// training paths · six tracks, in order
Training paths
Each pillar as an ordered track. Start at the top of any track; j/k steps you through once you're inside a module.
0/43 logged · no uptime yet — the first module starts the clock
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Directing the model; what you feed it
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 2026·06·18 Does 'Act as a senior lawyer' actually help? The truth about role prompting 2026·07·06 Say the what, delegate the how: specify the outcome, not the recipe 2026·07·21 The density tax: why a short, fact-packed paste can be harder than a long one
What persists across turns and sessions; retrieval
2026·06·08 Your context window is working memory, not a hard drive 2026·06·08 RAG without the jargon: how AI can answer from your documents instead of guessing 2026·06·16 Own the memory, not just the model: the harness layer that quietly traps you 2026·06·25 It only sees your slice: how permissions shape what your work assistant tells you 2026·07·08 Connected isn't constant: when your assistant actually reaches into your inbox
Extending the model: integrations, connectors, setup
2026·06·08 Connectors vs. file upload: when to plug into your live data and when to just drag a file in 2026·06·11 Projects, Custom GPTs, and Gems: which reusable workspace to build 2026·06·23 Citation theatre: the more a research agent cites, the more links it fabricates 2026·06·30 Be your own connector: feeding a sandboxed AI what it can't reach 2026·07·14 Show, don't tell: paste the screenshot instead of describing it 2026·07·22 The Silent Engine Swap: What to Do When Your AI Tool Changes Underneath You
Multi-step work, orchestration, refining to a result
2026·06·08 The generate-critique-refine loop: stop accepting first drafts 2026·06·08 Plan first, execute second: the 80/20 rule for letting AI tackle big tasks 2026·06·17 Briefing a Deep Research Agent: How to Get a 20-Source Report Worth Reading 2026·06·29 Convene a Panel: Using Multiple AI Personas to Stress-Test a Decision 2026·07·01 The handoff note: let the outgoing session write it for you 2026·07·13 The pre-mortem: assume the plan already failed, then ask why 2026·07·16 Read the why, not just the fix: using AI's formula repair as a free lesson
Knowing when not to; failure modes, over-reliance
2026·06·08 Why it makes things up: hallucination is a feature of the scoring, not a glitch you can prompt away 2026·06·15 Citation roulette: the verification habit that keeps you out of the AI-hallucination court database 2026·06·22 The account is not the artifact: judging AI work you didn't watch get made 2026·06·24 The summary that ate the caveat: what AI quietly drops when it condenses your documents 2026·07·02 It agrees because you pushed back: spotting sycophancy before it changes your mind 2026·07·09 The give-up reflex: what ten minutes of AI help does to your persistence 2026·07·15 Verify the request, not the voice: why spotting the deepfake is the wrong defence 2026·07·23 Inherited capture: on someone else's call, the note-taker runs on their defaults
Reading model developments; signal from hype
2026·06·08 The jagged frontier: why AI aces one task and bombs the next one that looks identical 2026·06·12 Leading through the dip: the productivity J-curve and the real work of the AI transition weekly 2026·06·12 Colleague or contractor: the two ways to hand work to an AI 2026·06·19 The rented mind: when intelligence is cheap, memory is the lock-in weekly 2026·06·26 The imagination gap: when execution is cheap, judgement is the divide weekly 2026·07·03 The supervision paradox: why more capable AI means more babysitting, not less weekly 2026·07·07 The tool is not the model: what your AI can do keeps changing under you 2026·07·10 Vibe citing: when generation is free, being able to vouch for it is the job weekly 2026·07·17 The ambition technology: why maximum AI value starts with a bigger ask, not a smaller workload weekly 2026·07·20 Why the Leaderboard Lies: Reading AI Benchmarks Without Getting Fooled 2026·07·24 Measurement debt: when belief in AI outruns the proof weekly
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