Lost Midas

@lostmidas

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Vibe coding thrives on clear planning Scattershot approaches waste time & kill productivity Building products with AI models demands robust context Each step feeds into the next, creating a system of clarity Good context creation follows a rhythm: - PRD defines the big "what" & "why" - User stories turn vision into actionable goals - User flows outline how users move through the experience - Design specs bring it all to life without ambiguity Context isn’t busywork It’s leverage Here’s a guide to doing it right

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Small passionate teams hit harder & move faster than any bloated bureaucracy ever could

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Building from nothing demands obsession Process polishes, obsession creates

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Survival is the foundation of every great startup Growth only matters if you’re still in the game Funding, press, features: none of it counts if you can’t keep the lights on Resilience beats brilliance Longevity unlocks everything else

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Discipline is action without motivation

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While prompt engineering gets the headlines Context engineering is the alpha move Most feed the model words Few feed it real perspective Value happens when you shape context not just prompts

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Context switching shreds productivity In startups it’s nonstop Everything shifts at breakneck speed Adapt or get steamrolled Staying sharp when the ground moves Good teams react Great teams thrive in the entropy

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When prompt engineering, clear outputs start with clear asks The challenge is knowing what you want Discovery is messy Expect to fumble Refining the ask is the craft Precision only comes after the scramble

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Projects drift Timelines stretch Even with the best tools Every build uncovers new complexity Patience beats hustle Real progress respects the process Shipping takes time, even when you plan for speed

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AI makes starting trivial Finishing is a grind Patience Taste Relentless iteration If you can’t define done, you’ll start everything & ship nothing

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Engineers don’t care if you can code Respect is earned by clarity, decisiveness, & not being insufferable Chasing technical street cred is insecurity Be likable Make real decisions That’s what actually moves teams

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AI innovation is relentless Exciting, exhausting, & terrifying It’s shaping the future, whether we’re ready or not

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So is it cool to bull post about ETH again?

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Prompt templates are a crutch at best Without real context & taste, they spit out generic slop Useful outputs need guidance, iteration, & patience Prompting is bespoke work Not an IKEA instruction manual

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Code is cheap Most can summon an MVP in a few days The real grind: - Knowing what to build - Turning bland features into movements - Designing beyond function - Wrestling with data walls, permissions, API hell - Winning real trust when AI can fake anything Fast prototyping is a solved game Now it’s taste, narrative, & nuance that separates signal from noise

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Idea to dev ticket, AI-native workflow: - Write the feature prompt - Auto-generate wireframe - Connect model to codebase context - Send wireframe & prompt to LLM for dev ticket - Build - Test - Ship Zero ceremony No middlemen Just flow

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Order is safe Entropy is profit The best lessons don’t come from playbooks They hide inside chaos If you aren’t stumbling through mess, you aren’t building anything worth remembering

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High value capital formation

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Nothing is as easy as YouTube tutorials claim Gurus make workflows look like wizardry: - Skip the pain - Hide the bugs - Never mention hours lost to broken dependencies Real building: - 90% debugging - 10% pretending it was simple Anyone selling easy is selling a fantasy

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Getting good with AI isn’t about "how to prompt" blog posts It’s relentless tinkering Trying Failing Trying again Shortcuts feel good But mastery comes from breaking things Collecting weird outputs Repeating until it clicks Avoid failure, avoid becoming AI-native

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