How to Explain AI Assistants to Parents and Family
The AZET team's guide to explaining AI assistants to parents: metaphors that work, safety rules worth teaching, and the scams to warn older relatives about.
Guides and maker's notes from the AZET team — what azet.io is, how the AI assistant and browser automation work, and the AZET product family.
The AZET team's guide to explaining AI assistants to parents: metaphors that work, safety rules worth teaching, and the scams to warn older relatives about.
The AZET team on using AI assistants for research: strengths, failure modes like stale info and unverifiable claims, and the habits that keep answers honest.
Why the AZET team reads the changelogs of the AI tools we use, how to read them as a user, and how our own dated notes model works on this blog.
How a tiny team assembles an AI toolstack: assistant, automation, review habits — a general framework from the AZET team, with our stack as one example.
The AZET team on keeping a simple automation diary: what you automated, what happened, and why a one-line log makes personal automation observable.
The AZET team on the honest cases where an AI assistant is the wrong tool: irreversible actions, sensitive data, and decisions that need human judgment.
The AZET team's guide to being a good early-access user: what feedback actually helps makers, what to expect from a waitlist, and patience with rough edges.
Straight answers from the AZET team: what azet.io is, whether it is free, who it is for, what the waitlist is, and who builds it, as of October 2026.
Practical notes on using AI assistants across Korean and English: what travels well, and what to watch — fixed commands, politeness register, sources.
How the AZET team builds trust into an AI product: dated claims, a completion matrix, execution receipts, and runtime honesty about what done means.
How a small team reasons about subscription seats versus API keys for AI assistants, and where AZET's bring-your-own-CLI stance sits in that choice.
One runtime, two surfaces: how the AZET desktop app and CLI divide the work, what they share, and what neither surface claims as verified.
A maker-written first walkthrough of the AZET CLI: install, login, your first run command, session list, providers, and what needs the desktop app.
An honest day with an AI assistant: what it genuinely helps with, what stays manual, and why some tasks are better kept — no productivity theater, from AZET.
The AZET team's honest, category-level map of Korean AI tools for global readers: global assistants, local platforms, open models, and culture-rooted apps.
AI assistant privacy in plain terms: what leaves your machine, local versus hosted models, and the questions to ask before you paste — by the AZET team.
What a browser profile stores, why separate profiles matter for automation and privacy, and how profiles differ from incognito — from the AZET team.
How to start personal automation without coding: pick one recurring task, keep it observable, build the kill switch first — written by the AZET team.
The AZET team's safe-start checklist for your first AI assistant: habits for sessions, data boundaries, approval gates, and spending — dated 2026-10-03.
Closer looks at two AZET products: Tonemoa personal color analysis told as a webtoon, and Sweep ad blocking for every device — status honest and dated.