Author: Delores Davidson

How to Choose a Payment Provider If You Run a Marketplace or Platform

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Standard payment gateways are built for one merchant collecting card payments. Marketplaces and platforms break that model: money flows both ways, and payouts happen at volume. The provider you choose needs explicit support for batch payouts, API-triggered disbursements and platform-scale reporting – or it becomes your bottleneck.

Key takeaways

  • Marketplaces break the single-merchant model: you collect from buyers and distribute to sellers, often at high volume.
  • Batch payout capability is non-negotiable above a certain size – manual transfers are a liability, not a workflow.
  • The most efficient platforms automate payouts entirely via a well-documented disbursement API.
  • Embedded payments for sub-merchants is a distinct capability from basic payouts – ask about it specifically.
  • Demand a transparent per-payout fee and a single dashboard showing processed, pending and failed payouts.

Imagine you’ve built a marketplace connecting 80 freelancers with clients across Southeast Asia. Business is growing. Every week, dozens of projects get completed – and dozens of payouts need to go out.

In the beginning, you handled it manually. Checked completed jobs on Monday, transferred money one by one via bank transfer on Tuesday. By Wednesday, half the freelancers had messaged asking where their payment was.

This is the moment most marketplace founders realise that standard payment gateways – the ones designed for a single merchant accepting card payments – aren’t built for their business model.

Here’s what to look for when you’re evaluating payment infrastructure for a marketplace or platform.

The Core Problem With Standard Payment Gateways

Most payment providers are designed around a simple model: one merchant, many customers. Money flows in one direction – from the customer to you.

Marketplaces and platforms break this model in two ways:

  1. Money flows both ways. You collect from buyers and distribute to sellers, freelancers, contractors, or partners. Sometimes in the same transaction cycle.
  2. You’re operating at volume. As the platform grows, payouts happen constantly – often hundreds or thousands per month. Manual processing doesn’t scale.

A provider that doesn’t have explicit support for payouts, disbursements, or platform-scale operations is going to become a bottleneck.

What to Look For: The Platform Payment Checklist

Batch Payout Capability

The ability to process many payments in a single operation is non-negotiable for platforms above a certain size. Manually triggering individual transfers for each seller is not a workflow – it’s a liability.

Ask any provider: can I upload a list of recipients and amounts and process them as a batch? If the answer involves manual steps or no clear batch tooling, move on.

API-Triggered Disbursements

Beyond batch uploads, the most efficient platforms automate payouts entirely via API. When a seller completes an order and the platform’s conditions are met, the payout is triggered automatically – no human in the loop.

This requires a payment provider with a clear API endpoint for disbursements, well-documented authentication and error handling, and a predictable per-payout fee structure so you can model the cost into your platform economics.

ONE Payments supports both batch payouts and API-triggered disbursements – meaning platforms can automate the payout layer rather than treating it as an ongoing manual process. See how ONE Payments handles platform payments.

Embedded Payments for Sub-Merchants

Some platforms want to go further: not just paying out to sellers, but allowing sellers to accept payments through the platform itself. This is embedded finance – and it’s a different capability from standard payouts.

If your roadmap includes letting sub-merchants collect payments through your platform, ask specifically about embedded payment tools. This is a distinct product from basic payout infrastructure.

Transparent Fee Structure at Scale

When you’re processing payouts at volume, fee predictability matters as much as fee size. A provider charging USD 2 per local transfer and USD 28 for a SWIFT transfer is more useful than one that gives you a “competitive rate” with no specific numbers attached.

Model your payout mix before you evaluate pricing: How many payouts per month? What’s the split between local and international recipients? What currencies are involved? With those numbers, you can calculate the actual monthly cost for any provider being considered.

A Single Dashboard Across the Whole Platform

As volume grows, visibility becomes critical. You need to see – in one place – which payouts have been processed, which are pending, which failed and why. Reconciling payment data from multiple systems is hours of work that your operations team shouldn’t be spending.

Ask to see a demo of how payout reporting works in practice. Can you filter by date, recipient, status, currency? Can you export in a format your accounting system can read?

Questions to Ask Any Payment Provider

Before committing to a provider for a marketplace or platform, run through these directly:

  • Do you support batch payouts? If yes, how many recipients per batch?
  • Can payouts be triggered via API? What does the endpoint look like?
  • What’s the per-payout fee? For local transfers and international?
  • Do you support embedded payments for sub-merchants?
  • What currencies can recipients be paid in?
  • What happens when a payout fails? Is there automatic retry? How are failures surfaced?

The quality and specificity of the answers will tell you a lot about whether the provider has actually built for platform use cases or is just accommodating them reluctantly.

Scaling Without Surprises

The businesses that build scalable marketplace payment infrastructure tend to have one thing in common: they thought about payouts before they needed them, not after they became a problem.

If you’re building or growing a marketplace or platform and want to understand how ONE Payments handles payout infrastructure – batch, API, and multi-currency – the clearest path is a direct conversation with the team.

Talk to ONE Payments about your platform

How I Finally Got Control of My 23 Subscriptions

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By Delores Davidson

I’ll start with the number that embarrassed me: 23.

That’s how many active recurring charges I was paying for when I finally sat down and counted. Not estimated – actually counted, with receipts. I’m a CTO. I manage infrastructure budgets. I review quarterly spend reports. And somehow I had 23 subscriptions running across personal and company accounts, totalling roughly $480 a month, with at least six of them completely unused for three months or more.

The problem isn’t stupidity. The problem is that subscription creep is designed to be invisible.

Why Nobody Tracks This

Every subscription is individually rational. $12/month for a design tool – reasonable. $8/month for a cloud storage backup – cheap insurance. $15/month for a video editing app you used for that one project – you’ll use it again, probably.

Then multiply by 23.

The charges are small enough that no single one triggers attention. Annual subscriptions bill once and disappear from memory. Free trials convert silently – you meant to cancel before day 14, but day 14 was a Tuesday and you were in back-to-back meetings. Team tools get adopted with enthusiasm and abandoned within weeks, but the billing doesn’t know about the abandonment.

And here’s the real killer: there’s no single place that shows you everything. Personal cards, company cards, PayPal, direct debits – the charges are scattered across systems that don’t talk to each other. Building the complete picture requires opening every bank statement, cross-referencing with email receipts, and checking last login dates. It’s a full afternoon project.

So you never do it. You tell yourself you’ll do it “this weekend.” You don’t. The subscriptions don’t care. They keep charging.

The Audit

I didn’t plan to audit my subscriptions. I was actually trying to find a specific receipt for a tax filing when I asked my assistant – through our usual Telegram chat – to help me search my email.

Then I thought: while you’re in there, find all subscription receipts and recurring payment confirmations from the last three months. List them with amounts and billing frequency.

What came back was a structured table. Service name, monthly or annual amount, billing cycle, last receipt date. Grouped by category: development tools, media and creative, productivity, entertainment, cloud and hosting.

Twenty-three lines. $480/month.

I stared at it for a minute. Then I asked the follow-up question: “Check when I last actually interacted with the service – any recent emails from them, any mentions in our conversations.”

That’s when the dead subscriptions surfaced. A project management tool from two team iterations ago – still active, $15/month, last login four months prior. A video conferencing subscription I’d replaced with another one but never cancelled. A “premium” weather app I’d signed up for during a hiking trip and forgotten about. A code formatting tool that was free when I first installed it and had silently moved to a paid tier.

Six services, completely unused. $87/month, going nowhere.

Then one more ask: “Which of these have overlapping functionality?” Two cloud storage services doing the same thing – one personal habit, one company policy, both paying for 1TB I was using 200GB of. Two project management tools from different eras, one actively used, one zombie.

Total waste: about $120/month in unused or redundant subscriptions. That’s $1,440 a year I was paying for nothing.

The entire audit took maybe 15 minutes of my time – mostly reading the results and making decisions. The assistant did the email searching and cross-referencing. I use Amplify, and the email access through Gmail integration made this trivially easy – but the principle applies anywhere you have an assistant with email access.

The System That Stuck

The audit was a one-time win. Satisfying, but a one-time win. What actually changed my relationship with subscriptions is the ongoing system I set up afterward:

Monthly subscription digest

On the 1st of each month, the assistant sends me a summary: “Here’s what renewed this month, total amount, anything I’ve flagged as potentially unused.” It takes 30 seconds to scan. Most months, everything’s fine. But twice now it’s caught a service I’d stopped using – once after a project ended, once after we switched tools. Both times I cancelled within the week instead of letting it run for months.

Trial expiry tracking

When I sign up for a free trial now, I mention it in the chat: “Started a 14-day trial of [service].” The assistant notes the end date and sends me a reminder two days before conversion. Simple. I’ve cancelled three trials I would have forgotten about. At $15-25 each, that’s real money.

Annual renewal alerts

This is the sneaky one. Annual subscriptions are easy to forget because you only see the charge once a year. Two weeks before each annual renewal, the assistant flags it: “Your Figma team plan renews in 14 days at $540/year. Last quarter, 4 of 8 seats were active. Keep or cancel?”

That “4 of 8 seats” detail is crucial. I was paying for seats for people who’d left the team. The assistant knew this because it could see the lack of activity in related emails. I downgraded to 5 seats and saved $200/year on that single subscription.

Renewal negotiation research

Before major renewals, I ask: “Check if there’s a cheaper alternative to [tool] or if they offer a retention discount.” The assistant researches current pricing across competitors and checks if the vendor has any published retention offers. Twice this has led me to contact the vendor and negotiate – once successfully ($8/month savings on a $40/month tool by mentioning a competitor’s pricing).

What It Can’t Do

Being honest about the boundaries:

It can’t automatically cancel subscriptions for you. You still need to go to each service and click the cancel button. Some make this deliberately difficult (looking at you, services that require a phone call to cancel). The assistant identifies what to cancel – you do the clicking.

It works from email receipts, not bank statements. If a service charges your card but sends no email confirmation, the assistant won’t catch it. Most legitimate subscriptions send receipts, but not all. Cash payments or charges without email trails are invisible.

It’s not accounting software. For business expense categorisation, tax reporting, or receipt archival – use proper accounting tools. This is about awareness and decision-making, not bookkeeping.

The initial audit takes your attention. The assistant does the searching and organising, but you need to review the results and make decisions. “Should I keep this?” is a judgment call only you can make. Budget 15-20 minutes for the first audit.

The Numbers

One-time audit: Identified $120/month in waste. Cancelled six unused subscriptions and consolidated two redundant ones. Annual savings: $1,440.

Ongoing system: Catches 1-2 forgotten trials per month ($15–25 each avoided). Flagged two annual renewals for seat reduction, saving ~$350/year combined. One successful vendor negotiation saving $96/year.

Total first-year recovery: Roughly $2,000 in charges that would have continued indefinitely.

Cost: $9.99 platform fee + approximately $1-2 in usage per month (email scanning and search queries) + 7.5% service fee. Call it $12/month.

ROI: $12/month in cost for $120+/month in recovered waste. The subscription audit paid for the entire platform fee for a decade – in the first 15 minutes.

What I’d Suggest

Try this tonight: ask your assistant (or search your email manually if you don’t have one) to find every subscription receipt from the last three months. Just the list – service name and amount.

You might be at 8 subscriptions totalling $60. Fine – you probably know about all of them.

Or you might be at 23 subscriptions totalling $480, with six you forgot existed. And if you’re anything like me, that number will bother you enough to actually do something about it.

The subscriptions don’t audit themselves. But they don’t have to be your job either.

Amplify connects to your email and calendar with persistent memory – subscription tracking, trial reminders, and renewal alerts through one assistant in Telegram or Discord. $9.99/mo platform fee + 7.5% service fee + pay only for what you use. [See how it works →]

I Built My First App in a Weekend Without Writing a Single Line of Code

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I’m a marketing manager. I have a journalism degree. The last time I “wrote code,” I was twelve years old, copy-pasting HTML into a Neopets profile page.

Last weekend, I shipped a working app.

It tracks the books my partner and I have lent to friends — who has what, when they took it, and a polite nudge button that emails them after 60 days. It has a login screen. It has a database. It has a working “forgot password” flow. I built the whole thing on Saturday and Sunday, between coffee and dinner, while watching a show in the background.

I did not write the code. An AI did.

This is my honest account of what people are now calling vibe coding — what it actually feels like as a non-technical person, where it genuinely surprised me, and the one moment I almost did something stupid that could have cost me real money.

What Vibe Coding Actually Is (In Plain English)

Vibe coding is building software by describing what you want in normal language and letting an AI write the code for you. You don’t learn syntax. You don’t memorize functions. You type something like “make a login page where users sign in with email and password,” and a tool generates the actual working page.

The phrase was coined in February 2025 by Andrej Karpathy, a co-founder of OpenAI. He described it as “fully giving in to the vibes” — letting the AI handle the code while you focus on what you want it to do.

For most of 2025 it was a niche thing for engineers. By 2026 it’s how my non-technical friends are quietly shipping side projects.

Why I Tried It

I’d been complaining about the book-lending problem for months. Every time we lent a book to a friend, I’d write it on a Post-it. The Post-it would fall behind the bookshelf. The book would never come back.

I’d looked for an app to solve it. Nothing fit. The closest options wanted $4.99/month for features I didn’t need.

A friend who works at a startup told me, casually, “Why don’t you just build it? It would take you a weekend now.”

I laughed. He didn’t.

The Setup (Total Time: 11 Minutes)

I picked a tool called Lovable — one of several apps in this space, alongside Bolt, Cursor, and Replit Agent. Lovable felt the most beginner-friendly because it shows you a live preview of your app while you describe it.

I signed up on Saturday morning at 9:14 AM. By 9:25, I was typing my first prompt:

“I want a simple app where I can log books I’ve lent to friends. Each entry should have the book title, the friend’s name, the date I lent it, and a button to mark it returned.”

Twenty seconds later, a working version appeared on the right side of my screen.

I almost cried. Not from joy — from a strange, slightly destabilizing feeling that something I had assumed was hard had just stopped being hard.

What Surprised Me

1. It understood vague instructions better than I expected.
When I typed “make it look nicer, more like a journal,” it actually did. Cream background, serif font, soft shadows. It made taste decisions I would have made.

2. It made mistakes I could see.
When I asked for an email reminder feature, it generated something that looked like it would send emails — a button that said “Send Reminder” — but nothing actually happened when you clicked it. The AI had built the visual part and skipped the actual sending. I had to specifically prompt: “the button should send a real email through a service, not just pretend to.”

3. It made mistakes I couldn’t see.
This is the part that scared me, and it’s why I’m writing this article instead of just posting screenshots.

The Moment I Almost Did Something Stupid

By Sunday afternoon, my app worked. Login, database, the works. I was about to share it with my partner when I noticed something off.

I had asked the AI to “let users see all the books they’ve lent.” The button worked. But when I tested it with a second account I’d created, that account could also see my books. And edit them. And delete them.

The AI had built a feature that fetched book records — but had not added a check to make sure the person looking at the records was the person who owned them.

If this had been a real app, with real users, anyone could have seen anyone else’s data.

I only caught it because I happened to test with two accounts. If I’d shipped it as-is and posted it on Twitter, I would have leaked the personal data of every user.

I went down a rabbit hole that night and learned that this is the most common security flaw in vibe-coded apps. It’s called Insecure Direct Object Reference (IDOR), and it’s been on the OWASP Top 10 list of web vulnerabilities for years.

I stumbled onto a really clear breakdown of this — and four other risks I hadn’t thought about — in a guide written by engineers at a software firm called Valletta. Their piece, Vibe Coding Explained: What It Is & 5 Risks to Avoid, walks through SQL injection, missing authentication, hardcoded secrets, and outdated dependencies — all in plain language. It’s the article I wish I’d read before my weekend project, not after. If you’re going to vibe code anything that touches real people’s data, read it first.

What I’d Tell Anyone Else Trying This

After two days of building, breaking, fixing, and re-prompting, here’s what I think actually matters:

Start absurdly small. Don’t say “build me a Notion competitor.” Say “build a page with one form that saves names to a list.” Add features one at a time. The AI handles small specific requests beautifully and large vague ones badly.

Test with two accounts. This is the single most important habit I picked up. Anything that handles user data needs to be tested from a second user’s perspective. If account B can see account A’s stuff, you have a problem.

Read what it generated, even if you don’t understand it. I don’t read code fluently. But I learned to skim it for words like password, email, and delete. If something dramatic was happening in the code, I’d ask the AI to explain that section in plain English. It always did.

Don’t ship it to strangers. My book app is for me and my partner. That’s the right scale for a weekend project. The moment you imagine real strangers using something you vibe-coded, the bar shifts dramatically — and the risks I mentioned above become concrete liabilities, not theoretical worries.

Write down what you built. Before going to bed Sunday night, I wrote a one-page document explaining what each part of my app does. Not the code — the features. “The reminder button sends an email through this service.” “The login uses this method.” Future-me, trying to fix something six months from now, will thank past-me.

The Honest Verdict

Vibe coding didn’t make me a developer. I still don’t know what most of the code in my app does. If something breaks, I’ll have to ask the AI to fix it, because I can’t.

But it did something I didn’t expect: it made the gap between I have an idea and the idea exists in the world about ten times smaller. For a problem like mine — a personal annoyance worth zero dollars to solve — that’s enough.

I don’t think this replaces real software engineering. I read enough this weekend to understand that there are good reasons people spend years learning this stuff. The apps that handle your money, your medical records, your private messages — those should not be vibe-coded by someone like me.

But the small, weird, personal problems that aren’t worth a startup? The ones we used to solve with spreadsheets and Post-its and a vague hope?

We can just build them now.

It’s a strange feeling. I’m still getting used to it.

Have you tried vibe coding? What did you build, and what surprised you? Drop a comment below — I want to know I’m not the only one who suddenly has a small empire of weekend apps.

Best AI App Builders: Build Apps with AI for App Development

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Best AI App Builders: Build Apps with AI for App Development

In the rapidly evolving world of technology, AI app builders have become indispensable tools for developers and non-developers alike. These platforms empower users to build apps quickly and efficiently by leveraging the power of artificial intelligence. From simplifying coding tasks to enhancing creativity, AI app builders are revolutionizing the app development landscape.

Introduction to AI App Builders

What is an AI App Builder?

An AI app builder is a platform that lets users create apps using AI-powered tools. These platforms often require little to no coding, making app development accessible to non-technical users. AI app builders harness machine learning and natural language processing to help users describe what they want and transform these prompts into functional apps. By automating complex backend processes and integrating with existing tools, these platforms streamline the app creation process.

Benefits of Using AI in App Development

Using AI in app development offers numerous benefits. AI tools automate repetitive tasks, enhancing productivity and enabling developers to focus on creative aspects. AI-powered platforms can suggest app ideas, generate code snippets, and optimize workflows. Additionally, AI features allow for seamless integration with APIs and databases, making it easier to deploy functional applications. This results in faster app development, enabling users to build apps in minutes rather than months.

Overview of the Best AI App Builders in 2025

As AI technology advances, the best AI app builders in 2025 will offer robust features and seamless user experiences. Platforms like Airtable, Softr, and Firebase lead the way, providing tools that cater to diverse use cases. These platforms integrate generative AI, enabling users to build AI-powered apps with ease. By offering enterprise-grade solutions and full-stack application support, the best AI app builders help users create sophisticated apps that meet their unique needs.

Top Features of AI-Powered App Builders

AI Features That Enhance App Development

AI-powered app builders are equipped with features that significantly enhance app development. These include natural language processing, which allows users to communicate their app ideas in plain language. Additionally, AI agents provide coding assistance, automating the generation of backend logic and database schemas. With built-in AI models, these platforms can suggest improvements and optimizations, ensuring that the final product is efficient and user-friendly.

Integration Capabilities with Existing Tools

Integration capabilities are crucial for AI app builders. These platforms support seamless connections with existing tools and APIs, facilitating smooth data exchange. By working with popular tools like ChatGPT and enterprise software, AI app builders ensure that users can extend their apps’ functionality without writing extensive code. This integration is essential for creating apps that align with current workflows and data sources, enhancing the overall application development process.

Generative AI for Creative App Ideas

Generative AI plays a key role in fostering creativity in app development. AI app builders equipped with generative AI can propose innovative app ideas and assist in designing user interfaces. This technology helps users explore various app concepts and refine them into viable applications. By leveraging generative AI, developers can create custom AI solutions tailored to specific needs, ultimately building apps faster and more efficiently than ever before.

No-Code vs. Traditional Coding in App Development

Understanding No-Code Platforms

No-code platforms have revolutionized app development by allowing users to build apps without writing code. These platforms leverage AI tools and drag-and-drop interfaces, making them accessible for non-technical users. By automating backend processes and utilizing AI features, no-code platforms enable rapid app creation, making them ideal for those who need to deploy apps quickly and efficiently.

When to Use No-Code Solutions

No-code solutions are particularly beneficial when time and resources are limited. They are best suited for projects that do not require complex backend logic or custom AI deployments. These platforms allow users to focus on app ideas and workflows without the need for extensive coding knowledge, streamlining app development and increasing productivity.

Comparing No-Code with Traditional Coding

While no-code platforms offer ease of use and speed, traditional coding provides greater flexibility and control. Traditional coding is preferred for complex, enterprise-grade applications that require custom AI solutions and sophisticated backend logic. However, no-code platforms are increasingly integrating AI-powered features, blurring the lines between the two approaches and offering more robust solutions for app developers.

Building Internal Tools with AI

Using AI App Builders for Enterprise-Grade Solutions

AI app builders are pivotal in developing enterprise-grade internal tools. These platforms harness AI to automate repetitive tasks and streamline workflows, allowing businesses to create sophisticated applications tailored to their specific needs. By leveraging AI-powered features, companies can build apps that enhance productivity, integrate seamlessly with existing systems, and support full-stack application development.

Examples of AI-Powered Internal Tools

Companies are increasingly using AI-powered tools for project management, data analysis, and customer relationship management. For instance, AI agents can automate data entry and analysis, while natural language processing tools facilitate seamless communication. These applications empower businesses to optimize operations and make data-driven decisions, showcasing the transformative potential of AI in internal tool development.

Best Practices for Developing Internal Apps

When developing internal apps, it is crucial to focus on integration capabilities and user experience. AI app builders should support APIs for seamless data exchange and offer intuitive interfaces that align with the users’ needs. Additionally, deploying apps with robust security measures and scalable architecture ensures that internal tools remain effective and adaptable to changing business requirements.

How to Build an AI-Powered App Faster

Steps to Get Started with AI App Development

To build an AI-powered app quickly, start by choosing a suitable AI app builder that aligns with your project requirements. Platforms like Airtable, Softr, or Firebase are excellent choices for both beginners and seasoned developers. Begin by clearly defining your app ideas and describing what you want from the application. Leverage AI tools within these platforms to automate complex backend logic and integrate APIs for enhanced functionality. Make use of natural language processing to interact with the platform, allowing the AI models to generate code snippets and assist in the app creation process efficiently.

Tips for Accelerating the Development Process

To accelerate the development process, take advantage of the built-in AI features that app builders offer. Use AI agents to automate repetitive coding tasks and streamline workflows. Employ drag-and-drop interfaces available in no-code platforms to build apps without writing code. Focus on leveraging generative AI to explore innovative app concepts and refine them into functional applications. Integration capabilities with existing tools and data sources will also help you create apps faster by facilitating seamless data exchange and reducing development time.

Deploying Your AI App Efficiently

Efficient deployment of your AI app involves ensuring that your application is scalable and secure. Use AI app builders to automate deployment processes and ensure that your app integrates well with existing systems. Utilize APIs to enhance the app’s functionality and provide a smooth user experience. Prioritize testing the app thoroughly to address any potential issues before going live. By following these practices, you can deploy your AI-powered app swiftly, ensuring it meets enterprise-grade standards and performs effectively once launched.

Conclusion

Future of AI App Builders

The future of AI app builders is promising, with advancements in AI technology continually enhancing their capabilities. As AI development progresses, these platforms will offer even more robust features, allowing users to build sophisticated apps with minimal effort. Expect future AI app builders to incorporate more advanced AI models and automation features, enabling users to create custom AI solutions that cater to evolving use cases and business requirements.

Final Thoughts on Choosing the Best AI App Builder

When choosing the best AI app builder, consider your specific app development needs and the platform’s capabilities. Look for AI-powered features that align with your project, such as natural language processing, integration with APIs, and generative AI. Evaluate platforms like Airtable, Softr, and Firebase for their ease of use, especially if you want to build apps quickly without extensive coding. Ensure that the app builder supports scalable and secure deployment to accommodate future growth and technological advancements.

Encouragement to Explore AI-Powered Solutions

AI-powered solutions represent the future of app development, providing opportunities to innovate and enhance productivity. Whether you’re a developer or a non-technical user, exploring AI app builders can open doors to building functional and creative applications effortlessly. Embrace the power of AI to transform your app ideas into reality, and stay ahead in the competitive technology landscape by utilizing AI tools to streamline your development processes and create impactful applications.