Tutorials – Postgres
Can AI Really Feel Your Pain?
AI can understand your emotions and respond appropriately, but it’s not actually feeling anything – just pattern-matching from millions of examples. This matters more than you think.
Why Your Expensive AI Tools Sit Unused
Smart teams buy expensive AI tools that end up collecting dust. The problem isn’t the technology – it’s that nobody wants to fight with it. Here’s how to build AI workflows people actually use.
Why Emotional Intelligence Beats Coding For AI Teams
Building AI agent teams isn’t about coding – it’s about managing dynamics. The same emotional intelligence that makes you good with people makes you exceptional at orchestrating agents through “vibe coding.”
5 Skills To Master AI Coding Teammates
After 30 years of coding, I learned AI works best when you treat it like a junior developer. Here are 5 skills that changed how I work with AI teammates.
Choosing The Right LLM Changes Everything
After decades of coding and building AI solutions, I learned that picking the right LLM isn’t about finding “the best one” – it’s about matching each tool to the right job and knowing how to use them properly.
How To Slow Down Time Using Your Mind
You can actually change how you experience time – not by doing more, but by slowing down inside through presence and cognitive empathy to make life feel less chaotic.
How Empathy Slows Down Time And Stops Racing
Ever feel like time is slipping away? Discover how cognitive empathy doesn’t just help you understand others – it actually slows down time and makes you present.
Why Do AI Coding Assistants Mislead Developers?
You know that feeling when someone gives you directions with total confidence – and you end up at a dead end? That’s AI coding assistants in a nutshell.
When To Tweak Versus Restart AI Prompts
After years of AI prompting, I’ve figured out the key question: when do you keep tweaking versus starting over? Here’s my framework for knowing which approach works.
After 30 Years Coding I Cracked AI
After 30 years of coding, I learned the secret to getting useful work from AI: break problems into small chunks instead of dumping everything into one prompt.
Why AI Projects Fail Despite Massive Investment
30 years watching AI projects fail because consultants build systems instead of workflows that work for real people. I teach teams to think differently about automation – solving actual problems, not imaginary ones.
Why Does Your AI Give Terrible Answers?
Your AI gives mediocre answers because you’re asking it to solve complex problems all at once. Break tasks into smaller chunks instead – like building a web scraper, then analyzing data, then generating a report separately. Each piece gets the model’s full attention and drastically improves quality.
Why Leaders Miss AI’s 3x Efficiency Gains
Most leaders think AI is just chatbots, but they’re missing 3x efficiency gains. After 30 years building AI workflows, I’ve learned the best systems understand people, not just data.
Break AI Tasks Into Chunks For Better Results
Breaking complex AI tasks into smaller chunks gets way better results than asking it to solve everything at once. Here’s my 30-year coding process for decomposition prompting.
From Rigid Code To Smart AI Agents
After 30 years of coding, I’ve seen workflows evolve from rigid rule-based systems to adaptive AI agents that make real-time decisions and optimize themselves.
AI Isn’t Hype After 30 Years Coding
30+ years of coding taught me every tech wave was overhyped. AI is different – it’s not automating tasks, it’s making entire workflows obsolete and reshaping what’s possible.
Are You Optimizing Workflows AI Already Replaced?
We’re optimizing workflows that AI has already made obsolete. After 30 years of coding, I’ve learned AI doesn’t speed up old processes – it replaces them entirely.
My Journey From Perfectionist To Self Compassionate Person
Published...
When To Iterate Versus Start Fresh Coding
After 30+ years in code and 8 years in AI, here’s the difference between getting stuck and getting results: knowing when to iterate vs when to start fresh.
Why Forced Positivity Destroys Team Trust
I learned that forcing positivity actually pushes people away and makes problems worse. When we dismiss struggles with “stay positive,” trust breaks down and real issues get buried.
Why AI Projects Fail Despite Perfect Technology
I spent 30 years watching companies waste money on AI tools that employees hate. The failures aren’t technical – they ignore how humans actually work and think.
The Real AI Skill After 30 Years
After 30 years of coding, I finally figured out the real AI skill that matters: breaking problems into pieces AI can handle, not chasing the latest tools or models.
Why Do Most AI Projects Fail Miserably?
After 30 years of coding, I learned the secret to AI success: treat agents like a specialized team, not magic wands. Break problems down, write clear prompts, give them tools.
Why AI Teams Beat Solo Agents Every Time
30 years of coding taught me: one AI agent is useful, but a team of specialists working together changes everything. Most people miss this completely.
AI Teammates Beat Search Engine Developers
Developers treating AI like a teammate instead of a search engine are pulling ahead. The gap isn’t about better models—it’s about learning to delegate effectively through skills like prompt engineering, modularization, and workflow integration.
LLM Choice Matters Less Than Prompt Engineering
After 30+ years coding and 8 years in AI, I’ve learned everyone focuses on which LLM is best, but misses what really matters: knowing how to talk to it properly.
Why Perfect AI Code Still Feels Wrong
AI code looks perfect but feels wrong? After 30 years coding, I’ve learned the most valuable skill isn’t getting AI to write code – it’s knowing when to ignore it.
AI Prompts: When To Iterate Versus Restart
30+ years of coding taught me this about AI prompts: it’s not about finding the “perfect” prompt, it’s knowing when to iterate vs start over completely.
Why Most People Fail At AI Prompting
Most people prompt AI once and hope for the best. The real skill is knowing when to refine versus when to scrap everything and start over.
Stop Perfecting Prompts Start Breaking Them Apart
After 30 years coding and 8 years in AI, I learned the key skill isn’t perfect prompts – it’s knowing when to keep tweaking vs starting fresh. Break prompts into pieces.