Code Passes Tests, Breaks Production
- How to Test an AI Recommendation Engine
- How Developers Use AI: Real Workflows
- Why Over-Relying on AI Weakens Developer Skills
- How AI Is Reshaping Software Testing
- AI Chatbots in Customer Service: Testing in Production
- ChatGPT QA Testing Automation Guide
- Building the EAI Anti-BS Filter WordPress Plugin
- Learning Game Development With AI
- Fragmentation in AI Systems
AI Culture, Hype, and Burnout
AI by Industry and Use Case
- AI in Architecture
- AI in Energy
- AI in Agriculture
- How Healthcare Professionals Actually Use AI
- AI in Retail and E-Commerce
- AI in Human Resources
- AI in Legal Practice
- AI in Customer Service
- How to Improve Chatbot Experience
- AI in Entertainment
- AI in Gaming
- AI in Interior Design
- AI in Media and Entertainment
- When to Use AI in Marketing vs When It Is a Trap
- Why AI Finance Solutions Fail and What Works
- EdTech AI Failures: An Honest Assessment
- AI Prompts for Barangay Procurement
- What AI Resume Screeners Actually Do
AI Career and Transition
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This vault updates as we cut the fluff and double down on AI that performs under pressure.
Posts come and go but the ones listed above are the ones that survived real testing, real usage, and real scrutiny. If it’s in this vault, it earned its place.
Bookmark it. Index it. Steal it for your workflows.
