Your Success Story Might Be Someone Else’s Script
Successful businessman has everything, feels like total failure. Turns out legacy isn’t what happens after you die – it’s what you do today. That’ll mess with your head.
Successful businessman has everything, feels like total failure. Turns out legacy isn’t what happens after you die – it’s what you do today. That’ll mess with your head.
Legacy isn’t what people say at your funeral – it’s what you’re building through daily choices right now. This book tears apart everything you think matters.
AI agent teams work better when you treat them like emotionally intelligent humans – understanding each agent’s strengths, managing their cognitive load, and letting them collaborate naturally.
Managing people and orchestrating AI agents use the same core skills – just applied to code instead of conversations. Recognition becomes observation, pattern analysis becomes prediction, and conflict resolution becomes debugging.
You’re using AI coding assistants wrong – they don’t need more freedom, they need better rails. 30 years of coding plus 8 years of AI work taught me why constraints beat creativity.
AI coding isn’t about autonomy – it’s about constraints. After 30+ years coding, I’ve learned the real breakthrough is “agents on rails” with precise specs.
After 30+ years coding, I’ve watched teams waste hours on AI that generates creative but wrong solutions. The AI isn’t broken – your instructions are missing.
Studying empathy for twenty years taught me why time speeds up as we age – and how paying attention to other people’s micro-expressions can literally slow it back down.
Spent 30+ years coding, 8 with AI. The secret isn’t the tech – it’s breaking problems into chunks AI can actually handle. Most people fail because they dump entire projects on it.
After 30 years of coding, I watched workflows evolve from rigid sequential tasks to adaptive AI systems that think, learn, and self-organize – flipping the human role entirely.
I tested every coding assistant for 30 years. Most are just fancy autocomplete. Roo Code is the first that actually gets it – runs locally, open-source, and keeps you in flow.
After 30 years of coding, I found the first assistant that actually collaborates instead of just guessing. Roo Code runs specialized agents that handle different dev tasks.
After 30 years of coding, I found the first AI assistant that actually feels like a teammate. Roo Code thinks in specs first, uses different models for different tasks, runs locally for privacy, and works autonomously like a junior dev who never gets tired.
After 30 years coding, I found an AI that actually understands my entire project, handles spec-to-deployment, runs locally, and acts like a real partner instead of fancy autocomplete.
30 years of coding taught me AI doesn’t speed up old processes—it replaces them. Companies see 30% lower costs and 90% fewer errors with agent workflows.
After 30 years building software and testing every AI coding assistant, I found one that actually works: Roo Code. It thinks in modes, runs locally, understands full codebases.
30 years of coding taught me AI isn’t just upgrading work – it’s making entire job categories obsolete. Your value now is giving instructions to machines, not following them.
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.
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.”
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.
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.
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.
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.
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.
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 of coding, I learned the secret to getting useful work from AI: break problems into small chunks instead of dumping everything into one prompt.
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.
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.
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.
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.
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