Why My AI Prompt Library Died (And What I Keep Instead)
I built a careful personal prompt library. It still died. What travels now is role, residue, and a short ticket.
Field notes on multi-model workflows, long-term memory, and the odd ways models behave when the task is not a toy prompt.
I built a careful personal prompt library. It still died. What travels now is role, residue, and a short ticket.
Gemini has quietly marked your text since 2024, and it has quirks Claude doesn’t. Five methods, one that actually improved the writing.
Manus data deletion, one-time restore, websites still down, and how to choose a cloud or local agent so your next eight months don't live only in a vendor sandbox.
Five methods people try. Only one improved the writing instead of just hiding the fingerprint.
OpenClaw, Hermes, DeepSeek Harness. Different names, same "local = private" illusion.
The problem is not finding another model. It is keeping research, decisions, drafts, and context connected as the work changes.
What I actually packed when the knowledge base went away. Not a ranking of bot stores.
Export is the handoff now, not where thinking starts. Personal workspace first, company tools second.
Same messy dilemma, four models, anonymized peer review. Self-preference bias and four structural blind spots.
People hide AI use from their boss, then show their setup to strangers online. Why that split exists, and what it is turning into.
If it is a draft, I can vibe. If it carries my name, I need to audit it.
Patterns and appointment prep for family health — not diagnoses. What stays offline.
On AI, work, and the things models get wrong. A few emails a month — only when there is something worth saying.
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