// library · pillar 01
Prompting & context
Directing the model; what you feed it.
15 modules
· all six pillars →
2026·09·21 Ask for three, then pick: you can't describe what you haven't seen 2026·09·09 Ask again in a clean thread 2026·09·01 Flatten the sheet before you ask: the layout is what it gets wrong, not the numbers 2026·08·31 The rule you wrote and the rule that binds 2026·08·20 Make each rule a yes or no: why half your saved instructions stopped firing 2026·08·06 Ask for the edit, not the rewrite 2026·08·04 It noticed your question couldn't be answered. Then it answered. 2026·07·29 Personas don't transfer: the role prompt that helps on one model can hurt on the next 2026·07·27 Front-load the goal: why a late correction can't save a long AI task 2026·07·21 The density tax: why a short, fact-packed paste can be harder than a long one 2026·07·06 Say the what, delegate the how: specify the outcome, not the recipe 2026·06·18 Does 'Act as a senior lawyer' actually help? The truth about role prompting 2026·06·08 Brief the AI like a brilliant new hire: writing clear, direct instructions 2026·06·08 Context engineering: curate the few high-signal tokens, don't dump everything in 2026·06·08 Beyond the prompt recipe: iterative collaboration, not a better template