[Overseas AI News] "It's Buzzing" 20 AI Side Hustle & Monetization Ideas Found on Reddit That Grabbed Attention Last Week [AI Side Hustle] reddit/side hustle/ClaudeCode/CodeX/ChatGPT/Gemini/monetization/generative AI/personal development/apps

Introduction

Hello, I'm AI Kawaki.

This week, I've picked up 20 posts from Reddit about AI side hustles, AI automation, and AI SaaS that have been trending overseas.

There is a way of thinking that I value when I do my research.

It is the perspective of

Fact → Abstraction → Application

which appears in Yuji Maeda's masterpiece, "The Magic of Memo-taking."

First, instead of just looking at Reddit posts as overseas examples, I view them as facts.

Next, I abstract from those facts.

And finally, I apply it into a form that Japanese people can execute.

This week, the content was particularly dense regarding vibe coding, AI agents, AI search, SaaS customer acquisition, local sales, and verification costs for AI-generated content.

The important thing is not to copy overseas posts exactly as they are.

Look at the facts, extract the structure, and apply it to your own market.

With this perspective, I will dig deep into 20 posts again this time!!

Table of Contents

1. Total of $75,000 in AI/business automation for clients

2. A suite of B2B lead generation agents built in 33 days after a layoff

3. The concept of running a one-person SaaS company with AI

4. A B2B SaaS idea for classifying Zendesk tickets using AI

5. A side hustle in maintenance and auditing to fix broken AI automations

6. An audit service for AI-generated apps

7. First revenue of $73 with 40 users and 6 paid users

8. A tool to detect landmine projects on Upwork using AI

9. An information product model selling specialized knowledge as a $29 PDF

10. The story of how the reason for not making money with SaaS was customer acquisition, not development

11. $8,000 MRR through a modest no-code choice

12. Outbound experiments tested on a $21,000 MRR developer tool

13. The story of how OSS and LLM projects led to the first enterprise client

14. The story of getting my first user on the 3rd day of launch

15. Consultation on landing the first paid pilot for an AI agent project

16. Learning roadmap + AI tutor app

17. AI companion you can talk to like FaceTime

18. Public API DB excluding dead APIs + Claude plugin

19. Real-time AI fact-check Chrome extension

20. Browser video tool for placing text behind people

1. $75,000 total in AI/business automation for clients

Original post: I just hit $75k building automations for my clients

Posted: 2026-06-20 13:54 JST
Reddit reaction: 149 upvotes / 64 comments

The poster writes that they have reached a total of $75,000 by accumulating business automation projects for clients.

This is a very realistic AI side hustle. It's not about selling AI tools themselves, but about automating and delivering client business workflows.

Specifically, the content involved automating mundane and repetitive tasks within companies, such as inquiry handling, lead processing, payment reminders, inventory notifications, and internal reporting, using n8n, Supabase, WhatsApp Business API, Claude, and GPT.

In the comments section, there were many questions about what kind of automations were built, whether n8n is self-hosted, whether it is handed over to the client, and what the unit price is. The poster replied that small projects are around $500-$800, while large projects are around $2,000-$5,000, and explained that there are cases where maintenance and infrastructure fees are charged monthly.

If you are Japanese and want to imitate this, business automation agency work is faster than building a SaaS first. For SMEs, e-commerce operators, professionals, schools, clinics, and real estate companies, just automating inquiry organization, reservation management, billing reminders, and report creation is enough to make a product.

The tools used are ChatGPT, Claude, n8n, Make, Zapier, Google Sheets, Airtable, and Codex. At first, one task for one company is enough.

2. B2B lead generation agent group built in 33 days after layoff

Original post: Got laid off 33 days ago. Here's everything I've built since.

Posted: 2026-06-22 22:17 JST
Reddit reaction: 264 upvotes / 138 comments

The poster has built multiple data-utilization agents in the 33 days since being laid off.

The content involves collecting data such as Google reviews, trade show exhibitors, government meeting minutes, public data, violation reports, and environmental data, and using them to create a mechanism to find companies and markets to target for sales.

It is interesting that they are using AI to organize this information and convert it into a list of prospective customers.

In the comments section, the discussion leaned toward data collection methods, the accuracy of sales lists, operations that avoid spam, and how to actually sell. It felt like the interest was focused not just on introducing AI tools, but on how to create an entry point for B2B sales.

If a Japanese person were to emulate this, they could collect information on companies that have received subsidies, companies that are hiring, trade show exhibitors, stores with poor Google reviews, and companies mentioned in government documents, and commercialize them as sales lists.

For example, for production companies, you could create a list of companies that are easy to propose website improvements to, for recruitment agencies, a list of companies that seem to be struggling with hiring, and for professionals like lawyers or accountants, a list of companies that would likely be interested in subsidy or grant proposals.

The tools used are Perplexity, Claude, ChatGPT, Google Sheets, Airtable, and Codex. The MVP doesn't need to be a SaaS; selling a list of 50 items is enough.

3. The idea of running a one-person SaaS company with AI

Original post: AI didn't turn me into a 10x dev. It just let me run a whole company by myself

Posted: 2026-06-20 07:03 JST
Reddit reaction: 820 upvotes / 150 comments

This post is not about how AI allowed the user to write code 10 times faster.

What the poster is saying is that thanks to AI, they were able to handle everything by themselves, including peripheral tasks they were not good at, such as development, support, marketing, research, documentation, and drafting sales emails.

In the comments section, there were reactions about how much can be delegated to AI, the limitations of a solo founder, and that while AI speeds up work, turning it into a product is a different issue. It was a highly relatable post, and the perspective of viewing AI not as a development aid, but as a support member for a one-person company really resonated.

If a Japanese person were to emulate this, when building a niche SaaS alone, it is best to use AI not only for development but also for landing pages, FAQs, sales emails, onboarding, inquiry responses, and help articles.

Claude Code, Codex, and Cursor for development, ChatGPT for sales copy, Claude for support replies, and Notion for organizing knowledge. For small SaaS, this kind of comprehensive capability is effective.

4. B2B SaaS idea for classifying Zendesk tickets with AI

Original post: So How can I sort this thing out?

Posted: 2026-06-22 02:19 JST
Reddit reaction: 17 upvotes / 17 comments

The poster writes about their experience building a tool that uses AI to classify Zendesk ticket data, analyzing why responses were delayed and which categories they should be sorted into.

When they tried similar sample tickets at another organization, the AI was able to classify them quite well. However, they sought advice on the barriers of trust, security, and data usage permission when actually receiving production data from companies.

The discussion in the comments section leaned toward practical issues such as how to obtain the data, whether companies would hand over ticket data to a third party, and whether one should enter through the Zendesk or ServiceNow marketplaces.

This is quite suitable for B2B. For companies with over 400 inquiries a day, just classification, prioritization, and root cause analysis are valuable enough.

If a Japanese person were to copy this, it would be better to start not as a SaaS, but by taking anonymized CSVs and creating inquiry classification reports. It is easier to get in by selling it to the head of the support department as a monthly analysis report.

Tools to use: Zendesk API, Claude, ChatGPT, Google Sheets, Looker Studio, Codex, Supabase.

5. Maintenance and audit side hustle for fixing broken AI automations

Original post: Vibe-coded automations are becoming a real problem and I don't think we're talking about it enough

Posted: 2026-06-18 23:35 JST
Reddit reaction: 104 upvotes / 121 comments

The poster writes that automations created sloppily with AI or no-code are causing problems in the field.

The issues are quite specific: lack of error handling, logic that only works by chance, one giant workflow, sloppy handling of credentials, no documentation, and no clear owner. In short, it works for a demo, but is dangerous as a business operation.

In the comments section, there was a long discussion about how this is a problem of inexperience rather than an AI problem, how AI makes immature people look more competent, and how it is dangerous to treat prototypes as business systems. In particular, there were many reactions stating that logs, owners, failure notifications, rollbacks, and ways to revert to manual operation are necessary.

This is quite realistic as a side hustle. You can diagnose business workflows created with Make, Zapier, n8n, and GAS, and sell a package of error handling, logs, notifications, documentation, and maintenance contracts.

If a Japanese person were to do this, it is easy to understand if you present it as follows:

This area isn't flashy, but it's quite solid.

6. Audit service for AI-generated apps

Original post: I’ve been auditing vibe-coded apps — here are the 8 things that break most often, all testable by you in an afternoon

Posted: 2026-06-21 03:37 JST
Reddit reaction: 18 upvotes / 11 comments

The poster lists 8 common ways that AI-generated apps built with tools like Lovable, Bolt, Replit, and Base44 tend to break.

Examples include: other users' emails or IDs appearing in responses, lack of ownership checks while logged in, access rights remaining after Stripe refunds or cancellations, infinite loading during communication errors, API keys or passwords being pasted into AI chat history, layout breaking on older Android devices, and workflows duplicating and causing double submissions, or lack of permission checks on admin screens.

In the comments, there was a particular reaction to the issue of access rights after Stripe refunds. The point is that many AI-generated apps only handle the success path and overlook refunds, cancellations, failed payments, and permission revocation.

If a Japanese person were to copy this, it would be best to first distribute an AI-generated app pre-release checklist for free and charge for detailed audits. Later, you can expand into offering fix implementation, security verification, and Stripe flow checks.

The tools to use are Claude, Codex, Playwright, Stripe test environment, Supabase, Firebase, Notion.

7. First revenue of $73 with 40 users and 6 paid users

Original post: Just hit 73 in revenue with 40 users!

Posted: 2026-06-23 01:26 JST
Reddit reaction: 57 upvotes / 33 comments

The poster writes that out of 40 users, 6 became paid users, resulting in a total revenue of $73.

Looking at the amount alone, it's small, but as an initial validation for solo development, it's quite significant.

In the comments, there were reactions such as the fact that 6 people paid is a huge signal itself, you should look at the paid conversion rate rather than the amount, and it's better to listen to the requests of paid users than free users.

If a Japanese person were to copy this, rather than building a large SaaS right away, it's better to aim for 5 paid users first with a small tool that has only one function.

Instead of increasing free users, ask why they paid. Focus features on that reason. This is very important.

The tools used are Codex, Vercel, Cloudflare Pages, Stripe, Lemon Squeezy, Gumroad, PostHog.

8. A tool that detects landmine jobs on Upwork using AI

Original post: I made a list of Upwork's WORST jobs, updated live

Posted: 2026-06-20 15:14 JST
Reddit reaction: 56 upvotes / 24 comments

The poster is building a tool that uses AI to detect terrible jobs posted on Upwork, rewrite them into honest titles, and list them.

For example, it uses AI to pick up obviously unfair jobs, such as those asking for resume writing, cover letters, sales calls, and social media management for $3 an hour, or those asking for HubSpot automation for $5.

The comment section focused on sharing links to the live list. The reaction is the type of post that strongly resonates with the issue of low-paying, over-demanding jobs on Upwork.

This can be applied quite well in Japan as well. You can create a tool that scores job descriptions from CrowdWorks, Lancers, Coconala, and job boards using AI to identify dangerous jobs, low-paying jobs, and jobs with excessive requirements.

It is easy to present it to side hustle beginners as a Landmine Job Checker. It can be a Chrome extension, a Notion database, a monthly list, or LINE notifications.

9. Information product model: Selling professional knowledge as a $29 PDF

Original post: I own a cabinet shop. I turned what I know into a $29 PDF. Here's how it's going.

Posted: 2026-06-20 03:06 JST
Reddit reaction: 5 upvotes / 34 comments

The poster shares the content of turning their cabinet manufacturing knowledge into a PDF product. While not a post about AI itself, it is a very useful reference for an information product model that is easy to replicate using AI.

They organized their industry experience, price lists, sales scripts, proposal templates, and common pitfalls into a $29 product.

There were 34 comments, and while the number of upvotes is low, it is the type of post that gathered questions about the pricing and the thinking behind productization. It's not a viral hit, but it is useful for practitioners.

If a Japanese person were to imitate this, it would be fastest to convert their own experience into PDFs, templates, checklists, Notion templates, or note articles.

For example, if you are in sales, you could create a collection of sales emails; if you are a video editor, short video script templates; if you are an e-commerce operator, a product page improvement checklist; or if you are an AI user, a collection of prompts or workflows.

AI can be used for structuring, copywriting, creating landing pages, designing covers, and creating additional bonuses for buyers.

10. The story of why the reason you can't make money with SaaS isn't development, but customer acquisition

Original post: 6 months into trying to build SaaS products, and I still can’t crack distribution - i will not promote

Posted: 2026-06-16 19:22 JST
Reddit reaction: 27 upvotes / 111 comments

The poster writes that they have been building SaaS for 6 months, and while they have learned about products, pricing, and onboarding, they just cannot break through with customer acquisition and distribution.

This is a very important failure case for personal development in the AI era. The speed of building with AI has increased. However, without knowing who to deliver to, how to get found, or which channel to sell through, it won't lead to sales.

The reason the comment section has grown to 111 comments is likely because many founders share the same struggle. Distributing is harder than building. SaaS, in particular, is prone to getting stuck here.

If you are a Japanese person looking to copy this, you should release only the landing page before building, and decide first which channel you will use to acquire customers: X, Reddit, SEO, cold emails, note, or YouTube.

Before building an MVP with Codex, it is better to use ChatGPT for the landing page, Claude for customer interviews, and Perplexity for market research.

11. $8,000 MRR with a boring no-code choice

Original post: The boring no-code choice that aged better than the clever one

Posted: 2026-06-19 17:14 JST
Reddit reaction: 8 upvotes / 13 comments

The poster shares the story of growing a niche CRM to $8,000 MRR.

They write that choosing a boring, stable configuration rather than a trendy new no-code tool was better in the long run.

It's a story about how boring tools like industry-specific CRMs, ledgers, booking systems, billing, and customer management are actually easier to monetize monthly than flashy AI features.

The comment count is 13, so it's not a huge viral hit, but the MRR is clearly stated, making it practical. Posts like this aren't flashy, but they are reproducible.

If you are a Japanese person looking to copy this, small management tools for niche industries are a good target. For example, chiropractic clinics, beauty salons, professional services, schools, vacation rental management, small-scale e-commerce, or classroom management.

The tools used are Airtable, Coda, WordPress, Supabase, Stripe, Codex, Claude. At first, it is easier to sell by presenting them as tools to reduce the hassle of work rather than putting AI at the forefront.

12. Outbound experiment tested with a $21,000 MRR developer tool

Original post: multichannel vs email only outbound. 6 months of data

Posted: 2026-06-18 17:05 JST
Reddit reaction: 8 upvotes / 7 comments

The poster is comparing email-only sales with multichannel sales (email + LinkedIn outreach) over 6 months to sell a $21,000 MRR developer tool.

The point is not about the product, but looking at the numbers of the sales funnel. They are verifying which is more effective by comparing reply rates, meeting rates, and deal sizes.

Although the number of comments is small at 7, it is valuable in practice because it provides MRR and sales experiment data.

A common failure in AI side hustles and SaaS is having no way to sell after building. This post teaches the importance of looking at sales numbers after building.

If a Japanese person were to copy this, once they build an AI tool, they should check the reply rate for each channel, such as 100 emails, 100 X DMs, and 100 LinkedIn messages.

Creating sales copy with ChatGPT, classifying replies with Claude, managing numbers in Google Sheets, and sending via Apollo or Instantly. These kinds of unglamorous verifications lead directly to sales.

13. How OSS and LLM projects led to the first enterprise client

Original post: Thesis is more important that product[I will not promote]

Posted: 2026-06-23 08:37 JST
Reddit reaction: 8 upvotes / 7 comments

The poster writes that although they were initially unprofitable, the OSS and technical initiatives they created in the past led to their current LLM projects.

It is about how technical hypotheses, published code, past achievements, and trust through partners led to enterprise projects, rather than just selling a finished product.

The number of comments is small, but it is a good reference for those starting in the AI/LLM field through contract work.

If a Japanese person were to copy this, it is good to publish small LLM demos, industry-specific RAG samples, MCP integrations, or tools made with Claude Code on GitHub.

Rather than going viral in the short term, this is the type that leads to corporate projects and consultations later on. Writing development logs on note or X also serves as sales.

14. The story of getting my first user on the third day of launch

Original post: I just got my 1st user!!!!!!!!

Posted: 2026-06-18 11:04 JST
Reddit reaction: 184 upvotes / 169 comments

The poster writes that they were feeling down after posting to Reddit post-launch with no response, but when they checked the analytics screen, they saw an IP other than their own, and upon checking the DB, they found a real user had registered and was using it.

I think the comment section grew to 169 entries because many solo developers empathized with this feeling. It's not the first sale, but the moment someone you don't know uses your product for the first time has value.

Even in AI side hustles, the first thing to look at isn't big sales, but whether someone you don't know registers, completes onboarding, or uses it for even a few minutes.

If a Japanese developer were to copy this, they should install PostHog or Google Analytics at the time of the MVP release to make initial actions visible. Just knowing who stopped where shows you where to fix things next.

15. Consultation on getting the first paid pilot for an AI agent project

Original post: Experienced founders: Best B2B distribution hacks people don’t usually talk about? I will not promote

Posted: 2026-06-19 02:47 JST
Reddit reaction: 7 upvotes / 16 comments

The poster is building an AI agent for administrative tasks at a construction MEP engineering firm and is asking for advice on how to secure the first paid pilot.

What's important here is that they aren't trying to sell the AI agent as a general-purpose tool. They have narrowed it down to a specific industry and task: construction, design, and administrative work.

In the comment section, the discussion focused on early B2B sales, referrals, industry networks, and the idea of opting for a paid pilot rather than a free demo.

If a Japanese developer were to copy this, it would be easier to sell if they made the AI agent industry-specific—such as for construction, professional services, medical, education, real estate, or e-commerce operations—rather than a jack-of-all-trades tool.

For the first MVP, you don't need to automate everything; just semi-automating one administrative task is enough.

16. Learning roadmap + AI tutor app

Original post: built an app that turns I want to learn X into a full roadmap + courses + a tutor that won't let you quit

Posted: 2026-06-17 05:12 JST
Reddit Reaction: 110 upvotes / 86 comments

The poster introduces an app that creates a roadmap, courses, and a tutor to encourage consistency once a user inputs a theme they want to learn.

The key is not just searching for teaching materials, but deciding what to learn in what order, what to do today, and how to support the user so they don't quit halfway.

With 86 comments, interest in learning-based AI is reasonably high. While the education sector is highly competitive, there is still room if you narrow it down to certifications, English, programming, side hustle skills, entrance exams, or sales talk.

If Japanese developers want to emulate this, they should focus on a single purpose rather than a general-purpose learning app.

For example, it could take the following forms:

The tools to use are Claude, ChatGPT, YouTube API, Notion, Supabase, Codex, Stripe.

17. AI companion you can talk to like FaceTime

Original post: I built an AI companion that people can talk to like FaceTime :- here’s what I learned

Posted: 2026-06-22 00:36 JST
Reddit Reaction: 9 upvotes / 24 comments

The poster created an AI companion that can talk naturally like FaceTime instead of text chat, and is having a small group try it out.

The lesson learned is that users were seeking natural conversation and personality, not just correct answers.

However, this area is quite competitive. I think it is difficult to copy it as a simple AI friend app.

But, you can turn it into a side hustle by narrowing down the use case.

There were 24 comments, and it was the type of post that gathered interest regarding the uses of conversational AI and continued usage.

For a Japanese audience, English conversation, interviews, and sales role-play are realistic. Especially in areas where you practice with voice, it is a great match for AI.

18. Public API DB with dead APIs removed + Claude plugin

Original post: Here is basically every public api you will ever need, and the dead ones are filtered out

Posted: 2026-06-17 21:02 JST
Reddit reaction: 52 upvotes / 30 comments

The poster has created a site that aggregates public API lists, removes duplicates and dead links, and checks them daily. Furthermore, the fact that it can be used as a Claude plugin feels very much in line with the AI era.

It is not just a collection of links; the value lies in keeping them in a usable state.

In the comments section, there were reactions regarding the usefulness of the API list, maintenance, Claude integration, and how developers can use it.

If a Japanese user were to replicate this, they could organize business APIs, municipal data, subsidy APIs, EC APIs, SNS APIs, and AI tool APIs in the Japanese-speaking sphere into a database with status monitoring.

Furthermore, it could be sold as an MCP server, API search tool, or developer template that is easy to use from Claude or Codex.

19. Real-time AI fact-checking Chrome extension

Original post: built a factchecker that catches politicians lying in real time

Posted: 2026-06-19 03:48 JST
Reddit reaction: 13,729 upvotes / 750 comments

This post received a significant reaction. The poster created a Chrome extension that extracts claims to be verified from speech transcripts and uses search results to have Claude judge them.

On the surface, it is a tool for checking politicians' statements in real time, but its potential applications are quite broad.

For example, it could be adapted for sales materials, financial results briefings, webinars, YouTube live streams, internal training, medical/legal content, and checking advertising copy.

With 750 comments, it is being heavily debated, including political reactions. However, if you were to replicate it, it would be safer and easier to sell if you focused on B2B document verification, video verification, and advertising copy checking rather than diving into the political realm.

The tools used are Claude, Whisper, Search API, Chrome extension, Codex, Supabase. Initially, it could also work as a service that provides a verification report when you input a video URL, rather than as an extension.

20. Browser video tool that places text behind people

Original post: I made a browser video tool that puts text behind people in your shot, no green screen or rotoscoping

Posted: 2026-06-21 20:00 JST
Reddit reaction: 222 upvotes / 56 comments

The poster is building a browser tool that can place text behind people in videos without green screens or manual rotoscoping.

This is easy to understand. For video creators, it's valuable if a tedious editing task can be finished in one click every time.

In the comments section, this type of post generated reactions from people asking how it's processed, how it differs from other editing features, and expressing a desire to use it.

If Japanese creators want to copy this, it's better to sharpen just one feature for short-form videos.

For example, things like the following:

The tools to use are MediaPipe, Segmentation, Runway, Kling, CapCut, Codex, WebCodecs, Vercel, Stripe.

Conclusion

Looking at the 20 items this time, these three are particularly easy for Japanese people to target.

The first is AI business automation for clients. The $75,000 post is a prime example, but this isn't about selling AI tools; it's about acting as an agency to reduce a company's tedious tasks. This is quite easy to replace in Japan as well.

The second is B2B lead generation and sales list creation. Using Google reviews, trade shows, government documents, job postings, subsidies, and public data to extract companies to target for sales. This is also easy for Japanese people to replicate.

The third is Auditing and repairing AI-generated apps or automation. As more people become able to build with AI, the value of those who can fix broken things, check them before release, and maintain them will increase.

What's important is to look at what kind of pain points are gathering reactions, where the money is being generated, and what it can be converted into for Japanese people to safely replicate.

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