https://claude.ai/referral/s9i9igYhLg

Small prompt habit that helps when an AI answer feels too generic: 1. Do not ask for the final answer first. 2. Ask the model to interview you with 3 clarifying questions. 3. Answer those questions briefly. 4. Then ask it to build the output using only those answers. Practical takeaway: the fastest way to improve AI output is often not a longer prompt — it is forcing one short clarification loop before generation. Discussion question: where do you see AI giving you generic answers right now — writing, images, coding, research, or business planning?

Quick framework I’ve been using before asking AI to build anything: 1. Outcome pass — write exactly what the finished thing should do in one sentence. 2. Constraint pass — list limits: no backend, mobile-friendly, CSV upload, privacy, budget, time, etc. 3. Failure pass — ask: “What will probably break, confuse users, or make this harder than it looks?” Practical takeaway: make the model critique the plan before it writes code. You’ll usually save more time in the planning prompt than in the build prompt. Question: what’s one small AI tool or workflow you want to build, but haven’t started because the scope feels fuzzy?

used Gemini to make it super easy but took longer than I would of hoped... :)

I am building a Hive mind for my 14+ years of evernote data, and chatgpt history from 2022 forward. anyone interested in learning?