Fully Copy-Pasteable: Steps to Build a 1 Million Yen/Month High-Ticket Affiliate Business with Codex Full Automation

First, I want to say this upfront because I don't want to be misunderstood.

There isn't a single line in this article about "making 1 million yen with one button."

What is written here is the procedure for using Codex (OpenAI's autonomous execution AI) to eliminate over 90% of the work in high-ticket affiliate marketing and then "Calculate Backwards → Systematize → Auto-pilot" the numbers needed for 1 million yen a month. I have listed about 40 copy-pasteable prompts, all assuming the reader is a beginner. Even if you have never touched Codex, if you follow the steps from start to finish, you will be able to set up a complete system.

Why write so specifically? The reason is simple: there are too many posts talking about "AI side hustles" and "automation" that stop at abstract theories. They just say "Codex is amazing" or "You can automate with ChatGPT," but no one writes what to move, in what order, and with what prompts. That's why people can't start, or can't continue even if they do.

I'll be honest. Making 1 million yen a month with high-ticket affiliates is not a magic trick that anyone can do in a few months. However, the structure is incredibly simple.

"High-ticket items (20k–100k yen) × 10–50 conversions per month × Auto-piloting that system." That's it.

Conversely, if you build these three things diligently, those who can replicate it will. Codex is the partner that takes over almost all of that assembly.

This article covers 10 chapters: Niche Selection → Persona Design → Article Mass Production → SNS Funnels → Sales Copy AB Testing → Prompt Engineering → Expanding Capabilities with MCP → Auto-piloting with Codex Automations → Avoiding Pitfalls → Discarding Old Habits. I'm leaving all ~40 prompts and operational know-how here.

By the time you finish reading, you will have both the "map of work to aim for 1 million yen" and the "implementation steps that work with copy-paste." Copy it, rewrite it with your own project and genre names, and run it on the spot. It works.

Let's get started.

Chapter 1: Niche Selection — 80% of the 1 Million Goal is Decided Here

The first chapter is about "what to sell."

Honestly, if you get this wrong, no matter how hard you work in the later chapters, you won't reach 1 million yen. If you automate a 1,000 yen product affiliate with Codex, you need 1,000 sales for 1 million yen. With a 30,000 yen high-ticket item, you reach the same revenue with 33 sales. The work is almost the same. The only difference is "what you chose first."

1. Tier-S Niche Sniper — Filtering Genres by 3 Axes

Survival in high-ticket affiliates is decided by "Unit Price × Approval Rate × Search Demand." If you vaguely choose "side hustle" or "beauty," you'll hit a red ocean, low prices, or a 3% approval rate landmine. Let the AI score these three axes and keep only the top ones.

▼ Prompt for Copy-Paste

You are a market analyst for high-ticket affiliate marketing.

Please score the following genre candidates on a 10-point scale based on three axes:

1. Average Unit Price (10,000 yen or more = high score)
2. Approval Rate (50% or more = high score)
3. Balance between monthly search volume and competition density

Add a one-line rationale for each axis and sort them in descending order of total score.

Finally, leave only genres with a total of 24 points or more as "entry candidates."

Genre candidates: [ ]

1. ASP Cross-Crawl — Comparing the Same Product Across Multiple ASPs

Even for the same product, the price and approval rate can vary by more than double depending on the ASP (Affiliate Service Provider). Checking this manually every time is a waste of time, so let Codex list them.

▼ Prompt for Copy-Paste

For the following product name, cross-search major ASPs (A8, Moshimo, afb, Access Trade, ValueCommerce, Cats) and output in a table format.

Columns: "ASP Name / Unit Price / Approval Conditions / Estimated Approval Rate / Availability of Special Price Negotiation."

If the source cannot be confirmed, write "Unknown" and do not fill with guesses.

Product Name: [ ]

1. LTV Reverse Calculator — Calculating Backwards from 1 Million Yen

Starting with dreams leads to frustration. Starting with numbers leads to persistence. Deconstruct the structure of 1 million yen and determine first how many sales at what price you should aim for.

▼ Prompt for Copy-Paste

Please provide 5 realistic patterns to achieve a monthly sales target of 1 million yen.

For each pattern, create a table with:

• Estimated unit price
• Required number of conversions
• Required traffic (at 1%/3%/5% conversion rates)
• Estimated number of articles (at 500/1500/3000 average monthly PV per article)

Finally, rank them in order of ease for a beginner to build in the shortest time.

1. Demand-Saturation Index — Quantifying the Balance of Demand and Saturation

Even if search demand is high, you can't win if the competition is too strong. Conversely, if the competition is weak but demand is small, you won't reach 1 million. Score both to visualize where you can win.

▼ Prompt for Copy-Paste

For the following keyword groups, score "Demand Score (0-10)" and "Saturation Score (0-10)," and calculate the "Demand ÷ Saturation" index.

Sort by the highest index and write 3 lines of rationale for each of the top 5 on "why a beginner can aim for top ranking in 3 months."

Keyword groups: [ ]

The common theme of this chapter is "stop choosing by feel and start choosing by numbers." More than half the difference between those who reach 1 million and those who don't is decided by this initial selection.

Chapter 2: Persona and Offer Design — A Blueprint to Target One Person

"Selling to everyone" doesn't sell. "Stabbing one person deeply" results in selling to many. This chapter contains four steps to make Codex materialize that "one person" and build an offer that resonates with them.

1. N=1 Persona Generator — Generating One Realistic Person

Thoroughly create one person, including name, age, occupation, income, layer of worry, catchphrases, search times, and the moment they hesitate to pay. A vague "30s male office worker" won't cut it.

▼ Prompt for Copy-Paste

Generate one typical customer who would buy in the following genre, with a resolution that feels real.

• Name/Age/Gender/Location
• Occupation/Income/Family Structure/Hobbies
• 5 worries from the last 3 months
• 3 keywords searched right before purchase
• 3 reasons for hesitating to pay
• 3 triggers that push them to pay

Generalities are prohibited; write with specific names.

Genre: [ ]

1. Pain-Stack Mapping — Layering Worries into 5 Levels

People don't move for surface-level worries. The real motivation is three layers down. Deconstruct into Surface → Middle → Deep → Fear → Ideal to decide the appeal axis.

▼ Prompt for Copy-Paste

Structure this persona's worries into the following 5 layers:

1. Surface (Worries they usually speak aloud)
2. Middle (Dissatisfaction not yet verbalized)
3. Deep (Root cause)
4. Fear (Worst-case scenario if left alone)
5. Ideal (What they truly want to become)

Write 3 points for each layer, and finally propose which layer should be targeted in the copy with rationale.

1. Offer-Market Fit Test — Scoring the Alignment Between Offer and Market

Even if you find a project, selling it as-is won't work. Let Codex score how well the persona's deep worries align with the project's benefits. If it doesn't fit, redesign the offer.

▼ Prompt for Copy-Paste

Read the following persona and project information and score the alignment between the two on 10 items.

Score each item out of 10 and provide a total.

• Under 70 points → "Pivot recommended"
• 70-85 points → "Redesign offer"
• 85+ points → "Execute immediately"

Write the reasons for the judgment in bullet points.

Persona: [ ]

Project: [ ]

1. Counter-Offer Generator — Creating the Opposite of Existing LPs to Differentiate

You'll lose if you use the same appeal axis as rivals. Let the AI read the claims of existing LPs and generate 3 ideas for "what would be an appeal from the exact opposite angle." You'll find a winning edge through contrarianism.

▼ Prompt for Copy-Paste

Read the following rival LP and extract 3 main appeal axes.

Next, for all three, generate an "appeal that can be justified from the exact opposite angle."

For each idea, also list:

• Which reader segment it will resonate with
• Implementation precautions

Rival LP: [URL or text]

Once the persona and offer are decided, writing articles or SNS posts becomes just a means to an end. This is the foundation that makes Chapter 3 and beyond much easier.

Chapter 3: Article Mass Production — Automatically Raising One Draft a Day

This is about "quantity."

Even in high-ticket affiliates, you ultimately need a certain amount of traffic. If you double 50k PV to 100k PV, revenue grows at a similar rate. Since it's impossible for humans to keep producing this volume, we hand it to Codex.

1. SERP Reverse Engineering — Deconstructing and Reconstructing Top Articles

Let the AI analyze why top articles are at the top and extract their structure. Then, have it generate a framework to beat them by filling in "missing sections" and "unresolved user questions."

▼ Prompt for Copy-Paste

Analyze the title and heading structure of the top 10 search results for the following keyword.

1. Common heading structures
2. Top 5 frequently mentioned points
3. 5 questions/loopholes not written anywhere

Based on this information, output a "unique structure proposal to beat the top results" with H2x6 and H3x3 each.

Keyword: [ ]

1. Skeleton-Then-Fill — Building the Framework in Parallel and Adding Content

If you let the AI write from the top, the latter half always loses steam. Have it create the heading skeleton first in parallel, then flesh out each heading as an independent task. For Codex, "running short tasks in parallel" results in more stable quality.

▼ Prompt for Copy-Paste

For the following theme, list the heading skeleton (H2x5, with H3x3 for each H2) in parallel first.

Next, treat each H2 as an independent task and flesh out each section with 800 characters.

Finally, integrate the whole and present a completed version with logical overlaps and contradictions removed.

Theme: [ ]

1. E-E-A-T Injection — Inserting Experience, Expertise, Authoritativeness, and Trustworthiness Later

Articles written by AI might have a high average score but lack "experience." Articles evaluated by Google always contain details of real experiences. Insert these after the fact.

▼ Prompt for Copy-Paste

Read the following draft article and evaluate it from the E-E-A-T perspective.

1. Experience
2. Expertise
3. Authoritativeness
4. Trustworthiness

List 3 missing points for each perspective.

Then, generate specific sentences (numbers, proper nouns, real-life episodes) to insert into the missing parts and indicate the positions with "Insert here."

Draft: [ ]

1. Internal Link Web Designer — Designing Internal Link Networks Structurally

As the number of articles increases, internal link design stagnates. Give Codex the sitemap and URL list and have it design internal links in a topic cluster structure.

▼ Prompt for Copy-Paste

Read the following URL list and title list for each article, and design an internal link map in a topic cluster structure.

Classify into 3 layers: "Pillar Articles," "Cluster Articles," and "Satellite Articles," and output a table of up to 5 internal links to be placed from each article.

Also include anchor text proposals.

URL List: [ ]

1. Comparative Review Stack — Mass Producing Comparative Reviews Structurally

High-ticket affiliates and comparative review articles are a perfect match. Mass produce articles comparing 3-5 products in the same genre with a fixed structure.

▼ Prompt for Copy-Paste

Generate 3 "comparative review articles with the same structure" for the following 3 products.

Change the main product for each article, and have the other 2 appear as "comparison targets."

The article structure is fixed:

• Intro (150 chars)
• General review of the main product
• Comparison table on 3 axes (Price, Effect, Support)
• Who the main product is for / not for
• Conclusion

Product List: [ ]

By this point, you'll be close to a state where "one draft is raised every day." If you proceed to Chapter 8's Codex Automations, you can run this completely on autopilot.

Chapter 4: SNS Funnels — Automatically Connecting the X → note → LINE Baton

To aim for 1 million yen with high-ticket affiliates, search traffic alone is volatile.

Generate traffic on X, warm them up on note, and close on LINE.

Automate this 3-stage relay baton with AI.

1. Hook Library Builder — Extracting Appeal Patterns from Past Viral Posts

Extract only the posts that grew from your own or similar accounts in the same genre, and have the AI extract common "hook types." This becomes your dedicated appeal template collection.

▼ Prompt for Copy-Paste

Analyze the following list of X posts (those with an engagement rate of 3% or higher) and extract 10 common "hook syntaxes."

For each syntax, output a table with:

• Situations where it's used
• Expected reaction
• General template (fill-in-the-blank format)

Post list: [ ]

1. Thread-to-Article Bridge — Automatically Generating CTAs from X Threads to note

How naturally you send readers who are interested on X to note determines 80% of the inflow rate. Automatically generate 3 patterns of transition text to place at the end of a thread.

▼ Prompt for Copy-Paste

Read the following X thread content and generate 3 patterns of natural CTAs to a note article.

1. "Curious about the rest" type
2. "Verbalizing the reader's worry" type
3. "Explicit benefit" type

Each within 140 characters, no hard sell, assuming the last sentence is "Place the link to the note article."

Thread: [ ]

1. Lead Magnet Generator — Mass Producing LINE Registration Benefits

The lifeline of high-ticket affiliates is the LINE list. Mass produce "benefits" that serve as motivation for registration for each persona. Registration rates can change several-fold just by changing the benefit.

▼ Prompt for Copy-Paste

Generate 10 lead magnet (benefit) ideas to encourage LINE registration for the following persona.

For each idea, output:

• Benefit name (within 20 chars)
• Summary of content
• Estimated registration rate
• Time required for production

Finally, rank them by production cost-effectiveness.

Persona: [ ]

1. Follow-up DM Script — Automatically Generating Follow-up LINEs After Registration

Half of the drop-offs are decided in the first 3 days after registration. Generate a 3-5 message follow-up scenario tailored to the persona and project.

▼ Prompt for Copy-Paste

Generate 5 follow-up LINE messages after registration for the following persona.

Message 1 = Immediate thanks + Expectation setting

Message 2 = Empathy story

Message 3 = Comparison with other companies/self-study

Message 4 = Social proof

Message 5 = Offer presentation

Write each message with a structure that can branch based on sticker reactions at the beginning.

Persona: [ ]

Project: [ ]

Chapter 5: Sales Copy Automatic AB Testing — Don't Bet on One, Measure with Five

Polishing one LP is important, but the final form doesn't appear from the start. Codex is good at "generating multiple variants for the same appeal," so run five and keep the winner.

1. Variant Spawner — Generating 5 Patterns for the Same LP

Just by changing one line in the first view, CVR can change 2x or 3x. Writing these manually is a waste of time, so generate 5 patterns in one go.

▼ Prompt for Copy-Paste

Read the following LP text and generate 5 variants changing only the "Catchphrase + Sub-copy + CTA button text" of the first view.

Clearly change the appeal axis for each variant.

Example:

• Fear appeal
• Gain appeal
• Authority appeal
• Empathy appeal
• Urgency appeal

For each idea, also list the reader segment it will resonate with.

LP text: [ ]

1. Objection Handler — Automatically Multiplying Objection Handling Parts

The places where people drop off an LP are fixed. Write handling for the three major objections—"It's expensive," "I'm worried if I can do it," "I don't need to buy now"—in the persona's words.

▼ Prompt for Copy-Paste

For the following project, list 10 expected objections before purchase and generate objection handling text for each.

The style should not be pushy; first accept the reader's anxiety, then resolve it with data or examples.

Each objection handling should be within 200 characters.

Project: [ ]

1. Urgency Calibrator — Adjusting Urgency and Scarcity Numerically

Too much hype is counterproductive; too little doesn't move people. Specify the "intensity" of urgency and scarcity from 1-10 and have it write at that intensity.

▼ Prompt for Copy-Paste

For the following offer, write urgency and scarcity presentations by intensity level (Low/Medium/High).

Generate 3 patterns of text around the CTA for each level, and also list expected reactions (increase/decrease in conversion rate, presence of aversion).

Offer: [ ]

1. Story Arc Injector — Building Story-type LPs Structurally

The higher the price, the less it sells on "logic alone." You need a story that moves the reader's emotions. Generate a story arc to insert at the beginning of the LP using a template structure.

▼ Prompt for Copy-Paste

Generate a story arc that fits the following persona and project.

Structure is 6 stages:

Daily Life → Incident → Conflict → Encounter → Turning Point → Success

200 characters per stage, one character, clearly indicate emotional ups and downs.

Finally, propose where in the LP this story should be inserted.

Persona: [ ]

Project: [ ]

Chapter 6: Polishing the Prompt Content — 5 Ways to Stabilize Output Quality Every Time

By now, "what to make" is decided. This chapter is about 5 types of "stabilizing the quality of that work every time." All of these are effective just by how you write the prompt.

1. Output-First Specification — Fixing the Final Template First

If you say "write a blog post," the output will vary. If you build the final template first and have it fill in the blanks, the variation disappears.

▼ Prompt for Copy-Paste

Please fill in the following template perfectly.

Title: [Within 40 chars, including numbers]

Intro: [3 reader worries, 1 sentence each]

Body: [H2x3 + 300 chars each]

Conclusion: [1 action proposal]

CTA: [Within 15 chars]

Theme: [ ]

1. Negative Constraints — NG List to Erase the AI Smell

"In natural writing" is too vague to be followed. If you provide a specific NG list in bullet points, the AI smell almost disappears.

▼ Prompt for Copy-Paste

Please create the following. Strictly observe prohibitions.

1. Prohibit "About..." or "It is important to..."
2. Prohibit consecutive use of 3-character kanji compounds
3. Prohibit opening greetings
4. Prohibit escaping with just bulleted lists
5. Prohibit using the same sentence ending 3 times in a row

If violated, rewrite the entire text.

Target: [ ]

1. XML Structured Tagging — Separating Information with Tags

If you pass goals, background, constraints, examples, and output format in one lump, the AI loses track of priorities. Just separating them with tags improves comprehension accuracy.

▼ Prompt for Copy-Paste

I will instruct with the following structure. Please answer according to the content of each tag.

<goal>Goal to be achieved</goal>

<context>Background information</context>

<constraints>Prohibitions</constraints>

<examples>Reference examples</examples>

<output_format>Output format frame</output_format>

1. Self-Refine — Running Generation, Criticism, and Revision in One Go

If you review a text you wrote alone, you won't see the flaws. Have the AI play 3 roles and complete generation → harsh scoring → revision in one response.

▼ Prompt for Copy-Paste

For the following topic, do all 3 steps in one response.

1. Write the first draft
2. As a harsh editor, score on 5 perspectives: Persuasiveness, Uniqueness, Logic, Readability, and Omissions
3. Write a revised version based on the scores

Topic: [ ]

1. Calibrated Confidence Prompting — Making Confidence Levels Explicit

In high-ticket affiliates, a single factual error loses trust. Having it include a "confidence level 0-100%" for each claim makes judging reliability overwhelmingly easier.

▼ Prompt for Copy-Paste

When answering the following question, always include a "confidence level 0-100%" for each claim.

• Under 50% → "Speculation"
• 70% or more → "Fact"

Label them and provide a one-line rationale for each confidence level.

Question: [ ]

Chapter 7: Giving Codex "Hands and Feet" with MCP — 4 to Include

MCP (Model Context Protocol) is a standard for connecting AI to external services.

With this, Codex changes from a "chat tool" to an "agent that moves the real world." I've selected 4 essential ones for high-ticket affiliates.

1. Firecrawl MCP — Converting Rival LPs and Sites Entirely to Markdown

Letting Codex read rival LPs directly makes analysis faster. Since it can process pages rendered with JavaScript, you can feed it modern dynamic LPs as they are.

▼ Example Usage

Convert the following URL to Markdown with Firecrawl, apply Chapter 2 Technique 8 (Counter-Offer Generator), and output 3 LP structure proposals that appeal from the exact opposite angle.

URL: [ ]

1. Supadata MCP — Extracting Appeal Elements from Videos in One Go

An MCP that can pass transcripts from YouTube/TikTok/Instagram to Codex. Deconstruct the structure of viral videos and repurpose them for your own LPs or threads.

▼ Example Usage

Extract the transcript from the following YouTube/TikTok video URL and extract 5 "hook syntaxes" and "drop-off avoidance points" that are generating viewer retention.

URL: [ ]

1. Memory MCP — Giving Codex Permanent Memory

Codex usually loses memory when a session ends. With Memory MCP, persona, project info, and past verification results are persisted. The work of "re-pasting premises every time" becomes zero.

▼ Example Usage

Register the following information in permanent memory.

1. Genre being handled [ ]
2. Main persona [ ]
3. Active projects and unit prices [ ]
4. NG appeal axes [ ]

In future sessions, always refer to this first before working.

1. Notion/Sheets MCP — Centralizing Project Management and Revenue Data

Have Codex directly interact with Notion or spreadsheets for project prices, monthly occurrences, approval rates, and confirmed amounts. This integrates "data update → analysis → next move."

▼ Example Usage

From the Notion DB "Project Management," retrieve the number of occurrences and confirmed cases for the current month and aggregate by ASP/Project.

Extract projects where the approval rate has dropped in the last 3 months and formulate 3 causal hypotheses for each.

With these four, you have "Reading (Firecrawl/Supadata)," "Remembering (Memory)," and "Moving (Notion/Sheets)." This is where Codex truly starts moving with hands and feet.

Chapter 8: Full Auto-pilot with Codex Automations — 5 That Work While You Sleep

Codex Automations is a scheduled execution automation feature.

Once set up, Codex continues to run your side hustle even while you are sleeping or in a meeting at work. Available with ChatGPT Plus ($20/month) or higher.

Combining all five introduced here will start a fully automated cycle of "Daily Drafts / Daily SNS Posts / Weekly Ranking Monitoring / Monthly Revenue Reports / Automatic Detection of Underperforming Articles."

1. Daily Article Drafter — One Article Draft Raised Every Morning

Every morning at 6:00 AM, generate one draft from the previous day's keyword list and save it to a specified folder. When you wake up, the draft is already on your desk.

▼ Setup Prompt

Create a Standalone Automation with the following schedule.

[Schedule] Every day at 6:00 AM

[Task]

1. Retrieve one keyword for today from ./keyword-queue/ in the project
2. Analyze the heading structure of the top 10 SERP results for that keyword (Apply Chapter 3 Technique 9)
3. Generate a 4,000-character draft based on the structure
4. Save as ./drafts/YYYY-MM-DD.md
5. Notify Slack of completion

1. Daily SNS Cannon — Automatic Generation and Scheduling of X Posts

Every morning, generate 3 X posts for today referring to the syntax of past viral posts and schedule them. The concept of running out of ideas disappears.

▼ Setup Prompt

Create an Automation with the following schedule.

[Schedule] Every day at 7:00 AM

[Task]

1. Refer to 10 viral posts (engagement rate 3%+) in ./content-bank/
2. Choose 3 syntax patterns from them and generate 3 X posts for today's theme
3. Insert a natural CTA to a note article in each post
4. Send API to a scheduling tool like Buffer
5. Notify Slack of the completion list

1. Weekly SERP Watcher — Weekly Automatic Monitoring of Ranking Fluctuations

Every Monday, retrieve the rankings of active keywords and list only articles that have dropped by 5 or more places compared to the previous week. No need to manually open Search Console.

▼ Setup Prompt

Create an Automation with the following schedule.

[Schedule] Every Monday at 9:00 AM

[Task]

1. Retrieve rankings for all active keywords (./keywords.csv)
2. Extract keywords that dropped by 5 or more places from the previous week
3. For each keyword, analyze the difference with top articles (heading structure/word count/E-E-A-T elements)
4. Report as rewrite candidates in order of priority
5. Notify Slack

1. Monthly P&L Reporter — Automatic Generation of Monthly Revenue Reports

At the beginning of the month, aggregate the previous month's occurrence amount / confirmed amount / approval rate / contribution by project and generate a summary report. You'll be in a state where you can have a monthly review meeting with Codex.

▼ Setup Prompt

Create an Automation with the following schedule.

[Schedule] 1st of every month at 8:00 AM

[Task]

1. Retrieve all data for the previous month from the Notion DB "Project Management"
2. Aggregate occurrence amount / confirmed amount / approval rate / contribution by project
3. Generate graphs for MoM/YoY comparison
4. Extract 3 highlights, 3 issues, and 3 priority actions for next month
5. Save as ./reports/YYYY-MM.md
6. Notify Slack

1. Failure Detection Loop — Automatically Detecting and Proposing Fixes for Poorly Performing Articles

As the number of articles increases, detecting underperforming ones is delayed. Link with Google Analytics to weekly detect articles whose PV has dropped by 30% or more in the last 30 days and automatically generate causal hypotheses and revision plans.

▼ Setup Prompt

Create an Automation with the following schedule.

[Schedule] Every Friday at 10:00 AM

[Task]

1. Retrieve PV/CV data for the last 30 days from GA
2. Extract articles whose PV has dropped by 30% or more compared to the last 90 days
3. Summarize the following for each article:
4. Causal hypothesis (SEO factors/Trend factors/Competitor factors)
5. 3 revision directions
6. Estimated man-hours for revision
7. Notify Slack in order of priority

When these five are running, you are in "Side Hustle Auto-pilot Mode."

All you do is decide the strategy, polish the drafts at the very end, and decide the next move by looking at the monthly reports. Just these three.

Chapter 9: Pitfalls Unique to High-Ticket Affiliates — 4 to Crush Before Automating

Automation is powerful, but if you automate with a weak design, you just mass-produce mistakes at high speed. Crush four pitfalls that frequently occur in high-ticket affiliates beforehand.

1. Compliance Guard — Automating Pharmaceutical and Advertising Law Checks

High-ticket genres (beauty/health/finance/career) have strict expression regulations. Violations lead not only to project suspension but also administrative guidance. Always have Codex check before publishing an article.

▼ Prompt for Copy-Paste

Read the following article and extract all risk expressions from the perspectives of the Pharmaceutical Affairs Law, the Premiums and Representations Act, and the Specified Commercial Transactions Act.

For each risk expression, output a table with:

• Applicable law
• Violation level (High/Medium/Low)
• Alternative expression proposal

Do not hesitate to point out gray zones.

Article: [ ]

1. Approval-Rate Optimizer — Article Structure That Doesn't Lower Approval Rates

For high-ticket projects, the ASP determines approval or rejection. If the approval rate drops, even if monthly sales look good, the confirmed amount might be half. Have Codex follow an article structure that is hard to lower the approval rate.

▼ Prompt for Copy-Paste

Read the following article and evaluate the risk of lowering the approval rate from 5 perspectives.

1. Presence of accidental click induction
2. Presence of excessive exaggeration
3. Exposure design to non-targets
4. Inappropriate implementation of AB tests
5. Unclear drop-off paths before application

Score each item out of 10, and if the total is under 30, judge as "Fix before publishing."

Article: [ ]

1. ASP Diversification — Designing to Break Dependency on a Single Project

If 80% or more of sales depend on one project, the moment that project ends, sales go to zero. Have it build a portfolio designed to balance across 3-5 projects.

▼ Prompt for Copy-Paste

Read the following current project configuration and evaluate it from the perspective of risk diversification.

1. Sales dependency of each project
2. Dependency by ASP
3. Dependency by genre

Calculate the impact amount if the project with the highest dependency ends, and propose 5 similar projects as replacement candidates.

Current status: [ ]

1. Tier Migration Plan — Gradual Transition from Low to High Price

It's difficult to get results with high-ticket projects from the start. Have Codex create a 3-stage blueprint: build a track record with low prices, stabilize with medium prices, and transition to high prices.

▼ Prompt for Copy-Paste

For the following persona and genre, design a roadmap to transition project price ranges in 3 stages: "Low (~3,000 yen) / Medium (3,000-15,000 yen) / High (15,000 yen+)."

For each stage, output a table with:

• Project types to handle
• Required number of articles
• Required verification period
• Criteria for moving to the next stage

Persona: [ ]

Genre: [ ]

Chapter 10: 3 Habits You Should Quit — Growth Through Subtraction

The last chapter is about subtraction.

The difference between those who grow with Codex automation and those who don't lies not in the content of automation but in the "habits they can quit."

1. Quit "Thinking After Writing 100 Articles"

This used to be the gold standard, but not anymore.

Before 100 articles, find a winning path with 5 articles and increase only that winning path. Thanks to Codex, we are in an era where we can quickly verify 5 articles.

Always design "metrics to measure" in the initial verification phase before you start writing.

1. Quit "Isolated Automation"

If you only automate article generation but SNS/analysis/reporting are manual, the bottleneck just moves there.

Automation works because you "combine and flow the whole."

I recommend running at least 3 of the 5 introduced in Chapter 8 as a set.

1. Quit "Skipping Final Human Checks"

This is the most important part.

As you advance automation, you'll want to skip human eyes before publishing. Please never do this.

Codex almost never makes average mistakes, but it makes fatal mistakes a few times a year. Compliance violations, wrong numbers, typos in project names. These can be prevented by a 30-second visual check before publishing.

Holding the final gate of automation is human. This is the decisive difference between those who earn for a long time and those who disappear in the short term.

Conclusion — 1 Million Yen is Built by "Design," Not "Magic"

I have introduced about 40 steps all at once. What I want to say again at the end is the first line I wrote.

1 million yen a month is built by "design," not "magic."

Choose a project in Chapter 1, design persona and offer in Chapter 2, mass produce articles in Chapter 3, build SNS funnels in Chapter 4, run sales copy AB tests in Chapter 5, improve prompt quality in Chapter 6, plug in MCP in Chapter 7, hand over to Codex Automations in Chapter 8, crush pitfalls in Chapter 9, and discard old habits in Chapter 10.

The common idea in all 10 chapters is "minimize the work humans do and maximize the work Codex does."

While you sleep, drafts are raised, SNS posts go out, rankings are monitored, reports are written, and underperforming articles are detected. What you do when you wake up is "judgment of direction" and "final gate check." This is the work structure when aiming for 1 million yen a month.

And if you start today, the first step is decided.

Just copy and paste the prompt for Chapter 1 Technique 3 "LTV Reverse Calculator" and throw it into Codex or ChatGPT now.

How 1 million yen is decomposed into "Unit Price × Conversions × Traffic" will appear before your eyes in 15 minutes. Once you see the "combination you should realistically aim for," all that's left is to proceed through this article in order.

Thank you for reading to the end. I hope this article serves as a catalyst to raise your side hustle's work structure by one level.

To You Who Read This Far

Those who read this far are probably the top 3%. Those who can actually move from there are further 1% of that.

Honestly, by the time you could read such a long article to the end, I don't think you are just on the "information gathering side" anymore.

For such people, I have decided to distribute the "Complete Blueprint for Creating a 1 Million Yen/Month Vending Machine," which I couldn't write in the main text, for free on LINE.

Register on LINE → Send "Roadmap" to the message field. That's it.

→ Receive Free Roadmap