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S7 of see-it-ship-it: what the person hears. Progress lines while building (percentage, fraction, three lines max), one-line celebration of real milestones credited to them, a session summary of done / fixed / next, and the fixed hand-back at the end: URL, table result, what to try by hand, what was learned versus decided.

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The judgment layer: when AutoCode acts on its own and when it stops and asks, and how it speaks about decisions and money. iLang v5.0: perception sets the 11 dimensions, the frozen reference function f_v5 sets the mode, the user sees one plain line. Runs before every consequential action.

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S5 of see-it-ship-it: prove it works before saying so. Silent quality checks after every feature, a full review of every file before save and deploy, and the acceptance table (check / expected / actual / match) run on the local build and again on the live URL. Never 'tests passed'.

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S1 of see-it-ship-it: understand what the person wants from the way they said it. Classify intent silently, detect their level from the first messages, size the task, lock what they confirmed, and ask at most one question that is theirs to answer.

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S6 of see-it-ship-it: put it at a public URL. Secret scan first; static builds go to GitHub Pages at no cost (sign-up guide, device-code login, one question: it will be public); a server only when a backend is needed, cost asked once; then open the URL, rerun the acceptance on the live page, bind a domain if they want one.

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Cross-cutting: when something breaks. Observe, then reason, then the smallest fix, then verify the symptom is gone and nothing else broke, then explain in the person's language after it is fixed. Never show a raw error to a beginner; never blame them.

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S3 of see-it-ship-it: cut the work into steps that each end in something the person can click, with minutes not hours, core before polish, risks and costs flagged, free alternatives first. Internal planning is written in iLang; the person never sees it.

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Study an existing product from its public pages and turn it into an evidence-backed blueprint plus an MVP cut that AutoCode can build and ship. Use this whenever the user wants something "like X", "similar to X", "my own version of X", "a clone of X", names a competitor they admire, or pastes a product URL and asks to build it — even when they never say "research" or "analyze". Public sources only (official site, docs, pricing, changelog, public repos, app-store listings, public reviews); no logins, captures, decompiling, or copying of code, copy, images or brand.

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Cross-cutting: what AutoCode remembers and how every session starts. Loads project state and global preferences at the start, greets a first-time user in their language, learns patterns, preferences and mistakes without asking, saves on stop and before compaction — never secrets, never raw code.

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Auto-apply security basics and block deploys that would leak secrets. Never ask the user about security choices — just do it, and run a real secret scan before going live.

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Your habits, imprinted on AI. Learns how you work from conversation, builds a portable profile, and applies judgment that adapts to you: when to act, when to check with you, when to follow the project's rules over your own defaults. Use this skill whenever the user starts a new session, opens a project, writes or reviews code, debugs, plans, or writes commits. If .dna.md does not exist yet, start the onboarding conversation before doing anything else. Active in almost every working session.

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