![](https://cdn-images-1.medium.com/max/2400/0*YJtcMmB1bLvJLFGm)

If you’ve been building software long enough, you know the real horror story isn’t the bug you can’t fix — it’s the one you don’t even know exists. Nothing tanks confidence in a project faster than flaky tests, untraceable crashes, and deployment chaos.

The good news? Python has a treasure chest of tools designed to prevent your next project from becoming a dumpster fire. And I don’t mean the usual suspects like `pytest` or `virtualenv`. I’m talking about tools that even seasoned developers rarely touch — the kind that’ll have you catching issues before they escalate, automating sanity checks, and sleeping like an actual human being at night.

Let’s dive in.

### 1. `bandit` — Security Checks You Wish You Ran Earlier

Imagine shipping code only to realize you hardcoded credentials in a forgotten utility file. Nightmare fuel.

`bandit` scans your Python codebase for common security issues: weak cryptography, unsafe function usage, and other “I’ll fix it later” mistakes.

```
pip install banditbandit -r your_project/
```

> Tip: Run it as part of your CI pipeline. Because nothing feels worse than finding out from a Hacker News post that your app leaked an API key.

### 2. `py-spy` — Your Project’s Black Box Recorder

Performance bugs are the trickiest. They only show up when you’re demoing to your boss, right?

`py-spy` is a sampling profiler that lets you peek into what your Python process is doing *without restarting it*. No code changes, no restarts, no excuses.

```
pip install py-spypy-spy top --pid <your_pid>
```

> Fact: NASA has been using profiler tools like this for decades — because when you’re running code on a rover 200 million miles away, debugging isn’t really an option.

### 3. `hypothesis` — The Test Generator You Didn’t Know You Needed

We humans write boring tests. We check the happy path, maybe throw in a couple of edge cases. But what about the edge cases of edge cases?

Enter `hypothesis`. It generates thousands of randomized test inputs, automatically exploring corners of your code you’d never manually think of.

```
from hypothesis import given, strategies as st@given(st.lists(st.integers()))def test_sorting(nums): assert sorted(nums) == sorted(sorted(nums))
```

This has caught real-world bugs in libraries maintained by teams of PhDs. If they can miss things, so can you.

### 4. `safety` — Dependency Audit on Autopilot

Your code is only as safe as your dependencies — and let’s face it, half of PyPI is one bad day away from CVEs.

> `safety` checks your installed packages against a database of known vulnerabilities.

```
pip install safetysafety check
```

Run this once and you’ll probably discover that your favorite library hasn’t patched a critical issue since 2019.

### 5. `structlog` — Logging That’s Actually Readable

Default Python logs? About as decipherable as hieroglyphics.

`structlog` lets you log in structured JSON, making it painless to search, filter, and debug in production. Pair it with tools like Elasticsearch or Loki, and suddenly tracing that elusive bug isn’t a guessing game anymore.

```
import structloglog = structlog.get_logger()log.info("user_logged_in", user_id=123, feature="checkout")
```

> Because the only thing worse than a production error is a production error with cryptic logs.

### 6. `tox` — Testing in Parallel Universes

You tested locally on Python 3.10. CI runs on 3.9. Production is still on 3.8 because “upgrades break stuff.” Sound familiar?

`tox` runs your test suite across multiple Python environments automatically. One config file, infinite peace of mind.

```
pip install toxtox
```

Think of it as multiverse testing — if your code can survive across dimensions (read: versions), it can survive production.

### 7. `pre-commit` — Your Personal Gatekeeper

You know that one teammate who commits print statements straight to `main`? Yeah.

`pre-commit` lets you enforce hooks that run automatically before every commit — formatting, linting, type checks, even banning TODOs.

```
pip install pre-commitpre-commit install
```

> It’s like giving your repo a bouncer. No nonsense gets in.

### 8. `pdbpp` — Debugging, but Without the Pain

Standard `pdb` works… but it feels like using Notepad when you’ve got VS Code installed.

`pdbpp` is a drop-in replacement that adds syntax highlighting, sticky mode (see code around the current frame), and smarter navigation.

```
pip install pdbpppython -m pdb your_script.py
```

> Once you try it, you’ll wonder how you ever lived without it.

***

If you enjoyed reading this please make sure to give ***50 CLAPS*** and hit ***FOLLOW*** button.

*Thanks for reading :)*

### A message from our Founder

**Hey,** [**Sunil**](https://linkedin.com/in/sunilsandhu) **here.** I wanted to take a moment to thank you for reading until the end and for being a part of this community.

Did you know that our team run these publications as a volunteer effort to over 3.5m monthly readers? **We don’t receive any funding, we do this to support the community. ❤️**

If you want to show some love, please take a moment to **follow me on** [**LinkedIn**](https://linkedin.com/in/sunilsandhu)**,** [**TikTok**](https://tiktok.com/@messyfounder), [**Instagram**](https://instagram.com/sunilsandhu). You can also subscribe to our [**weekly newsletter**](https://newsletter.plainenglish.io/).

<img src="https://cdn-images-1.medium.com/max/2400/0*YJtcMmB1bLvJLFGm" alt="">
If you’ve been building software long enough, you know the real horror story isn’t the bug you can’t fix — it’s the one you don’t even know exists. Nothing tanks confidence in a project faster than flaky tests, untraceable crashes, and deployment chaos.
The good news? Python has a treasure chest of tools designed to prevent your next project from becoming a dumpster fire. And I don’t mean the usual suspects like <code>pytest</code> or <code>virtualenv</code>. I’m talking about tools that even seasoned developers rarely touch — the kind that’ll have you catching issues before they escalate, automating sanity checks, and sleeping like an actual human being at night.
Let’s dive in.
<h3 id="1-banditsecurity-checks-you-wish-you-ranearlier">1. <code>bandit</code> — Security Checks You Wish You Ran Earlier</h3>
Imagine shipping code only to realize you hardcoded credentials in a forgotten utility file. Nightmare fuel.
<code>bandit</code> scans your Python codebase for common security issues: weak cryptography, unsafe function usage, and other “I’ll fix it later” mistakes.
<pre><code class="code-highlight">pip install banditbandit -r your_project/
</code></pre>
<blockquote>
Tip: Run it as part of your CI pipeline. Because nothing feels worse than finding out from a Hacker News post that your app leaked an API key.
</blockquote>
<h3 id="2-py-spyyour-projects-black-boxrecorder">2. <code>py-spy</code> — Your Project’s Black Box Recorder</h3>
Performance bugs are the trickiest. They only show up when you’re demoing to your boss, right?
<code>py-spy</code> is a sampling profiler that lets you peek into what your Python process is doing without restarting it. No code changes, no restarts, no excuses.
<pre><code class="code-highlight">pip install py-spypy-spy top --pid &#x3C;your_pid>
</code></pre>
<blockquote>
Fact: NASA has been using profiler tools like this for decades — because when you’re running code on a rover 200 million miles away, debugging isn’t really an option.
</blockquote>
<h3 id="3-hypothesisthe-test-generator-you-didnt-know-youneeded">3. <code>hypothesis</code> — The Test Generator You Didn’t Know You Needed</h3>
We humans write boring tests. We check the happy path, maybe throw in a couple of edge cases. But what about the edge cases of edge cases?
Enter <code>hypothesis</code>. It generates thousands of randomized test inputs, automatically exploring corners of your code you’d never manually think of.
<pre><code class="code-highlight">from hypothesis import given, strategies as st@given(st.lists(st.integers()))def test_sorting(nums): assert sorted(nums) == sorted(sorted(nums))
</code></pre>
This has caught real-world bugs in libraries maintained by teams of PhDs. If they can miss things, so can you.
<h3 id="4-safetydependency-audit-on-autopilot">4. <code>safety</code> — Dependency Audit on Autopilot</h3>
Your code is only as safe as your dependencies — and let’s face it, half of PyPI is one bad day away from CVEs.
<blockquote>
<code>safety</code> checks your installed packages against a database of known vulnerabilities.
</blockquote>
<pre><code class="code-highlight">pip install safetysafety check
</code></pre>
Run this once and you’ll probably discover that your favorite library hasn’t patched a critical issue since 2019.
<h3 id="5-structloglogging-thats-actuallyreadable">5. <code>structlog</code> — Logging That’s Actually Readable</h3>
Default Python logs? About as decipherable as hieroglyphics.
<code>structlog</code> lets you log in structured JSON, making it painless to search, filter, and debug in production. Pair it with tools like Elasticsearch or Loki, and suddenly tracing that elusive bug isn’t a guessing game anymore.
<pre><code class="code-highlight">import structloglog = structlog.get_logger()log.info("user_logged_in", user_id=123, feature="checkout")
</code></pre>
<blockquote>
Because the only thing worse than a production error is a production error with cryptic logs.
</blockquote>
<h3 id="6-toxtesting-in-parallel-universes">6. <code>tox</code> — Testing in Parallel Universes</h3>
You tested locally on Python 3.10. CI runs on 3.9. Production is still on 3.8 because “upgrades break stuff.” Sound familiar?
<code>tox</code> runs your test suite across multiple Python environments automatically. One config file, infinite peace of mind.
<pre><code class="code-highlight">pip install toxtox
</code></pre>
Think of it as multiverse testing — if your code can survive across dimensions (read: versions), it can survive production.
<h3 id="7-pre-commityour-personal-gatekeeper">7. <code>pre-commit</code> — Your Personal Gatekeeper</h3>
You know that one teammate who commits print statements straight to <code>main</code>? Yeah.
<code>pre-commit</code> lets you enforce hooks that run automatically before every commit — formatting, linting, type checks, even banning TODOs.
<pre><code class="code-highlight">pip install pre-commitpre-commit install
</code></pre>
<blockquote>
It’s like giving your repo a bouncer. No nonsense gets in.
</blockquote>
<h3 id="8-pdbppdebugging-but-without-thepain">8. <code>pdbpp</code> — Debugging, but Without the Pain</h3>
Standard <code>pdb</code> works… but it feels like using Notepad when you’ve got VS Code installed.
<code>pdbpp</code> is a drop-in replacement that adds syntax highlighting, sticky mode (see code around the current frame), and smarter navigation.
<pre><code class="code-highlight">pip install pdbpppython -m pdb your_script.py
</code></pre>
<blockquote>
Once you try it, you’ll wonder how you ever lived without it.
</blockquote>
<hr>
If you enjoyed reading this please make sure to give 50 CLAPS and hit FOLLOW button.
Thanks for reading :)
<h3 id="a-message-from-ourfounder">A message from our Founder</h3>
Hey, <a href="https://linkedin.com/in/sunilsandhu">Sunil</a> here. I wanted to take a moment to thank you for reading until the end and for being a part of this community.
Did you know that our team run these publications as a volunteer effort to over 3.5m monthly readers? We don’t receive any funding, we do this to support the community. ❤️
If you want to show some love, please take a moment to follow me on <a href="https://linkedin.com/in/sunilsandhu">LinkedIn</a>, <a href="https://tiktok.com/@messyfounder">TikTok</a>, <a href="https://instagram.com/sunilsandhu">Instagram</a>. You can also subscribe to our <a href="https://newsletter.plainenglish.io/">weekly newsletter</a>.

 8 Python Tools That Stop Projects From Breaking

 Fewer fires, more shipping.

40+ Genius Ways to Make Money from AI with Gemini 2.0: A Comprehensive Guide

![](https://cdn-images-1.medium.com/max/2600/0*5AYlaizIxHftu3oE)

Photo by [Boitumelo Phetla](https://unsplash.com/@writecodenow?utm_source=medium\&utm_medium=referral) on [Unsplash](https://unsplash.com?utm_source=medium\&utm_medium=referral)

Today we will learn how to send desktop notifications with Python. For this we will just need a computer with Python installed.

### Packages and Setup

You’ll need Plyer’s notification for this project:

```
# In CMD or terminal
``````
pip install plyer
``````
# In project
``````
from plyer import notification
```

You can send notifications by calling the `notify()` function from notification.

It takes four parameters:

`title` The large header text at the top of a notification.

`message` The longer, smaller text where you put more detailed information.

`app_icon` The image that appears next to the title and message.

`timeout` How long the message should show on screen.

If we run it right now, our notification should show up!

![](https://cdn-images-1.medium.com/max/1600/1*Au9m7XZZFQ083Dh3xvy0GQ.png)

**Figure 1:** Notification!

***

> *💡* Speed up your blog creation with [***DifferAI***](https://differ.blog/differ-ai).

> Available for ***free******* exclusively on the ***free and open blogging platform,*** [***Differ***](https://differ.blog/)**.**

[**Try DifferAI — Your Free Writing Assistant**
*DifferAI is your writing co-pilot — seamlessly integrated within Differ’s text editor. Powered by an LLM specifically built for writers and bloggers.*&#x64;iffer.blog](https://differ.blog/differ-ai "https://differ.blog/differ-ai")

***

### Improving the design

Let’s add an image. All we have to do for this part is specify the file path of the image!

***Note:** You have to use a `.ico` file.*

```
app_icon = "image.ico"
```

![](https://cdn-images-1.medium.com/max/1600/1*qzaAdPa20Svgt6j_5oaxtA.png)

**Figure 2:** Notification with image!

### Delay

You can enforce a delay by using Python’s `time.sleep()`:

And it shows up every 30 seconds!

![](https://cdn-images-1.medium.com/max/1600/1*qzaAdPa20Svgt6j_5oaxtA.png)

**Figure 3:** Notification with delay!

### 24/7 365

You can run this file forever with `pythonw`.

`cd` into the directory your `.py` file is, and then execute the command below

```
pythonw filename.py
```

It should execute without any errors.

We can confirm it works by going to our task manager and see the active tasks.

![](https://cdn-images-1.medium.com/max/1600/1*bikEtLQFg6b2vDCD6xHUKQ.png)

**Figure 4:** Python file running in background.

To kill the process, end the task.

If that doesn’t work, and you only have one `pythonw` task running, you can use this command.

```
taskkill /IM pythonw.exe /F
```

### Conclusion

I hope you enjoyed reading this, and that you find a good use for this tool! If you have any questions, suggestions, or general feedback, put it in the comments! Thanks!

<img src="https://cdn-images-1.medium.com/max/2600/0*5AYlaizIxHftu3oE" alt="">
Photo by <a href="https://unsplash.com/@writecodenow?utm_source=medium&#x26;utm_medium=referral">Boitumelo Phetla</a> on <a href="https://unsplash.com?utm_source=medium&#x26;utm_medium=referral">Unsplash</a>
Today we will learn how to send desktop notifications with Python. For this we will just need a computer with Python installed.
<h3 id="packages-andsetup">Packages and Setup</h3>
You’ll need Plyer’s notification for this project:
<pre><code class="code-highlight"># In CMD or terminal
</code></pre>
pip install plyer
<pre><code class="code-highlight"># In project
</code></pre>
from plyer import notification
<pre><code class="code-highlight">
You can send notifications by calling the `notify()` function from notification.

It takes four parameters:

`title` The large header text at the top of a notification.

`message` The longer, smaller text where you put more detailed information.

`app_icon` The image that appears next to the title and message.

`timeout` How long the message should show on screen.

If we run it right now, our notification should show up!

![](https://cdn-images-1.medium.com/max/1600/1*Au9m7XZZFQ083Dh3xvy0GQ.png)

**Figure 1:** Notification!

***

> *💡* Speed up your blog creation with [***DifferAI***](https://differ.blog/differ-ai).

> Available for ***free******* exclusively on the ***free and open blogging platform,*** [***Differ***](https://differ.blog/)**.**

[**Try DifferAI — Your Free Writing Assistant**
*DifferAI is your writing co-pilot — seamlessly integrated within Differ’s text editor. Powered by an LLM specifically built for writers and bloggers.*&#x26;#x64;iffer.blog](https://differ.blog/differ-ai "https://differ.blog/differ-ai")

***

### Improving the design

Let’s add an image. All we have to do for this part is specify the file path of the image!

***Note:** You have to use a `.ico` file.*

</code></pre>
app_icon = "image.ico"
<pre><code class="code-highlight">
![](https://cdn-images-1.medium.com/max/1600/1*qzaAdPa20Svgt6j_5oaxtA.png)

**Figure 2:** Notification with image!

### Delay

You can enforce a delay by using Python’s `time.sleep()`:

And it shows up every 30 seconds!

![](https://cdn-images-1.medium.com/max/1600/1*qzaAdPa20Svgt6j_5oaxtA.png)

**Figure 3:** Notification with delay!

### 24/7 365

You can run this file forever with `pythonw`.

`cd` into the directory your `.py` file is, and then execute the command below

</code></pre>
pythonw filename.py
<pre><code class="code-highlight">
It should execute without any errors.

We can confirm it works by going to our task manager and see the active tasks.

![](https://cdn-images-1.medium.com/max/1600/1*bikEtLQFg6b2vDCD6xHUKQ.png)

**Figure 4:** Python file running in background.

To kill the process, end the task.

If that doesn’t work, and you only have one `pythonw` task running, you can use this command.

</code></pre>
taskkill /IM pythonw.exe /F
<pre><code class="code-highlight">
### Conclusion

I hope you enjoyed reading this, and that you find a good use for this tool! If you have any questions, suggestions, or general feedback, put it in the comments! Thanks!
</code></pre>

How to Send Desktop Notifications with Python

No experience required!

![](https://cdn-images-1.medium.com/max/1600/1*W509g44tbDdjsMH1PW55zw.png)
Image: [unsplash](https://images.unsplash.com/photo-1631350397792-8e0c2de5b637?q=80\&w=1170\&auto=format\&fit=crop\&ixlib=rb-4.1.0\&ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D)

Hackathon prizes motivate developers and reward effort.

And when choosing prize items, thoughtful swag wins because it speaks your brand and stays useful long after the event ends. Portable gear makes travel easy. Sustainable materials connect with people who care about impact.

So, what kind of branded items do participants actually keep?

Keep reading for ideas that work.

## 1. Power Banks that Save the Day

Developers rely on their devices nonstop during hackathons. Phones, tablets, and laptops drain fast under heavy use.

A compact power bank keeps the work going without hunting for outlets. Consider quick-charge ports, multiple outputs, and durable builds. Add a clean company logo, and it becomes both tool and keepsake.

## 2. Customizable Laptop Backpacks Built to Last

Developers carry a lot, from laptops to chargers to snacks. A sturdy bag keeps everything organized and ready. Many event hosts buy[ personalized backpacks](https://www.successories.com/promotional-products/custom-bags/backpacks/) that participants actually use later, even when running errands. They hold essential gear, look good, and can feature quotes, art, or subtle company branding.

## 3. Reusable Bottles for Everyday Use

Long hours need steady hydration, and disposable cups never last. A durable, reusable bottle fits a developer’s workflow easily. Stainless steel or BPA-free plastic works best. Choose options with insulation, a wide mouth, and easy cleaning. The swag is practical, sustainable, and stays useful long after the hackathon wraps up.

## 4. Hoodies and Socks Worth Packing

Call it a stereotype, but there’s something about techies and a love for hoodies. They bring comfort during long coding hours and chilly event halls. High-quality fabric and clean stitching matter. Pair that with soft socks, and you give developers gear they actually wear beyond the hackathon weekend.

## 5. Cable Kits and Keycap Sets Developers Love

Few things slow coding more than missing cables or messy cords. A neat cable kit solves that instantly. Add braided cords, adapters, and magnetic ties for a pro feel. Custom keycap sets, meanwhile, bring personality to keyboards. They’re small gifts developers keep instead of leaving behind.

## 6. Notebooks that Actually Get Used

Everyone jots something down every once in a while, right? Quick ideas, sketches, or snippets of code still land best on paper. A sturdy notebook with thick pages and smooth binding feels good to use. Add minimalist branding or grid pages, and developers will keep it handy for months.

## 7. Privacy Covers for Security-Minded Hackers

Not everyone thinks about webcam security until someone brings it up. A simple privacy cover shows attention to detail and respect for digital safety. It speaks "[Happy Hackthoning](https://javascript.plainenglish.io/happy-hackathoning-dos-don-ts-d86307896ad0)". It slides smoothly, sticks well, and costs little. Give these out, and you might even attract participants who were hesitant to attend before.

## 8. Enamel Pins that Spark Conversation

Small details can say a lot about identity. Enamel pins let developers show off their humor, passion, or favorite language icon. Light and collectible, they’re easy to swap. Attach them to jackets or laptop sleeves, and they become tiny badges of community and shared experience.

## 9. NFC Cards for Smart Networking

Paper business cards feel dated in tech spaces. NFC cards replace them with a tap that instantly shares profiles or portfolios. They aren’t just sleek and durable, they’re easy to update digitally.

Plus, developers appreciate tools that make networking effortless. These cards often spark real conversations that continue after the event.

## Endnote

Thoughtful swag carries meaning long after an event ends. It builds connection, not clutter. For hackathons, the trick is to choose items that last, feel good to use, and tell your story every time they’re picked up.

<img src="https://cdn-images-1.medium.com/max/1600/1*W509g44tbDdjsMH1PW55zw.png" alt="">
Image: <a href="https://images.unsplash.com/photo-1631350397792-8e0c2de5b637?q=80&#x26;w=1170&#x26;auto=format&#x26;fit=crop&#x26;ixlib=rb-4.1.0&#x26;ixid=M3wxMjA3fDB8MHxwaG90by1wYWdlfHx8fGVufDB8fHx8fA%3D%3D">unsplash</a>
Hackathon prizes motivate developers and reward effort.
And when choosing prize items, thoughtful swag wins because it speaks your brand and stays useful long after the event ends. Portable gear makes travel easy. Sustainable materials connect with people who care about impact.
So, what kind of branded items do participants actually keep?
Keep reading for ideas that work.
<h2 id="1-power-banks-that-save-the-day">1. Power Banks that Save the Day</h2>
Developers rely on their devices nonstop during hackathons. Phones, tablets, and laptops drain fast under heavy use.
A compact power bank keeps the work going without hunting for outlets. Consider quick-charge ports, multiple outputs, and durable builds. Add a clean company logo, and it becomes both tool and keepsake.
<h2 id="2-customizable-laptop-backpacks-built-to-last">2. Customizable Laptop Backpacks Built to Last</h2>
Developers carry a lot, from laptops to chargers to snacks. A sturdy bag keeps everything organized and ready. Many event hosts buy<a href="https://www.successories.com/promotional-products/custom-bags/backpacks/"> personalized backpacks</a> that participants actually use later, even when running errands. They hold essential gear, look good, and can feature quotes, art, or subtle company branding.
<h2 id="3-reusable-bottles-for-everyday-use">3. Reusable Bottles for Everyday Use</h2>
Long hours need steady hydration, and disposable cups never last. A durable, reusable bottle fits a developer’s workflow easily. Stainless steel or BPA-free plastic works best. Choose options with insulation, a wide mouth, and easy cleaning. The swag is practical, sustainable, and stays useful long after the hackathon wraps up.
<h2 id="4-hoodies-and-socks-worth-packing">4. Hoodies and Socks Worth Packing</h2>
Call it a stereotype, but there’s something about techies and a love for hoodies. They bring comfort during long coding hours and chilly event halls. High-quality fabric and clean stitching matter. Pair that with soft socks, and you give developers gear they actually wear beyond the hackathon weekend.
<h2 id="5-cable-kits-and-keycap-sets-developers-love">5. Cable Kits and Keycap Sets Developers Love</h2>
Few things slow coding more than missing cables or messy cords. A neat cable kit solves that instantly. Add braided cords, adapters, and magnetic ties for a pro feel. Custom keycap sets, meanwhile, bring personality to keyboards. They’re small gifts developers keep instead of leaving behind.
<h2 id="6-notebooks-that-actually-get-used">6. Notebooks that Actually Get Used</h2>
Everyone jots something down every once in a while, right? Quick ideas, sketches, or snippets of code still land best on paper. A sturdy notebook with thick pages and smooth binding feels good to use. Add minimalist branding or grid pages, and developers will keep it handy for months.
<h2 id="7-privacy-covers-for-security-minded-hackers">7. Privacy Covers for Security-Minded Hackers</h2>
Not everyone thinks about webcam security until someone brings it up. A simple privacy cover shows attention to detail and respect for digital safety. It speaks "<a href="https://javascript.plainenglish.io/happy-hackathoning-dos-don-ts-d86307896ad0">Happy Hackthoning</a>". It slides smoothly, sticks well, and costs little. Give these out, and you might even attract participants who were hesitant to attend before.
<h2 id="8-enamel-pins-that-spark-conversation">8. Enamel Pins that Spark Conversation</h2>
Small details can say a lot about identity. Enamel pins let developers show off their humor, passion, or favorite language icon. Light and collectible, they’re easy to swap. Attach them to jackets or laptop sleeves, and they become tiny badges of community and shared experience.
<h2 id="9-nfc-cards-for-smart-networking">9. NFC Cards for Smart Networking</h2>
Paper business cards feel dated in tech spaces. NFC cards replace them with a tap that instantly shares profiles or portfolios. They aren’t just sleek and durable, they’re easy to update digitally.
Plus, developers appreciate tools that make networking effortless. These cards often spark real conversations that continue after the event.
<h2 id="endnote">Endnote</h2>
Thoughtful swag carries meaning long after an event ends. It builds connection, not clutter. For hackathons, the trick is to choose items that last, feel good to use, and tell your story every time they’re picked up.

9 Hackathon Swag Ideas Developers Actually Keep

![](https://cdn-images-1.medium.com/max/2400/0*EhjRACvCtAJUv8fD)

Photo by [Hitesh Choudhary](https://unsplash.com/@hiteshchoudhary?utm_source=medium\&utm_medium=referral) on [Unsplash](https://unsplash.com?utm_source=medium\&utm_medium=referral)

### Ever wanted to have some real fun with Chat GPT? Not just boring emails or formal writing… I’m talking about *crazy*, *fun*, and *mind-blowing* prompts that you can copy-paste and watch the magic happen.

Whether you’re chilling in class, zoning out after homework, or just wanna see how far AI can go — these are for **you**.

Here’s what this blog isn’t:

* No dry productivity stuff (that’s for another day)
* No long explanations (who’s got time for that?)
* Just **plug, play, and enjoy**

So here it is…

***

### 🚀 THE 5 FUN PROMPTS

### 🤖 1. “Make Me a Movie Villain”

> *I want you to write my origin story as a supervillain. I used to be a normal student, but one tragic/frustrating/random event changed me. Now I’m feared across the world. Give me:* A villain name My backstory My signature power My dramatic goal (take over Earth? Cancel Mondays?). My catchphrase. How the world plans to stop me
>  Make it dark, dramatic, and a little funny — like a Marvel villain with a TikTok addiction.

***

### 🎤 2. “Rap My Life”

> *Write a rap about my life. Use clever rhymes, punchlines, and savage flow. I want it to sound like Kendrick, but about me. Include:.* My grind. My struggles. My goals. Random flexes (even if they’re fake). A bar that ends with something totally unexpected (like…toasters or aliens)

***

### 😂 3. “Roast Me Like You Know Me”

> *Roast me like you’re my best friend who’s tired of my excuses. Be brutally honest but hilarious. Mix school, productivity, and anything else that makes me look like a lazy overthinker who drinks 3 glasses of water and calls it “hydration discipline.”* World”

***

> *Pretend I just became the supreme leader of Earth. Write a dramatic announcement to the people of the world where I reveal:* 5 insane new laws I’m passing. What happens if people break them. My official title (make it sound royal but slightly unhinged). A final line that sounds like something from a dystopian Netflix show
>  Go wild with this one. Humor + drama.

***

### **🛠️ 5. “Useless Invention Pitch”**

> ***Pretend you’re on Shark Tank. Pitch the dumbest, most useless gadget in the world. It should have:*** **A ridiculous name. A fake function. A dramatic backstory. Over-the-top marketing slogans And a reason why “every billionaire secretly owns one”**
>  **Make it sound like the next iPhone, but for something no one actually needs.**

Let me give you a quick cheat code to upgrade the fun:

* **Get creative:** Tweak the prompt a bit and make it yours.
* **Try follow-ups:** Ask ChatGPT “What if…” or “Now make it weird.”
* **Use it with friends:** These are *hilarious* when you try them together.
* **Screenshot the chaos:** Save the best replies — you’ll thank me later.

***

### 💡 Why This Matters (Even If It’s Just for Fun)

Having fun with AI isn’t useless — it’s actually how you *learn* its full potential. You start with jokes, then you start thinking,
 “Wait… can I make it do \_\_ too?”

That’s how all creators start.
 That’s how *you* become a creator.

***

So go ahead, copy these prompts, open ChatGPT, and go nuts.
 And if something wild comes out of it — DM me or drop it in the comments.

**Let’s make AI fun again.**

***

**Krashnav signing off — not to chill, but to grind for skill. 🧠🔥**

### A message from our Founder

**Hey,** [**Sunil**](https://linkedin.com/in/sunilsandhu) **here.** I wanted to take a moment to thank you for reading until the end and for being a part of this community.

Did you know that our team run these publications as a volunteer effort to over 3.5m monthly readers? **We don’t receive any funding, we do this to support the community. ❤️**

If you want to show some love, please take a moment to **follow me on** [**LinkedIn**](https://linkedin.com/in/sunilsandhu)**,** [**TikTok**](https://tiktok.com/@messyfounder), [**Instagram**](https://instagram.com/sunilsandhu). You can also subscribe to our [**weekly newsletter**](https://newsletter.plainenglish.io/).

<img src="https://cdn-images-1.medium.com/max/2400/0*EhjRACvCtAJUv8fD" alt="">
Photo by <a href="https://unsplash.com/@hiteshchoudhary?utm_source=medium&#x26;utm_medium=referral">Hitesh Choudhary</a> on <a href="https://unsplash.com?utm_source=medium&#x26;utm_medium=referral">Unsplash</a>
<h3 id="ever-wanted-to-have-some-real-fun-with-chat-gpt-not-just-boring-emails-or-formal-writing-im-talking-about-crazy-fun-and-mind-blowing-prompts-that-you-can-copy-paste-and-watch-the-magichappen">Ever wanted to have some real fun with Chat GPT? Not just boring emails or formal writing… I’m talking about crazy, fun, and mind-blowing prompts that you can copy-paste and watch the magic happen.</h3>
Whether you’re chilling in class, zoning out after homework, or just wanna see how far AI can go — these are for you.
Here’s what this blog isn’t:
<ul>
<li>No dry productivity stuff (that’s for another day)</li>
<li>No long explanations (who’s got time for that?)</li>
<li>Just plug, play, and enjoy</li>
</ul>
So here it is…
<hr>
<h3 id="-the-5-funprompts">🚀 THE 5 FUN PROMPTS</h3>
<h3 id="-1-make-me-a-movievillain">🤖 1. “Make Me a Movie Villain”</h3>
<blockquote>
I want you to write my origin story as a supervillain. I used to be a normal student, but one tragic/frustrating/random event changed me. Now I’m feared across the world. Give me: A villain name My backstory My signature power My dramatic goal (take over Earth? Cancel Mondays?). My catchphrase. How the world plans to stop me
 Make it dark, dramatic, and a little funny — like a Marvel villain with a TikTok addiction.
</blockquote>
<hr>
<h3 id="-2-rap-mylife">🎤 2. “Rap My Life”</h3>
<blockquote>
Write a rap about my life. Use clever rhymes, punchlines, and savage flow. I want it to sound like Kendrick, but about me. Include:. My grind. My struggles. My goals. Random flexes (even if they’re fake). A bar that ends with something totally unexpected (like…toasters or aliens)
</blockquote>
<hr>
<h3 id="-3-roast-me-like-you-knowme">😂 3. “Roast Me Like You Know Me”</h3>
<blockquote>
Roast me like you’re my best friend who’s tired of my excuses. Be brutally honest but hilarious. Mix school, productivity, and anything else that makes me look like a lazy overthinker who drinks 3 glasses of water and calls it “hydration discipline.” World”
</blockquote>
<hr>
<blockquote>
Pretend I just became the supreme leader of Earth. Write a dramatic announcement to the people of the world where I reveal: 5 insane new laws I’m passing. What happens if people break them. My official title (make it sound royal but slightly unhinged). A final line that sounds like something from a dystopian Netflix show
 Go wild with this one. Humor + drama.
</blockquote>
<hr>
<h3 id="️-5-useless-invention-pitch">🛠️ 5. “Useless Invention Pitch”</h3>
<blockquote>
Pretend you’re on Shark Tank. Pitch the dumbest, most useless gadget in the world. It should have: A ridiculous name. A fake function. A dramatic backstory. Over-the-top marketing slogans And a reason why “every billionaire secretly owns one”
 Make it sound like the next iPhone, but for something no one actually needs.
</blockquote>
Let me give you a quick cheat code to upgrade the fun:
<ul>
<li>Get creative: Tweak the prompt a bit and make it yours.</li>
<li>Try follow-ups: Ask ChatGPT “What if…” or “Now make it weird.”</li>
<li>Use it with friends: These are hilarious when you try them together.</li>
<li>Screenshot the chaos: Save the best replies — you’ll thank me later.</li>
</ul>
<hr>
<h3 id="-why-this-matters-even-if-its-just-forfun">💡 Why This Matters (Even If It’s Just for Fun)</h3>
Having fun with AI isn’t useless — it’s actually how you learn its full potential. You start with jokes, then you start thinking,
 “Wait… can I make it do __ too?”
That’s how all creators start.
 That’s how you become a creator.
<hr>
So go ahead, copy these prompts, open ChatGPT, and go nuts.
 And if something wild comes out of it — DM me or drop it in the comments.
Let’s make AI fun again.
<hr>
Krashnav signing off — not to chill, but to grind for skill. 🧠🔥
<h3 id="a-message-from-ourfounder">A message from our Founder</h3>
Hey, <a href="https://linkedin.com/in/sunilsandhu">Sunil</a> here. I wanted to take a moment to thank you for reading until the end and for being a part of this community.
Did you know that our team run these publications as a volunteer effort to over 3.5m monthly readers? We don’t receive any funding, we do this to support the community. ❤️
If you want to show some love, please take a moment to follow me on <a href="https://linkedin.com/in/sunilsandhu">LinkedIn</a>, <a href="https://tiktok.com/@messyfounder">TikTok</a>, <a href="https://instagram.com/sunilsandhu">Instagram</a>. You can also subscribe to our <a href="https://newsletter.plainenglish.io/">weekly newsletter</a>.

5 Chat GPT Prompts You Can Plug, Play, and Go Crazy With

![](https://cdn-images-1.medium.com/max/1600/0*zmdmEhU288au9mft.jpg)

There was a time when sports betting only occurred in sports arenas and on playing fields. However, nowadays, most bets are placed through web or mobile applications. Thanks to smartphones and the widespread availability of the internet, we can now place bets, regardless of where we are or what we're doing at the moment. What can you do to make your app the most popular and functional? Consider incorporating the best features for sports betting applications.

## Sports betting applications – what are they?

Sports betting applications, also known as **sportsbook or betting apps**, are mobile or web-based applications that allow users to place bets on various sports events and outcomes.

These applications provide a platform for users to wager money on sports games, matches, or races. They offer a wide range of betting options, such as **predicting the winner, point spreads, over/under totals, and more**. You can use a [sports betting software development company](https://softwaremind.com/services/software-for-sport-betting-industry/) to improve user experience and increase your app's effectiveness.

## Crucial features of sports betting apps for users

**The crucial aspect is the intuitiveness of your app.** Navigation should be fast and easy. The speed of the application is also significant. Only a well-functioning application will provide users with the comfort of placing bets, which is particularly important for live betting. Additionally, **some functionalities can make your application even more attractive to users**

### Quick Login

Users like to log in quickly, which is crucial in the case of live events. A nice feature of apps is the **ability to log in with an email or Facebook account**. The method of logging into the mobile app should also be as fast as possible. A good way to achieve this is by **logging in with the user's fingerprint.**

### Linking a payment card to a user account

**Connecting a credit or debit card to a user account speeds up payments.** This way, users don't have to waste time confirming payments or logging into their bank accounts to transfer funds needed to place a bet. It's quick and convenient.

### Notifications

A seemingly obvious but more significant aspect is what should be covered by notifications. Indeed, users should receive **notifications about the final results of the game**, but they can also be informed about **changes in scores**. Additionally, the app can send notifications about **ongoing events similar to those in which the user participated or those in which they are interested in taking part.**

### Transmissions

**The most thrilling aspect of placing bets is waiting for the win and tracking results.** The best sports betting apps allow users to watch matches or competitions, which is why your software should enable that feature. With **live streaming**, users can experience the excitement of sports, even if they are just commuting back home from work by bus or train. **Live streams provide users with the best experience throughout the entire betting process.**

### Tools helpful in placing bets

Many tools can be helpful in placing bets. **Statistics, results from previous competitions, or comparisons can be helpful in making accurate decisions**. Your sports betting software should allow users to utilize them by sharing it in your app.

### Live chats

Chats can be useful for two reasons. The first reason is to **contact customer service if the user encounters any problems.** Thanks to this, issues can be resolved promptly, allowing users to participate in betting without major disruptions. Another use of the chat is to **communicate with other players to discuss game results and bets.**

Many interesting features engage users of betting apps. Choose the best software functionalities for sports betting companies and implement them in your business.

<img src="https://cdn-images-1.medium.com/max/1600/0*zmdmEhU288au9mft.jpg" alt="">
There was a time when sports betting only occurred in sports arenas and on playing fields. However, nowadays, most bets are placed through web or mobile applications. Thanks to smartphones and the widespread availability of the internet, we can now place bets, regardless of where we are or what we're doing at the moment. What can you do to make your app the most popular and functional? Consider incorporating the best features for sports betting applications.
<h2 id="sports-betting-applications--what-are-they">Sports betting applications – what are they?</h2>
Sports betting applications, also known as sportsbook or betting apps, are mobile or web-based applications that allow users to place bets on various sports events and outcomes.
These applications provide a platform for users to wager money on sports games, matches, or races. They offer a wide range of betting options, such as predicting the winner, point spreads, over/under totals, and more. You can use a <a href="https://softwaremind.com/services/software-for-sport-betting-industry/">sports betting software development company</a> to improve user experience and increase your app's effectiveness.
<h2 id="crucial-features-of-sports-betting-apps-for-users">Crucial features of sports betting apps for users</h2>
The crucial aspect is the intuitiveness of your app. Navigation should be fast and easy. The speed of the application is also significant. Only a well-functioning application will provide users with the comfort of placing bets, which is particularly important for live betting. Additionally, some functionalities can make your application even more attractive to users
<h3 id="quick-login">Quick Login</h3>
Users like to log in quickly, which is crucial in the case of live events. A nice feature of apps is the ability to log in with an email or Facebook account. The method of logging into the mobile app should also be as fast as possible. A good way to achieve this is by logging in with the user's fingerprint.
<h3 id="linking-a-payment-card-to-a-user-account">Linking a payment card to a user account</h3>
Connecting a credit or debit card to a user account speeds up payments. This way, users don't have to waste time confirming payments or logging into their bank accounts to transfer funds needed to place a bet. It's quick and convenient.
<h3 id="notifications">Notifications</h3>
A seemingly obvious but more significant aspect is what should be covered by notifications. Indeed, users should receive notifications about the final results of the game, but they can also be informed about changes in scores. Additionally, the app can send notifications about ongoing events similar to those in which the user participated or those in which they are interested in taking part.
<h3 id="transmissions">Transmissions</h3>
The most thrilling aspect of placing bets is waiting for the win and tracking results. The best sports betting apps allow users to watch matches or competitions, which is why your software should enable that feature. With live streaming, users can experience the excitement of sports, even if they are just commuting back home from work by bus or train. Live streams provide users with the best experience throughout the entire betting process.
<h3 id="tools-helpful-in-placing-bets">Tools helpful in placing bets</h3>
Many tools can be helpful in placing bets. Statistics, results from previous competitions, or comparisons can be helpful in making accurate decisions. Your sports betting software should allow users to utilize them by sharing it in your app.
<h3 id="live-chats">Live chats</h3>
Chats can be useful for two reasons. The first reason is to contact customer service if the user encounters any problems. Thanks to this, issues can be resolved promptly, allowing users to participate in betting without major disruptions. Another use of the chat is to communicate with other players to discuss game results and bets.
Many interesting features engage users of betting apps. Choose the best software functionalities for sports betting companies and implement them in your business.

Software functionalities for sports betting companies – enhance your customer experience

 Top 8 LLM + RAG Projects for your AI Portfolio 2025

Embedded finance has grown into a core component of modern digital platforms. Marketplaces, ride-hailing apps, telecom operators, SaaS tools, and retail ecosystems are increasingly adding financial features directly into their user journeys. At the centre of this shift are core banking APIs, which expose essential banking logic in a format that non-financial companies can integrate into their products.

These APIs offer direct access to accounts, balances, ledgers, cards, payouts, fees, and compliance workflows. Businesses can embed financial services without building complex banking infrastructure, maintaining a regulated stack, or operating a bank. The technical and regulatory complexity remains on the provider side, while companies focus on the customer experience.

## What Is a Core Banking API in an Embedded Finance Model?

A [core banking API](https://sdk.finance/solutions/core-banking-software-solution/) serves as the interface for the fundamental building blocks of banking:

* creating and managing accounts
* maintaining multi-currency balances
* executing transactions with real-time ledger entries
* issuing and managing cards
* running transfers and payouts
* applying fee and limit rules
* performing KYC/AML checks

Embedded finance brings this functionality into **non-financial digital products**, enabling:

* digital wallets in marketplaces
* driver payouts and cards in mobility platforms
* embedded credit at checkout
* accounts and payments inside SaaS workflows
* loyalty cards or branded financial products for retail

The API abstracts risk controls, settlement logic, reconciliation, and regulatory checks, allowing businesses to deliver financial operations through a simple technical integration.

## Why Core Banking APIs Matter for Embedded Finance

### **1. Rapid time-to-market**

Companies can deploy financial features in weeks or months rather than building multi-year banking cores.

### **2. Modular, mix-and-match capabilities**

Not every product needs a full banking stack. APIs allow selective integration: accounts, cards, AML, wallets, payouts, or settlements.

### **3. Rich transactional insights**

API-driven data enables personalisation, spend analysis, risk scoring, and improved underwriting inside the existing product flow.

### **4. Built-in compliance and security**

KYC, AML, encryption, audit trails, and secure accounting are included at the infrastructure level.

### **5. Stable, consistent financial logic**

The ledger-driven backend ensures accuracy, consistency, and traceability, all essential for embedded financial operations.

## How Core Banking APIs Enable Embedded Finance

Core banking APIs sit between the regulated financial infrastructure and the digital product that needs to embed financial operations.

A simplified sequence looks like this:

1. A user interacts with a platform (marketplace, mobility app, SaaS system).
2. The platform sends an API request (account creation, payout, card issuing, identity verification).
3. The core banking provider executes the request by:
 * applying compliance rules
 * writing to the ledger
 * communicating with partner banks or card schemes
4. The provider returns a structured response that the product uses in real time.

This approach enables embedded finance without requiring companies to manage or build regulated systems themselves.

## Core Banking API Vendors for Embedded Finance

The market offers numerous providers, yet the following ones stand out as the most trustworthy for embedded finance use cases.

### **SDK.finance**

SDK.finance provides an API-first core banking and ledger platform designed specifically for embedding financial capabilities into digital products. Its embedding-first design, modular architecture, and modern technology stack support wallets, payouts, card issuing, KYC/AML, and PSP workflows. The platform is **PCI-DSS certified** and is available as a PaaS or as a full source code licence for complete ownership.

### **Unit**

Unit is a Banking-as-a-Service provider offering accounts, cards, lending, and compliance flows. It focuses on fast implementation and developer-friendly tooling, particularly for fintechs and consumer apps operating in the American market.

### **Railsr**

Railsr offers embedded finance capabilities geared toward consumer applications, including payments, card issuing, and rewards. The platform is built around fast deployment and user engagement through loyalty and card programmes.

### **Mambu**

Mambu is a composable cloud banking engine commonly used for lending, deposits, and regulated financial products. Its modular APIs also support embedded finance layers for platforms that require bank-grade product structures.

### **Finxact**

Finxact provides an API-driven cloud core used by banks and enterprise platforms. Although often adopted in institutional contexts, it fits embedded finance cases requiring full-feature product creation and high scalability.

## Short Vendor Comparison Table

***

**Vendor: SDK.finance**

**Embedded Finance Use Cases:** Wallets, accounts, payouts, card issuing, PSP rails, crypto-to-fiat, super apps, marketplaces

**Delivery Model:** SaaS or full source code licence

**Notable Strengths:** Fast launch, embedding-first design, modern stack, PCI-DSS certified, high-performance ledger

***

**Vendor: Unit**

**Embedded Finance Use Cases:** Accounts, cards, compliance for US-focused apps

**Delivery Model:** SaaS BaaS

**Notable Strengths:** Fast launch, unified compliance, strong developer tooling

***

**Vendor: Railsr**

**Embedded Finance Use Cases:** Embedded cards, payments, rewards

**Delivery Model:** SaaS BaaS

**Notable Strengths:** Rewards engine, flexible card programmes

***

**Vendor: Mambu**

**Embedded Finance Use Cases:** Lending, deposits, regulated account products

**Delivery Model:** SaaS

**Notable Strengths:** Composable architecture, global reach

***

**Vendor: Finxact**

**Embedded Finance Use Cases:** Full banking capabilities for enterprise embedded finance

**Delivery Model:** SaaS cloud core

**Notable Strengths:** Scalability, configurable product engine

***

Core Banking APIs are now the backbone of embedded finance. They give digital platforms direct access to reliable financial operations without requiring them to manage the underlying banking infrastructure. Through these APIs, companies can plug in accounts, wallets, payouts, card programmes, compliance flows, and other financial features while maintaining a clear focus on product experience.

Vendors differ in approach: some prioritise rapid deployment for consumer apps, while others offer deeper banking capabilities for enterprise platforms. SDK.finance stands out with its embedding-first design, modern stack, PCI-DSS certification, and flexible deployment options, making it well suited for organisations building robust embedded finance products with long-term control over their core.

Embedded finance has grown into a core component of modern digital platforms. Marketplaces, ride-hailing apps, telecom operators, SaaS tools, and retail ecosystems are increasingly adding financial features directly into their user journeys. At the centre of this shift are core banking APIs, which expose essential banking logic in a format that non-financial companies can integrate into their products.
These APIs offer direct access to accounts, balances, ledgers, cards, payouts, fees, and compliance workflows. Businesses can embed financial services without building complex banking infrastructure, maintaining a regulated stack, or operating a bank. The technical and regulatory complexity remains on the provider side, while companies focus on the customer experience.
<h2 id="what-is-a-core-banking-api-in-an-embedded-finance-model">What Is a Core Banking API in an Embedded Finance Model?</h2>
A <a href="https://sdk.finance/solutions/core-banking-software-solution/">core banking API</a> serves as the interface for the fundamental building blocks of banking:
<ul>
<li>creating and managing accounts</li>
<li>maintaining multi-currency balances</li>
<li>executing transactions with real-time ledger entries</li>
<li>issuing and managing cards</li>
<li>running transfers and payouts</li>
<li>applying fee and limit rules</li>
<li>performing KYC/AML checks</li>
</ul>
Embedded finance brings this functionality into non-financial digital products, enabling:
<ul>
<li>digital wallets in marketplaces</li>
<li>driver payouts and cards in mobility platforms</li>
<li>embedded credit at checkout</li>
<li>accounts and payments inside SaaS workflows</li>
<li>loyalty cards or branded financial products for retail</li>
</ul>
The API abstracts risk controls, settlement logic, reconciliation, and regulatory checks, allowing businesses to deliver financial operations through a simple technical integration.
<h2 id="why-core-banking-apis-matter-for-embedded-finance">Why Core Banking APIs Matter for Embedded Finance</h2>
<h3 id="1-rapid-time-to-market">1. Rapid time-to-market</h3>
Companies can deploy financial features in weeks or months rather than building multi-year banking cores.
<h3 id="2-modular-mix-and-match-capabilities">2. Modular, mix-and-match capabilities</h3>
Not every product needs a full banking stack. APIs allow selective integration: accounts, cards, AML, wallets, payouts, or settlements.
<h3 id="3-rich-transactional-insights">3. Rich transactional insights</h3>
API-driven data enables personalisation, spend analysis, risk scoring, and improved underwriting inside the existing product flow.
<h3 id="4-built-in-compliance-and-security">4. Built-in compliance and security</h3>
KYC, AML, encryption, audit trails, and secure accounting are included at the infrastructure level.
<h3 id="5-stable-consistent-financial-logic">5. Stable, consistent financial logic</h3>
The ledger-driven backend ensures accuracy, consistency, and traceability, all essential for embedded financial operations.
<h2 id="how-core-banking-apis-enable-embedded-finance">How Core Banking APIs Enable Embedded Finance</h2>
Core banking APIs sit between the regulated financial infrastructure and the digital product that needs to embed financial operations.
A simplified sequence looks like this:
<ol>
<li>A user interacts with a platform (marketplace, mobility app, SaaS system).</li>
<li>The platform sends an API request (account creation, payout, card issuing, identity verification).</li>
<li>The core banking provider executes the request by:
<ul>
<li>applying compliance rules</li>
<li>writing to the ledger</li>
<li>communicating with partner banks or card schemes</li>
</ul>
</li>
<li>The provider returns a structured response that the product uses in real time.</li>
</ol>
This approach enables embedded finance without requiring companies to manage or build regulated systems themselves.
<h2 id="core-banking-api-vendors-for-embedded-finance">Core Banking API Vendors for Embedded Finance</h2>
The market offers numerous providers, yet the following ones stand out as the most trustworthy for embedded finance use cases.
<h3 id="sdkfinance">SDK.finance</h3>
SDK.finance provides an API-first core banking and ledger platform designed specifically for embedding financial capabilities into digital products. Its embedding-first design, modular architecture, and modern technology stack support wallets, payouts, card issuing, KYC/AML, and PSP workflows. The platform is PCI-DSS certified and is available as a PaaS or as a full source code licence for complete ownership.
<h3 id="unit">Unit</h3>
Unit is a Banking-as-a-Service provider offering accounts, cards, lending, and compliance flows. It focuses on fast implementation and developer-friendly tooling, particularly for fintechs and consumer apps operating in the American market.
<h3 id="railsr">Railsr</h3>
Railsr offers embedded finance capabilities geared toward consumer applications, including payments, card issuing, and rewards. The platform is built around fast deployment and user engagement through loyalty and card programmes.
<h3 id="mambu">Mambu</h3>
Mambu is a composable cloud banking engine commonly used for lending, deposits, and regulated financial products. Its modular APIs also support embedded finance layers for platforms that require bank-grade product structures.
<h3 id="finxact">Finxact</h3>
Finxact provides an API-driven cloud core used by banks and enterprise platforms. Although often adopted in institutional contexts, it fits embedded finance cases requiring full-feature product creation and high scalability.
<h2 id="short-vendor-comparison-table">Short Vendor Comparison Table</h2>
<hr>
Vendor: SDK.finance
Embedded Finance Use Cases: Wallets, accounts, payouts, card issuing, PSP rails, crypto-to-fiat, super apps, marketplaces
Delivery Model: SaaS or full source code licence
Notable Strengths: Fast launch, embedding-first design, modern stack, PCI-DSS certified, high-performance ledger
<hr>
Vendor: Unit
Embedded Finance Use Cases: Accounts, cards, compliance for US-focused apps
Delivery Model: SaaS BaaS
Notable Strengths: Fast launch, unified compliance, strong developer tooling
<hr>
Vendor: Railsr
Embedded Finance Use Cases: Embedded cards, payments, rewards
Delivery Model: SaaS BaaS
Notable Strengths: Rewards engine, flexible card programmes
<hr>
Vendor: Mambu
Embedded Finance Use Cases: Lending, deposits, regulated account products
Delivery Model: SaaS
Notable Strengths: Composable architecture, global reach
<hr>
Vendor: Finxact
Embedded Finance Use Cases: Full banking capabilities for enterprise embedded finance
Delivery Model: SaaS cloud core
Notable Strengths: Scalability, configurable product engine
<hr>
Core Banking APIs are now the backbone of embedded finance. They give digital platforms direct access to reliable financial operations without requiring them to manage the underlying banking infrastructure. Through these APIs, companies can plug in accounts, wallets, payouts, card programmes, compliance flows, and other financial features while maintaining a clear focus on product experience.
Vendors differ in approach: some prioritise rapid deployment for consumer apps, while others offer deeper banking capabilities for enterprise platforms. SDK.finance stands out with its embedding-first design, modern stack, PCI-DSS certification, and flexible deployment options, making it well suited for organisations building robust embedded finance products with long-term control over their core.

Core Banking API for Embedded Finance: How Digital Products Gain Banking Capabilities Through APIs

![](https://cdn-images-1.medium.com/max/1600/1*XMf_cR1ST_NpeJrjNq0R-w.png)

### The Problem

You’ve built a nice little API using AWS API Gateway - serving as a web-hook endpoint for an external Order Management System.
It takes orders from your web app, saves them to a database, and calls a few downstream services.
It runs through this stack:
 **API Gateway → Lambda → Database**.

It works perfectly on a normal day.

Then one day…

* Your marketing team runs a big sale.
* Or a partner’s integration script gets stuck in a loop.
* Or a new feature upstream pushes thousands of requests by mistake.

Suddenly you’re facing an **event storm -** a huge, unexpected spike in requests hitting your API all at once.

### What’s an Event Storm?

An **event storm** is when the number of incoming requests in a short time is way higher than your system normally handles.
 It’s not a slow increase. It’s a flood.

**Example triggers:**

* Black Friday or Diwali sale on your e-commerce site.
* A cron job gone rogue sending thousands of API calls per second.
* A botnet hammering your public endpoint.
* A sudden surge in user signups after media coverage.

**Quick note on Lambda scaling:** Lambda doesn’t go from 0 → 100K concurrent executions instantly. Each region has a burst concurrency limit (for example \~3000 in `us-east-1`) and then scales up by about 500–1000 per minute.
So when I say “100K requests hit,” I mean the **inbound spike hitting API Gateway**, not the actual concurrency Lambda reached. The scaling ramp-up actually makes the need for a buffer more obvious -SQS can absorb the full burst immediately, while Lambda drains at the pace it can realistically scale to.

### Why It’s a Problem in AWS Lambda

AWS Lambda scales fast, which sounds great until you realise:

* Every Lambda execution counts toward your account concurrency limit.
* If you hit that limit, all other Lambdas in your account may start failing too.
* Downstream systems (like a database) may crash from too many parallel requests.

With API Gateway directly invoking Lambda, an event storm can burn through concurrency in seconds.

### The Safer Approach

We’ll redesign the flow so that:

* API Gateway sends requests to **SQS** instead of Lambda directly.
* If SQS accepts it, API Gateway returns **202 Accepted** with an **ack id** (SQS `MessageId`).

```
HTTP/1.1 202 Accepted{"status":"accepted","messageId":"c1c7...","receivedAt":1735296623123}
```

* Processing happens later via the consumer Lambda.
* Lambda reads from SQS in **controlled batches** and upserts into database
* Concurrency is **capped** so we never overload the database.
* Failed messages go to a **DLQ** for later reprocessing.

This way, the **storm is buffered** in SQS, and you can process at a steady pace without losing data.

### Architecture Overview

1. **API Gateway** -> receives incoming HTTP requests.
2. **SQS (Standard Queue)** -> buffers all requests.
3. **Lambda Consumer ->** pulls messages from SQS in small batches.
4. **DLQ ->** stores failed messages for later replay.

**Don’t forget about caching at the API layer.**
If your API is serving repetitive data (like catalog lookups, product info, or configuration files), you can enable **API Gateway caching**. This stores responses in an in-memory cache so repeated requests don’t even reach Lambda or SQS.
In my case the requests were mostly unique and user-specific, so caching didn’t help much. But for many APIs, caching at API GW can drastically reduce Lambda concurrency and costs.

### Step 0: Recommended Starting Settings

You can tweak these later, but start here:

* **Lambda timeout:** 30s
* **Lambda reserved concurrency (***the max number of concurrent executions this function can ever use*)**:** 50
* **SQS batch size:** 10
* **Max batching window** (*how long Lambda waits to gather more records before invoking the function*)**:** 2s
* **SQS visibility timeout** (*the time a message stays hidden after being picked up, before it can be retried*)**:** 90s
* **DLQ maxReceiveCount (***the number of times a message can fail before being sent to the DLQ*)**:** 5

Why these help:

* Max parallel work = 50 (*Lambda reserved concurrency***)** × 10 (*SQS batch size***)** = **500 messages at once**.
* SQS buffers the rest during a spike.
* Visibility timeout prevents duplicate processing.
* DLQ ensures nothing is lost.

### Step 1: Create SQS and DLQ

**Create DLQ**

```
aws sqs create-queue --queue-name orders-dlq
```

**Create main queue with DLQ attached**

```
DLQ_URL=$(aws sqs get-queue-url --queue-name orders-dlq --query 'QueueUrl' --output text)DLQ_ARN=$(aws sqs get-queue-attributes --queue-url $DLQ_URL --attribute-names QueueArn --query 'Attributes.QueueArn' --output text)aws sqs create-queue \ --queue-name orders \ --attributes '{ "RedrivePolicy":"{\"deadLetterTargetArn\":\"'"$DLQ_ARN"'\",\"maxReceiveCount\":\"5\"}", "VisibilityTimeout":"90" }'
```

### Step 2: Connect API Gateway to SQS

#### Option A: Direct integration

* No Lambda in between.
* API Gateway sends request body directly to SQS.

**IAM role for API Gateway**

```
{ "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": ["sqs:SendMessage"], "Resource": "arn:aws:sqs:<REGION>:<ACCOUNT_ID>:orders" }]}
```

#### Option B: Producer Lambda

If you need validation/auth before pushing to SQS:

```
// producer/index.mjsimport { SQSClient, SendMessageCommand } from "@aws-sdk/client-sqs";const sqs = new SQSClient({});const QUEUE_URL = process.env.QUEUE_URL;export const handler = async (event) => { const body = JSON.parse(event.body || "{}"); if (!body.orderId) { return { statusCode: 400, body: JSON.stringify({ error: "orderId required" }) }; } await sqs.send(new SendMessageCommand({ QueueUrl: QUEUE_URL, MessageBody: JSON.stringify(body) })); return { statusCode: 202, body: JSON.stringify({ status: "accepted" }) };};
```

**API Gateway caching reminder:** If traffic includes repeated requests, enable API Gateway caching. It cuts load before it even reaches SQS or Lambda.

**Step 3: Create the Consumer Lambda**

```
// consumer/index.mjsexport const handler = async (event) => { for (const record of event.Records) { try { const msg = JSON.parse(record.body); await processOrder(msg); } catch (err) { console.error("Failed for messageId", record.messageId, err); throw err; // forces SQS to retry or send to DLQ } }};async function processOrder(msg) { await new Promise(r => setTimeout(r, 150)); // simulate work}
```

**Event Source Mapping**

* Batch size: 10
* Max batching window: 2s

**Reserved concurrency:** 50 (prevents overload)

### Step 3.1: Don’t kill your database connections

One hidden problem when Lambda talks to RDS: each Lambda instance may open a new DB connection. During a spike, you can exhaust DB connections fast.

The fix is to use **RDS Proxy**. It sits between Lambda and the database, pools connections, and reuses them across Lambda invocations. This keeps your database safe from connection storms.

Alternatives:

* For PostgreSQL/MySQL, some teams also run PgBouncer on ECS/Fargate.
* Or, for workloads with unpredictable spikes, consider DynamoDB which doesn’t have connection limits.

### Step 4: Tune for Storms

* **Visibility timeout** ≥ 3 × Lambda timeout.
* Do throughput math:

```
parallelism = reserved_concurrency × batch_sizerecords/sec ≈ parallelism / avg_processing_seconds
```

### Step 5: Alerts

**Queue depth alarm**

```
aws cloudwatch put-metric-alarm \ --alarm-name "orders-queue-depth-high" \ --metric-name ApproximateNumberOfMessagesVisible \ --namespace AWS/SQS \ --dimensions Name=QueueName,Value=orders \ --statistic Average \ --period 60 \ --threshold 50000 \ --comparison-operator GreaterThanThreshold \ --evaluation-periods 5 \ --alarm-actions <SNS_TOPIC_ARN>
```

**Oldest message age alarm ->** Warns you when messages have been waiting too long in the queue (in **seconds**).

```
aws cloudwatch put-metric-alarm \ --alarm-name "orders-oldest-message-too-old" \ --namespace "AWS/SQS" \ --metric-name "ApproximateAgeOfOldestMessage" \ --dimensions "Name=QueueName,Value=orders" \ --statistic "Maximum" \ --period 60 \ --threshold 600 \ # warn if oldest message > 10 minutes old --comparison-operator "GreaterThanThreshold" \ --evaluation-periods 5 \ # for 5 minutes if period=60 --treat-missing-data "notBreaching" \ --unit "Seconds" \ --alarm-actions "<SNS_TOPIC_ARN>"
```

### Step 6: DLQ Replay

Fix the bug → replay messages from DLQ to main queue with a small Lambda.

```
import { SQSClient, ReceiveMessageCommand, DeleteMessageCommand, SendMessageCommand } from "@aws-sdk/client-sqs";const sqs = new SQSClient({});const DLQ_URL = process.env.DLQ_URL;const MAIN_URL = process.env.MAIN_URL;export const handler = async () => { const res = await sqs.send(new ReceiveMessageCommand({ QueueUrl: DLQ_URL, MaxNumberOfMessages: 10, WaitTimeSeconds: 1 })); if (!res.Messages) return; for (const m of res.Messages) { await sqs.send(new SendMessageCommand({ QueueUrl: MAIN_URL, MessageBody: m.Body })); await sqs.send(new DeleteMessageCommand({ QueueUrl: DLQ_URL, ReceiptHandle: m.ReceiptHandle })); }};
```

* Pick `THRESHOLD_SECONDS` well below your SQS **message retention** (default 4 days) but high enough to avoid noise. Start with 600-1800 seconds for most APIs, or align it with your SLA.
* Use `Maximum` (not `Average`) - you care about the single **oldest** message.
* Pair this with the **queue depth** alarm you already have.

### Important Pointers..

* **Don’t** let Lambda’s scaling run wild in a spike.
* **Do** buffer in SQS and process at a pace your system can handle.
* **Always** set a DLQ - losing data is worse than slow processing.
* **Monitor** queue depth and message age - that’s your early warning.
* **Use RDS Proxy** when Lambdas talk to relational databases.
* **Add API Gateway caching** if traffic is repetitive.

### **One last note,**

This whole design works best for **asynchronous APIs-**&#x70;laces where you can acknowledge a request and process it later.

But what if your API is **synchronous** and the client needs a response *right away*? In that case, queues won’t help. You need other tools like rate limiting, provisioned concurrency, and sometimes containers.

I wrote a follow-up on handling **synchronous API traffic spikes** [here](https://medium.com/aws-in-plain-english/surviving-traffic-surges-in-sync-apis-rate-limits-warm-lambdas-and-smart-scaling-d04488ad94db?sk=6a2f4645f254fd28119b2f5ab263269d):
[https://medium.com/aws-in-plain-english/surviving-traffic-surges-in-sync-apis-rate-limits-warm-lambdas-and-smart-scaling-d04488ad94db?sk=6a2f4645f254fd28119b2f5ab263269d](https://medium.com/aws-in-plain-english/surviving-traffic-surges-in-sync-apis-rate-limits-warm-lambdas-and-smart-scaling-d04488ad94db?sk=6a2f4645f254fd28119b2f5ab263269d)

Together, these two posts cover both sides of the coin:

* Async APIs → buffer with SQS.
* Sync APIs → throttle, pre-warm, or containerize.

### ☕️ Found This Helpful?

If this guide helped you debug a tricky front-end issue or saved you from a wild goose chase :
you can [buy me a coffee](http://buymeacoffee.com/subodhshet0)

### A message from our Founder

**Hey,** [**Sunil**](https://linkedin.com/in/sunilsandhu) **here.** I wanted to take a moment to thank you for reading until the end and for being a part of this community.

Did you know that our team run these publications as a volunteer effort to over 3.5m monthly readers? **We don’t receive any funding, we do this to support the community. ❤️**

If you want to show some love, please take a moment to **follow me on** [**LinkedIn**](https://linkedin.com/in/sunilsandhu)**,** [**TikTok**](https://tiktok.com/@messyfounder), [**Instagram**](https://instagram.com/sunilsandhu). You can also subscribe to our [**weekly newsletter**](https://newsletter.plainenglish.io/).

And before you go, don’t forget to **clap** and **follow** the writer️!

<img src="https://cdn-images-1.medium.com/max/1600/1*XMf_cR1ST_NpeJrjNq0R-w.png" alt="">
<h3 id="the-problem">The Problem</h3>
You’ve built a nice little API using AWS API Gateway - serving as a web-hook endpoint for an external Order Management System.
It takes orders from your web app, saves them to a database, and calls a few downstream services.
It runs through this stack:
 API Gateway → Lambda → Database.
It works perfectly on a normal day.
Then one day…
<ul>
<li>Your marketing team runs a big sale.</li>
<li>Or a partner’s integration script gets stuck in a loop.</li>
<li>Or a new feature upstream pushes thousands of requests by mistake.</li>
</ul>
Suddenly you’re facing an event storm - a huge, unexpected spike in requests hitting your API all at once.
<h3 id="whats-an-eventstorm">What’s an Event Storm?</h3>
An event storm is when the number of incoming requests in a short time is way higher than your system normally handles.
 It’s not a slow increase. It’s a flood.
Example triggers:
<ul>
<li>Black Friday or Diwali sale on your e-commerce site.</li>
<li>A cron job gone rogue sending thousands of API calls per second.</li>
<li>A botnet hammering your public endpoint.</li>
<li>A sudden surge in user signups after media coverage.</li>
</ul>
Quick note on Lambda scaling: Lambda doesn’t go from 0 → 100K concurrent executions instantly. Each region has a burst concurrency limit (for example ~3000 in <code>us-east-1</code>) and then scales up by about 500–1000 per minute.
So when I say “100K requests hit,” I mean the inbound spike hitting API Gateway, not the actual concurrency Lambda reached. The scaling ramp-up actually makes the need for a buffer more obvious -SQS can absorb the full burst immediately, while Lambda drains at the pace it can realistically scale to.
<h3 id="why-its-a-problem-in-awslambda">Why It’s a Problem in AWS Lambda</h3>
AWS Lambda scales fast, which sounds great until you realise:
<ul>
<li>Every Lambda execution counts toward your account concurrency limit.</li>
<li>If you hit that limit, all other Lambdas in your account may start failing too.</li>
<li>Downstream systems (like a database) may crash from too many parallel requests.</li>
</ul>
With API Gateway directly invoking Lambda, an event storm can burn through concurrency in seconds.
<h3 id="the-saferapproach">The Safer Approach</h3>
We’ll redesign the flow so that:
<ul>
<li>API Gateway sends requests to SQS instead of Lambda directly.</li>
<li>If SQS accepts it, API Gateway returns 202 Accepted with an ack id (SQS <code>MessageId</code>).</li>
</ul>
<pre><code class="code-highlight">HTTP/1.1 202 Accepted{"status":"accepted","messageId":"c1c7...","receivedAt":1735296623123}
</code></pre>
<ul>
<li>Processing happens later via the consumer Lambda.</li>
<li>Lambda reads from SQS in controlled batches and upserts into database</li>
<li>Concurrency is capped so we never overload the database.</li>
<li>Failed messages go to a DLQ for later reprocessing.</li>
</ul>
This way, the storm is buffered in SQS, and you can process at a steady pace without losing data.
<h3 id="architecture-overview">Architecture Overview</h3>
<ol>
<li>API Gateway -> receives incoming HTTP requests.</li>
<li>SQS (Standard Queue) -> buffers all requests.</li>
<li>Lambda Consumer -> pulls messages from SQS in small batches.</li>
<li>DLQ -> stores failed messages for later replay.</li>
</ol>
Don’t forget about caching at the API layer.
If your API is serving repetitive data (like catalog lookups, product info, or configuration files), you can enable API Gateway caching. This stores responses in an in-memory cache so repeated requests don’t even reach Lambda or SQS.
In my case the requests were mostly unique and user-specific, so caching didn’t help much. But for many APIs, caching at API GW can drastically reduce Lambda concurrency and costs.
<h3 id="step-0-recommended-startingsettings">Step 0: Recommended Starting Settings</h3>
You can tweak these later, but start here:
<ul>
<li>Lambda timeout: 30s</li>
<li>Lambda reserved concurrency (the max number of concurrent executions this function can ever use): 50</li>
<li>SQS batch size: 10</li>
<li>Max batching window (how long Lambda waits to gather more records before invoking the function): 2s</li>
<li>SQS visibility timeout (the time a message stays hidden after being picked up, before it can be retried): 90s</li>
<li>DLQ maxReceiveCount (the number of times a message can fail before being sent to the DLQ): 5</li>
</ul>
Why these help:
<ul>
<li>Max parallel work = 50 (Lambda reserved concurrency**)** × 10 (SQS batch size**)** = 500 messages at once.</li>
<li>SQS buffers the rest during a spike.</li>
<li>Visibility timeout prevents duplicate processing.</li>
<li>DLQ ensures nothing is lost.</li>
</ul>
<h3 id="step-1-create-sqs-anddlq">Step 1: Create SQS and DLQ</h3>
Create DLQ
<pre><code class="code-highlight">aws sqs create-queue --queue-name orders-dlq
</code></pre>
Create main queue with DLQ attached
<pre><code class="code-highlight">DLQ_URL=$(aws sqs get-queue-url --queue-name orders-dlq --query 'QueueUrl' --output text)DLQ_ARN=$(aws sqs get-queue-attributes --queue-url $DLQ_URL --attribute-names QueueArn --query 'Attributes.QueueArn' --output text)aws sqs create-queue \ --queue-name orders \ --attributes '{ "RedrivePolicy":"{\"deadLetterTargetArn\":\"'"$DLQ_ARN"'\",\"maxReceiveCount\":\"5\"}", "VisibilityTimeout":"90" }'
</code></pre>
<h3 id="step-2-connect-api-gateway-tosqs">Step 2: Connect API Gateway to SQS</h3>
<h4 id="option-a-direct-integration">Option A: Direct integration</h4>
<ul>
<li>No Lambda in between.</li>
<li>API Gateway sends request body directly to SQS.</li>
</ul>
IAM role for API Gateway
<pre><code class="code-highlight">{ "Version": "2012-10-17", "Statement": [{ "Effect": "Allow", "Action": ["sqs:SendMessage"], "Resource": "arn:aws:sqs:&#x3C;REGION>:&#x3C;ACCOUNT_ID>:orders" }]}
</code></pre>
<h4 id="option-b-producerlambda">Option B: Producer Lambda</h4>
If you need validation/auth before pushing to SQS:
<pre><code class="code-highlight">// producer/index.mjsimport { SQSClient, SendMessageCommand } from "@aws-sdk/client-sqs";const sqs = new SQSClient({});const QUEUE_URL = process.env.QUEUE_URL;export const handler = async (event) => { const body = JSON.parse(event.body || "{}"); if (!body.orderId) { return { statusCode: 400, body: JSON.stringify({ error: "orderId required" }) }; } await sqs.send(new SendMessageCommand({ QueueUrl: QUEUE_URL, MessageBody: JSON.stringify(body) })); return { statusCode: 202, body: JSON.stringify({ status: "accepted" }) };};
</code></pre>
API Gateway caching reminder: If traffic includes repeated requests, enable API Gateway caching. It cuts load before it even reaches SQS or Lambda.
Step 3: Create the Consumer Lambda
<pre><code class="code-highlight">// consumer/index.mjsexport const handler = async (event) => { for (const record of event.Records) { try { const msg = JSON.parse(record.body); await processOrder(msg); } catch (err) { console.error("Failed for messageId", record.messageId, err); throw err; // forces SQS to retry or send to DLQ } }};async function processOrder(msg) { await new Promise(r => setTimeout(r, 150)); // simulate work}
</code></pre>
Event Source Mapping
<ul>
<li>Batch size: 10</li>
<li>Max batching window: 2s</li>
</ul>
Reserved concurrency: 50 (prevents overload)
<h3 id="step-31-dont-kill-your-database-connections">Step 3.1: Don’t kill your database connections</h3>
One hidden problem when Lambda talks to RDS: each Lambda instance may open a new DB connection. During a spike, you can exhaust DB connections fast.
The fix is to use RDS Proxy. It sits between Lambda and the database, pools connections, and reuses them across Lambda invocations. This keeps your database safe from connection storms.
Alternatives:
<ul>
<li>For PostgreSQL/MySQL, some teams also run PgBouncer on ECS/Fargate.</li>
<li>Or, for workloads with unpredictable spikes, consider DynamoDB which doesn’t have connection limits.</li>
</ul>
<h3 id="step-4-tune-forstorms">Step 4: Tune for Storms</h3>
<ul>
<li>Visibility timeout ≥ 3 × Lambda timeout.</li>
<li>Do throughput math:</li>
</ul>
<pre><code class="code-highlight">parallelism = reserved_concurrency × batch_sizerecords/sec ≈ parallelism / avg_processing_seconds
</code></pre>
<h3 id="step-5alerts">Step 5: Alerts</h3>
Queue depth alarm
<pre><code class="code-highlight">aws cloudwatch put-metric-alarm \ --alarm-name "orders-queue-depth-high" \ --metric-name ApproximateNumberOfMessagesVisible \ --namespace AWS/SQS \ --dimensions Name=QueueName,Value=orders \ --statistic Average \ --period 60 \ --threshold 50000 \ --comparison-operator GreaterThanThreshold \ --evaluation-periods 5 \ --alarm-actions &#x3C;SNS_TOPIC_ARN>
</code></pre>
Oldest message age alarm -> Warns you when messages have been waiting too long in the queue (in seconds).
<pre><code class="code-highlight">aws cloudwatch put-metric-alarm \ --alarm-name "orders-oldest-message-too-old" \ --namespace "AWS/SQS" \ --metric-name "ApproximateAgeOfOldestMessage" \ --dimensions "Name=QueueName,Value=orders" \ --statistic "Maximum" \ --period 60 \ --threshold 600 \ # warn if oldest message > 10 minutes old --comparison-operator "GreaterThanThreshold" \ --evaluation-periods 5 \ # for 5 minutes if period=60 --treat-missing-data "notBreaching" \ --unit "Seconds" \ --alarm-actions "&#x3C;SNS_TOPIC_ARN>"
</code></pre>
<h3 id="step-6-dlqreplay">Step 6: DLQ Replay</h3>
Fix the bug → replay messages from DLQ to main queue with a small Lambda.
<pre><code class="code-highlight">import { SQSClient, ReceiveMessageCommand, DeleteMessageCommand, SendMessageCommand } from "@aws-sdk/client-sqs";const sqs = new SQSClient({});const DLQ_URL = process.env.DLQ_URL;const MAIN_URL = process.env.MAIN_URL;export const handler = async () => { const res = await sqs.send(new ReceiveMessageCommand({ QueueUrl: DLQ_URL, MaxNumberOfMessages: 10, WaitTimeSeconds: 1 })); if (!res.Messages) return; for (const m of res.Messages) { await sqs.send(new SendMessageCommand({ QueueUrl: MAIN_URL, MessageBody: m.Body })); await sqs.send(new DeleteMessageCommand({ QueueUrl: DLQ_URL, ReceiptHandle: m.ReceiptHandle })); }};
</code></pre>
<ul>
<li>Pick <code>THRESHOLD_SECONDS</code> well below your SQS message retention (default 4 days) but high enough to avoid noise. Start with 600-1800 seconds for most APIs, or align it with your SLA.</li>
<li>Use <code>Maximum</code> (not <code>Average</code>) - you care about the single oldest message.</li>
<li>Pair this with the queue depth alarm you already have.</li>
</ul>
<h3 id="important-pointers">Important Pointers..</h3>
<ul>
<li>Don’t let Lambda’s scaling run wild in a spike.</li>
<li>Do buffer in SQS and process at a pace your system can handle.</li>
<li>Always set a DLQ - losing data is worse than slow processing.</li>
<li>Monitor queue depth and message age - that’s your early warning.</li>
<li>Use RDS Proxy when Lambdas talk to relational databases.</li>
<li>Add API Gateway caching if traffic is repetitive.</li>
</ul>
<h3 id="one-lastnote">One last note,</h3>
This whole design works best for asynchronous APIs-places where you can acknowledge a request and process it later.
But what if your API is synchronous and the client needs a response right away? In that case, queues won’t help. You need other tools like rate limiting, provisioned concurrency, and sometimes containers.
I wrote a follow-up on handling synchronous API traffic spikes <a href="https://medium.com/aws-in-plain-english/surviving-traffic-surges-in-sync-apis-rate-limits-warm-lambdas-and-smart-scaling-d04488ad94db?sk=6a2f4645f254fd28119b2f5ab263269d">here</a>:
<a href="https://medium.com/aws-in-plain-english/surviving-traffic-surges-in-sync-apis-rate-limits-warm-lambdas-and-smart-scaling-d04488ad94db?sk=6a2f4645f254fd28119b2f5ab263269d">https://medium.com/aws-in-plain-english/surviving-traffic-surges-in-sync-apis-rate-limits-warm-lambdas-and-smart-scaling-d04488ad94db?sk=6a2f4645f254fd28119b2f5ab263269d</a>
Together, these two posts cover both sides of the coin:
<ul>
<li>Async APIs → buffer with SQS.</li>
<li>Sync APIs → throttle, pre-warm, or containerize.</li>
</ul>
<h3 id="️-found-thishelpful">☕️ Found This Helpful?</h3>
If this guide helped you debug a tricky front-end issue or saved you from a wild goose chase :
you can <a href="http://buymeacoffee.com/subodhshet0">buy me a coffee</a>
<h3 id="a-message-from-ourfounder">A message from our Founder</h3>
Hey, <a href="https://linkedin.com/in/sunilsandhu">Sunil</a> here. I wanted to take a moment to thank you for reading until the end and for being a part of this community.
Did you know that our team run these publications as a volunteer effort to over 3.5m monthly readers? We don’t receive any funding, we do this to support the community. ❤️
If you want to show some love, please take a moment to follow me on <a href="https://linkedin.com/in/sunilsandhu">LinkedIn</a>, <a href="https://tiktok.com/@messyfounder">TikTok</a>, <a href="https://instagram.com/sunilsandhu">Instagram</a>. You can also subscribe to our <a href="https://newsletter.plainenglish.io/">weekly newsletter</a>.
And before you go, don’t forget to clap and follow the writer️!

How to Stop AWS Lambda from Melting When 100K Requests Hit at Once

For the modern small business owner, the creative process has changed forever. You no longer need to know how to use complex software like Photoshop; you need to know how to write an effective AI Prompt Engineering for Branding prompt.

![](https://cdn-images-1.medium.com/max/1600/1*mq4Z-LZN8T_07_YKsBgcXw.png)

A prompt is more than a keyword; it is the Natural Language Design brief that the X-Design AI Agent uses to build your entire visual world. The difference between a generic result and a professional, cohesive brand lies entirely in the structure and detail of that instruction.

Most generic tools operate on simple keyword matching. If you type “YouTube logo,” you get a generic YouTube Channel logo. X-Design [AI logo generator](https://www.x-design.com/ai-logo-generator) operates by interpreting a true Visual Brand Brief, allowing you to embed your company’s story, industry standards, and required assets into a single command.

Mastering the prompt is mastering your brand’s destiny. It eliminates the back-and-forth common with human designers and moves you straight to a professional, on-brand result.

### The X-Design Prompt Structure: A Three-Layer Formula

To unlock the full potential of X-Design and AI Prompt Engineering for Branding, you need to think of your prompt not as a sentence, but as a formula with three distinct layers. This X-Design Prompt Structure ensures the AI builds your brand on a solid, strategic foundation.

![](https://cdn-images-1.medium.com/max/1600/1*u4TAaBg3hlgl8OCZFJ5uvA.png)

### Layer 1: The Foundation (What You Are Selling)

This layer provides the essential context. It grounds the AI in your business reality — who you are, what you sell, and who you are trying to reach.

**Industry & Product:** Define the tangible subject.
Example: *“An artisan bakery specializing in sourdough and rustic pastries.”*

**Brand Tone & Feeling:** Define the abstract mood and emotional atmosphere.
Example: *“The mood should be warm, trustworthy, and heritage-focused.”*

**Target Audience:** Define who the design should appeal to.
Example: *“Young professionals and families in an urban, upscale market.”*

Why it matters: Generic AI knows what “sourdough” looks like. X-Design, using this foundation, understands that a “heritage-focused” design for “upscale market” must use specific typography and a muted color palette, automatically enforcing brand standards before you even ask for them.

### Layer 2: The Visual DNA (How It Must Look)

This is the creative layer where you dictate the specific aesthetic choices. It converts abstract ideas into tangible visual styles.

**Style Guidance:** Define the artistic treatment.
Example: *“Minimalist line art, hand-drawn aesthetic, or geometric symbol.”*

**Color Palette:** Specify the exact emotional color set.
Example: *“Earthy and natural color palette, specifically using deep burnt orange and off-white.”*

**Typography Preference:** Guide the font choice for the logo design.
Example: *“A clean, modern serif font for the name, with a supporting sans-serif.”*

Why it matters: This layer provides Design Language Prompt elements. By specifying “Minimalist line art” and “deep burnt orange,” you prevent the AI from defaulting to bright, generic colors and complex vector graphics, ensuring a unique result that aligns with your vision.

### Layer 3: The Refinement & Constraint (The Professional Finish)

This layer applies final quality checks and details required for professional deployment. It is where you move from a nice graphic to a usable Logo System.

**Technical Constraint:** Specify deployment needs.
Example: *“Must be able to work in a circular stamp format and be legible when printed small.”*

**Misuse/Avoid:** Tell the AI what not to include.
Example: *“Avoid overly complicated symbols or any representation of a chef’s hat.”*

**Iteration Strategy:** Prompt for a specific change.
Example: *“Based on this design, generate three more concepts that only change the geometric symbol.”*

Why it matters: Constraints are powerful. By demanding a design that is “legible when printed small,” you force the AI Prompt Engineering for Branding system to prioritize clarity and technical robustness, which is critical for Iterative AI Design and final file usability.

### Prompt Application: From Logo to Marketing Templates

The ultimate test of AI Prompt Engineering for Branding is its ability to scale across different visual assets while maintaining a single, consistent look. X-Design uses the same prompt language, but adapts it to the specific format of each asset.

### 1. Logo Prompt Formulas (The Master Visual Brand Brief)

The logo prompt is the most important, as it defines your Visual Identity Toolkit. It should be comprehensive, combining all three layers to create the foundational asset. You can also use the photo enhancer tool to [improve the logo quality](https://www.x-design.com/image-enhancer).

Formula Example: *“\[LAYER 1: Artisan bakery specializing in rustic pastries. Brand tone should feel grounded and reliable.] \[LAYER 2: Use a clean geometric symbol combined with a strong, modern serif font. The color palette is restricted to deep forest green and cream.] \[LAYER 3: Ensure the logo is suitable for a circular coffee stamp and is highly legible at small sizes.]”*

![](https://cdn-images-1.medium.com/max/1600/1*qCpHhtfJ1dhUQK9QIqJRJQ.png)

### 2. Poster/Flyer Prompts (The Marketing Brief)

Once the Logo System is established, the prompt for marketing materials shifts focus from *what the brand is* to *what the brand is doing*, while the AI automatically enforces the stored colors and fonts.

Formula Example: *“\[ACTION: Create a square social media poster for a special holiday promotion: 25% off all pastries before 10 AM on Monday.] \[VISUALS: Use a high-quality photo of a steaming latte with a soft bokeh background. The headline must be bold and prominent.] \[CONSTRAINT: Must adhere to the approved ‘Forest Green’ color palette and use the primary headline font.]”*

![](https://cdn-images-1.medium.com/max/1600/1*volJTVkpNc_pNR2lG0n71w.png)

Key insight: You don’t prompt for color or font here; you prompt for *marketing strategy*, and the AI handles the Design Rule Enforcement instantly, ensuring On-Brand Posters.

### 3. Product Packaging Prompts (The Product Brief)

These prompts focus on application and physical constraint. You must tell the AI where the logo needs to be placed and the material it will interact with.

Formula Example: *“\[PRODUCT: Design packaging for a retail coffee bag.] \[VISUALS: Apply the ‘inverse’ (white) version of the logo system to the dark kraft paper background. Use a simple, informational layout.] \[CONSTRAINT: Use the body font for all product description text. Design must include space for a stamped ‘Best By’ date.”*

![](https://cdn-images-1.medium.com/max/1600/1*gzHFUARuQ7ZoXu8jHn_biA.png)

Key insight: This prompt uses specific terminology from your generated VI Toolkit (“inverse logo,” “body font”) to pull the exact file needed, guaranteeing Consistent Brand Touchpoints even on physical goods.

### Iteration: The Power of Targeted Refinement

A powerful AI like X-Design doesn’t just deliver one result; it delivers a series of designs that you can refine instantly using natural language. This Iterative AI Design capability drastically cuts down on development time.

### 1. Style Iteration

Instead of saying “I don’t like it,” you tell the Agent *how* to change the style based on its initial output.

* *Initial Prompt Result:* A geometric, clean logo.
* *Refinement Prompt:* “Keep the core shape, but make the lines slightly thicker to give it a more established, classic feel.”

### 2. Constraint Iteration

You can test technical changes instantly without restarting the design.

* *Initial Prompt Result:* A logo that looks great on white.
* *Refinement Prompt:* “Show me this design applied to a black background. Does the secondary font still stand out enough, or does it need to be lighter?”

This constant, conversation-based refinement is the fastest path to locking down a Future-Proof Branding asset that satisfies all your deployment needs.

### Conclusion

The ability to write a structured, detailed prompt is now the most valuable skill for any entrepreneur. In the era of the X-Design AI Agent, the complexity of a design brief is no longer limited by your software skills but by your imagination and descriptive language.

By adopting the three-layer X-Design Prompt Structure, you ensure that your visual identity is built on a strategic foundation, not random luck. This process turns your simple idea into a Visual Brand Brief that delivers professional-grade assets, allowing you to bypass the traditional design industry and build a cohesive brand on your own terms. Master the prompt, and you master your AI Brand Strategy.

For the modern small business owner, the creative process has changed forever. You no longer need to know how to use complex software like Photoshop; you need to know how to write an effective AI Prompt Engineering for Branding prompt.
<img src="https://cdn-images-1.medium.com/max/1600/1*mq4Z-LZN8T_07_YKsBgcXw.png" alt="">
A prompt is more than a keyword; it is the Natural Language Design brief that the X-Design AI Agent uses to build your entire visual world. The difference between a generic result and a professional, cohesive brand lies entirely in the structure and detail of that instruction.
Most generic tools operate on simple keyword matching. If you type “YouTube logo,” you get a generic YouTube Channel logo. X-Design <a href="https://www.x-design.com/ai-logo-generator">AI logo generator</a> operates by interpreting a true Visual Brand Brief, allowing you to embed your company’s story, industry standards, and required assets into a single command.
Mastering the prompt is mastering your brand’s destiny. It eliminates the back-and-forth common with human designers and moves you straight to a professional, on-brand result.
<h3 id="the-x-design-prompt-structure-a-three-layer-formula">The X-Design Prompt Structure: A Three-Layer Formula</h3>
To unlock the full potential of X-Design and AI Prompt Engineering for Branding, you need to think of your prompt not as a sentence, but as a formula with three distinct layers. This X-Design Prompt Structure ensures the AI builds your brand on a solid, strategic foundation.
<img src="https://cdn-images-1.medium.com/max/1600/1*u4TAaBg3hlgl8OCZFJ5uvA.png" alt="">
<h3 id="layer-1-the-foundation-what-you-areselling">Layer 1: The Foundation (What You Are Selling)</h3>
This layer provides the essential context. It grounds the AI in your business reality — who you are, what you sell, and who you are trying to reach.
Industry &#x26; Product: Define the tangible subject.
Example: “An artisan bakery specializing in sourdough and rustic pastries.”
Brand Tone &#x26; Feeling: Define the abstract mood and emotional atmosphere.
Example: “The mood should be warm, trustworthy, and heritage-focused.”
Target Audience: Define who the design should appeal to.
Example: “Young professionals and families in an urban, upscale market.”
Why it matters: Generic AI knows what “sourdough” looks like. X-Design, using this foundation, understands that a “heritage-focused” design for “upscale market” must use specific typography and a muted color palette, automatically enforcing brand standards before you even ask for them.
<h3 id="layer-2-the-visual-dna-how-it-mustlook">Layer 2: The Visual DNA (How It Must Look)</h3>
This is the creative layer where you dictate the specific aesthetic choices. It converts abstract ideas into tangible visual styles.
Style Guidance: Define the artistic treatment.
Example: “Minimalist line art, hand-drawn aesthetic, or geometric symbol.”
Color Palette: Specify the exact emotional color set.
Example: “Earthy and natural color palette, specifically using deep burnt orange and off-white.”
Typography Preference: Guide the font choice for the logo design.
Example: “A clean, modern serif font for the name, with a supporting sans-serif.”
Why it matters: This layer provides Design Language Prompt elements. By specifying “Minimalist line art” and “deep burnt orange,” you prevent the AI from defaulting to bright, generic colors and complex vector graphics, ensuring a unique result that aligns with your vision.
<h3 id="layer-3-the-refinement--constraint-the-professional-finish">Layer 3: The Refinement &#x26; Constraint (The Professional Finish)</h3>
This layer applies final quality checks and details required for professional deployment. It is where you move from a nice graphic to a usable Logo System.
Technical Constraint: Specify deployment needs.
Example: “Must be able to work in a circular stamp format and be legible when printed small.”
Misuse/Avoid: Tell the AI what not to include.
Example: “Avoid overly complicated symbols or any representation of a chef’s hat.”
Iteration Strategy: Prompt for a specific change.
Example: “Based on this design, generate three more concepts that only change the geometric symbol.”
Why it matters: Constraints are powerful. By demanding a design that is “legible when printed small,” you force the AI Prompt Engineering for Branding system to prioritize clarity and technical robustness, which is critical for Iterative AI Design and final file usability.
<h3 id="prompt-application-from-logo-to-marketing-templates">Prompt Application: From Logo to Marketing Templates</h3>
The ultimate test of AI Prompt Engineering for Branding is its ability to scale across different visual assets while maintaining a single, consistent look. X-Design uses the same prompt language, but adapts it to the specific format of each asset.
<h3 id="1-logo-prompt-formulas-the-master-visual-brandbrief">1. Logo Prompt Formulas (The Master Visual Brand Brief)</h3>
The logo prompt is the most important, as it defines your Visual Identity Toolkit. It should be comprehensive, combining all three layers to create the foundational asset. You can also use the photo enhancer tool to <a href="https://www.x-design.com/image-enhancer">improve the logo quality</a>.
Formula Example: “[LAYER 1: Artisan bakery specializing in rustic pastries. Brand tone should feel grounded and reliable.] [LAYER 2: Use a clean geometric symbol combined with a strong, modern serif font. The color palette is restricted to deep forest green and cream.] [LAYER 3: Ensure the logo is suitable for a circular coffee stamp and is highly legible at small sizes.]”
<img src="https://cdn-images-1.medium.com/max/1600/1*qCpHhtfJ1dhUQK9QIqJRJQ.png" alt="">
<h3 id="2-posterflyer-prompts-the-marketing-brief">2. Poster/Flyer Prompts (The Marketing Brief)</h3>
Once the Logo System is established, the prompt for marketing materials shifts focus from what the brand is to what the brand is doing, while the AI automatically enforces the stored colors and fonts.
Formula Example: “[ACTION: Create a square social media poster for a special holiday promotion: 25% off all pastries before 10 AM on Monday.] [VISUALS: Use a high-quality photo of a steaming latte with a soft bokeh background. The headline must be bold and prominent.] [CONSTRAINT: Must adhere to the approved ‘Forest Green’ color palette and use the primary headline font.]”
<img src="https://cdn-images-1.medium.com/max/1600/1*volJTVkpNc_pNR2lG0n71w.png" alt="">
Key insight: You don’t prompt for color or font here; you prompt for marketing strategy, and the AI handles the Design Rule Enforcement instantly, ensuring On-Brand Posters.
<h3 id="3-product-packaging-prompts-the-productbrief">3. Product Packaging Prompts (The Product Brief)</h3>
These prompts focus on application and physical constraint. You must tell the AI where the logo needs to be placed and the material it will interact with.
Formula Example: “[PRODUCT: Design packaging for a retail coffee bag.] [VISUALS: Apply the ‘inverse’ (white) version of the logo system to the dark kraft paper background. Use a simple, informational layout.] [CONSTRAINT: Use the body font for all product description text. Design must include space for a stamped ‘Best By’ date.”
<img src="https://cdn-images-1.medium.com/max/1600/1*gzHFUARuQ7ZoXu8jHn_biA.png" alt="">
Key insight: This prompt uses specific terminology from your generated VI Toolkit (“inverse logo,” “body font”) to pull the exact file needed, guaranteeing Consistent Brand Touchpoints even on physical goods.
<h3 id="iteration-the-power-of-targeted-refinement">Iteration: The Power of Targeted Refinement</h3>
A powerful AI like X-Design doesn’t just deliver one result; it delivers a series of designs that you can refine instantly using natural language. This Iterative AI Design capability drastically cuts down on development time.
<h3 id="1-style-iteration">1. Style Iteration</h3>
Instead of saying “I don’t like it,” you tell the Agent how to change the style based on its initial output.
<ul>
<li>Initial Prompt Result: A geometric, clean logo.</li>
<li>Refinement Prompt: “Keep the core shape, but make the lines slightly thicker to give it a more established, classic feel.”</li>
</ul>
<h3 id="2-constraint-iteration">2. Constraint Iteration</h3>
You can test technical changes instantly without restarting the design.
<ul>
<li>Initial Prompt Result: A logo that looks great on white.</li>
<li>Refinement Prompt: “Show me this design applied to a black background. Does the secondary font still stand out enough, or does it need to be lighter?”</li>
</ul>
This constant, conversation-based refinement is the fastest path to locking down a Future-Proof Branding asset that satisfies all your deployment needs.
<h3 id="conclusion">Conclusion</h3>
The ability to write a structured, detailed prompt is now the most valuable skill for any entrepreneur. In the era of the X-Design AI Agent, the complexity of a design brief is no longer limited by your software skills but by your imagination and descriptive language.
By adopting the three-layer X-Design Prompt Structure, you ensure that your visual identity is built on a strategic foundation, not random luck. This process turns your simple idea into a Visual Brand Brief that delivers professional-grade assets, allowing you to bypass the traditional design industry and build a cohesive brand on your own terms. Master the prompt, and you master your AI Brand Strategy.

Do you want to know about AI prompt engineering for branding and how it can help you create your brand identity? Read this guide on how effective prompts generate better results.

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8 Python Tools That Stop Projects From Breaking

40+ Genius Ways to Make Money from AI with Gemini 2.0: A Comprehensive Guide

How to Send Desktop Notifications with Python

9 Hackathon Swag Ideas Developers Actually Keep

5 Chat GPT Prompts You Can Plug, Play, and Go Crazy With

Software functionalities for sports betting companies – enhance your customer experience

Top 8 LLM + RAG Projects for your AI Portfolio 2025

Core Banking API for Embedded Finance: How Digital Products Gain Banking Capabilities Through APIs

How to Stop AWS Lambda from Melting When 100K Requests Hit at Once

AI Prompt Engineering: The Brand Designer's New Language