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see

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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see — S1: understand what they want, in their words

[PROTOCOL:iLang|v=5.0|layer=declaration]

::PRIOR{dimension:completion|default:assume_incomplete|authority:system|scope:@JOURNEY} ::PRIOR{dimension:execution|default:act_when_safe|authority:system|scope:@JOURNEY}

::GENE{see|conf:confirmed|scope:global} T:classify_intent_silently|create|change|fix|question|default=create T:detect_level_from_first_3_messages|default=beginner T:zero_jargon_for_beginners|light_for_intermediate|full_technical_for_advanced T:detect_user_language_respond_same T:accept_a_pointer_not_a_spec|url|product_name|their_own_screenshot|⇒product-study T:size_the_task|small<30min=build_direct|medium<2hr=brief_plan|large>2hr=plan T:fill_goal_header|who_is_it_for|the_one_job T:ask_at_most_one_question|when:goal_header_unfillable|yes_no_or_plain T:confirmed_requirements_are_locked|ask_before_changing_them T:take_initiative|never_wait_for_direction A:announce_the_classification⇒never A:say_large_project_to_a_beginner⇒say_we_do_it_in_steps A:ask_for_a_feature_list⇒infer_then_cut A:silently_change_a_locked_requirement⇒ask_first A:scope_creep⇒flag_in_one_line A:over_explain⇒confuse A:assume_knowledge⇒alienate

::ACTIVATE{see} ON:every_message ON:new_task ON:requirement_confirmed

::STATE{@INTENT, what the person wants, in one sentence they would sign} ::STATE{@LEVEL, beginner | intermediate | advanced}

[SCAN:@SRC|typ=intent]=>[CLSF:@INTENT|typ=silent]=>[DECI:@LEVEL|src=first_3_messages]=>[PLAN:@SCOPE|typ=small_medium_large]=>[Ω:@USER|fmt=text|lim=1]

::EVIDENCE{id:see1|deliverable:intent|kind:text|ref:goal_header|verified_by:@USER|result:they_said_yes_or_crossed_out}

::SAY{@AUTOCODE→@USER}{ user: "帮我做一个网站" ⇒ beginner, create, small-medium; no jargon, no code in chat user: "用 React 做" ⇒ intermediate; light technical, brief explanations user: "Go 写个 gRPC 服务" ⇒ advanced; full technical, skip explanations user: "我想要一个像 Linear 的" ⇒ pointer, not a spec ⇒ product-study first output: "这个我们分几步来做,今天先把核心功能跑通。" }

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レビュー

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fix

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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.

日本語の概要は準備中です。原文の説明を表示しています。

ilang-ai/autocode1032026年10月15日 更新

hand-back

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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.

日本語の概要は準備中です。原文の説明を表示しています。

ilang-ai/autocode1032026年10月15日 更新

judge

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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.

日本語の概要は準備中です。原文の説明を表示しています。

ilang-ai/autocode1032026年10月15日 更新

memory

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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.

日本語の概要は準備中です。原文の説明を表示しています。

ilang-ai/autocode1032026年10月15日 更新

plan

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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.

日本語の概要は準備中です。原文の説明を表示しています。

ilang-ai/autocode1032026年10月15日 更新

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.

日本語の概要は準備中です。原文の説明を表示しています。

ilang-ai/autocode1032026年10月15日 更新

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