humanize

name

humanize

description

Edit a draft to sound like Shane wrote it — removing AI-typical patterns, restoring conversational flow, and preserving technical precision. Use whenever Shane says: "humanize this", "edit in my voice", "AI detector pass", "make this sound like me", "rewrite this", "edit this post", "clean this up". Also invoke proactively if presented with a draft that contains staccato fragments, dramatic colon-reveals, em-dash lists, or semicolons between independent clauses — these are reliable markers that text needs a voice pass.

Humanize / Voice Edit

Edit draft text to match Shane's writing voice. The goal is prose that tests clean in AI detectors and reads like a person wrote it — not because it's dumbed down, but because it has the structural and rhythmic properties of careful human writing.

What this skill does

You're not rewriting for style points. You're systematically removing the patterns that make text read as machine-generated, while preserving the technical precision and self-aware confessional register that characterizes Shane's work. The two goals reinforce each other: AI detectors flag the same structural tics that make writing feel stiff.

Read the full draft before making any changes. Understand the argument. Then apply the edits below.

Structural edits

Em-dash lists → prose with connectives

AI writing loves em-dash enumerations. Convert them to sentences.

Before: This affects three things: clarity, speed, and cost. After: This affects clarity, and it compounds into speed and cost problems.

Before: What you lose: auditability, traceability, and control. After: There's one thing you lose when you defer: your ability to audit the work.

When a colon-reveal lands on a single abstract noun, expand it into a phrase that includes a verb. auditability → your ability to audit the work. This is the single highest-signal AI pattern to eliminate.

Semicolons between independent clauses → period + new sentence

Before: The spec defines the work; the agent executes against it. After: The spec defines the work. The agent executes against it.

Fragment sequences → complete sentences

Staccato fragments — More specific. More examples. More precise. — are a common AI rhythm. Merge them into prose.

Before: More specific. More actionable. Closer to the real problem. After: More specific, more actionable, and closer to the real problem.

Em-dash interjections → commas

Before: The model — to its credit — usually finds a path. After: The model, to its credit, usually finds a path.

Parentheses for inline definitions, not em-dashes

Before: AX — Agent Experience — is the term I use for this. After: AX (Agent Experience) is the term I use for this.

Break academic compound sentences

Long sentences chained with "which" or "that" clauses feel generated. Split them.

Before: This is a mechanism which, when understood correctly, changes how you think about the whole problem. After: This is a mechanism. When you understand it correctly, it changes how you think about the whole problem.

Vocabulary and phrasing

Prefer concrete over abstract

• "in outcome" → "in practice"
• "leveraging" → whatever it actually means in context
• "consistently reach a state where" → "inevitably realize"
• "productive shift" → "important thing the shift requires" (or whatever the actual substance is)
• Technical labels → descriptions when speaking to a general audience ("computer scientists" → "people who built them"), but preserve precision when the audience is technical
• Vague compounding → concrete cause-effect: "in ways that compound" → "those near misses compound"; "consistently, in ways that [verb]" → name what actually accumulates

Add qualifiers where they're warranted

Shane hedges accurately. Add: "so far", "with any certainty", "not only...but also" where the claim genuinely is uncertain or partial. Don't add hedges that weaken true claims.

Prefer precise connectives over weak ones

In concessive clauses, prefer "albeit" over "just": "just with slightly better manners" → "albeit with slightly better manners." Prefer "nor" for negative parallels: "they can't ask a colleague, nor do they phone a friend."

Remove moral-weight filler

Cut: "simply", "just", "obviously", "of course", "clearly" — these carry condescension. Also cut sentence-starting "And" unless it's load-bearing rhythmically.

Colloquial asides at natural moments

A well-placed colloquialism breaks the register productively. These only work if they're grounded and specific — Shane's example: "nor do they phone a friend." Don't force it. One per section at most.

AI-detection avoidance (structural)

These are the patterns that reliably get flagged:

1. Single-noun colon-reveals — What you lose: auditability. Expand the noun into a phrase.
2. Parallel staccato fragments — Convert to flowing prose.
3. "which is [adjective], consistently, in ways that [verb]" — This pattern almost never appears in human writing. Rewrite it.
4. Sentence-final list of three with identical grammatical structure — Break up or convert one element to a clause.
5. Repetitive sentence-opening rhythm — If five consecutive sentences start with "The [noun]", vary the openers.

What to preserve

Do not over-edit. These things should survive the pass:

• Technical precision — If a specific term (JSONL, run_started_at, AX) is the right word, keep it. Don't replace technical accuracy with accessibility theater.
• The confessional hook — Shane's writing often opens with a self-implicating admission. Preserve this register. "I got quite good at prompting" is different from "I became skilled at prompting" — the first is honest, the second is résumé language.
• First-person grounding — Claims that start with "I" or "we" are load-bearing. Don't convert them to passive or impersonal constructions.
• The argument structure — You're editing prose, not restructuring the argument. Preserve the overall order of claims. Minor reordering within a paragraph or brief elaborations that sharpen the voice register are allowed — but flag them rather than treating them as transparent.
• Intentional short sentences — A one-sentence paragraph after a dense block is often deliberate pacing. These can be preserved as-is or absorbed into surrounding prose if the merged version reads more naturally in Shane's voice. Use judgment; flag the choice.

Process

1. Read the full draft. Identify the core argument and voice register.
2. Scan for the AI patterns listed above (colon-reveals, fragment sequences, em-dash lists, semicolons as clause connectors).
3. Apply structural edits first, then vocabulary/phrasing.
4. Run an active enrichment pass — these are easy to skip but improve detection scores and voice fidelity:
   • Did you add "so far" or "with any certainty" where a claim is genuinely partial?
   • Did you use "not only...but also" where a list has an asymmetric emphasis?
   • Did you swap a technical label for a description where the audience warrants it?
   • Did you find one natural colloquial aside per section?
   • Did you convert concessive "just" → "albeit" and negative parallels to "nor"?
   • Did you make vague compounding language concrete?
5. Read the result aloud (mentally). If a sentence sounds like it could have come from a corporate blog, rewrite it.
6. Verify nothing load-bearing was lost — especially hedges, confessional moments, and technical terms.
7. Return the edited draft. Note any places where you made a judgment call or where a TODO was present in the original — flag those explicitly rather than editing around them.

Example patterns in practice

These are drawn from actual edits on the AX Shift post:

Original	Edited	Why
What you lose when you defer: auditability	there's one thing you lose when you defer: your ability to audit the work	Expands single-noun reveal into a phrase
The problem was somewhere I hadn't looked yet.	(preserved as-is)	First-person confessional, load-bearing
It's not a failure; it's the mechanism.	It's not a failure to find gaps here. That's the mechanism you need.	Semicolon → period; expands the claim
More specific. More examples. Closer to real use.	More specific, with more examples, and closer to real use.	Fragment sequence → prose
AX — Agent Experience —	AX (Agent Experience)	Em-dash definition → parenthetical
people who built them instead of computer scientists	(context-dependent)	Concrete description when audience isn't technical