I Turned Myself Into an Action Figure

I Turned Myself Into an Action Figure

Part of being in tech, especially in emerging memory technology, is constantly switching between the serious and the surreal. One day you’re in kernel debug mode, the next you’re explaining complex system architectures on a whiteboard, and then suddenly you’re jumping on the latest craze such as making yourself into an action figure.

It’s fun. It’s human. And honestly? It’s a reminder not to take yourself too seriously. (Even if your job title suggests differently)

Why Blister Packs Are Suddenly Everywhere

If you’ve been seeing action figure-style blister packs all over your timeline lately, you’re not imagining things; it’s a full-blown craze.

This trend kicked off when OpenAI released the ChatGPT-4o model on May 13, 2024, and introduced a set of new image generation capabilities that included more refined control over layout, packaging design, and high-fidelity photo rendering. People instantly began using it to turn themselves (and their friends, pets, and even fictional alter-egos) into collectible-style figures—complete with accessories, personality-driven packaging, and clever titles.

Why blister packs? They’re nostalgic, instantly recognizable, and strangely satisfying. The combination of pop culture toy aesthetics with modern personal branding hits a sweet spot. Whether you’re a tech professional, artist, or just someone who loves a good meme, these creations are the perfect blend of humor, identity, and design.

For me, it was a way to merge my professional identity with a playful twist. I spend my days working on serious memory tech—CXL, persistent memory, data platforms—but this was a chance to repackage that story (literally) in a totally unexpected way.

Plus… who wouldn’t want to be their own action figure?

The Prompt

Here is the prompt I used to create the final image

Create an image. Create an action figure of the person in the photo.

Next to the figure, there should be the toy’s equipment, each in its individual blister.

1. A book called “Programming Persistent Memory”. Use the attached book cover image
2. Cell Phone
3. A MacBook Pro (closed)
4. The MemVerge logo (Use the attached logo)

Don’t repeat the equipment under any circumstances. 

The blister pack should have a black header with a large white text –Steve Scargall – with smaller white text underneath – Director of Product Management. The blister pack background should be beige with a black border.

Visualize this in a realistic way. The action figure must retain my facial features with a smiling expression, and be rendered in high-detail, photorealistic quality.

The Result

While the result is very impressive this generation/version of the model struggles to maintain the original facial features, so you end up with something that doesn’t quite resemble your original image.

Blister Pack Steve

Final Thoughts – Collect ’Em All!

Honestly, this whole thing was way more fun than I expected. I got to see myself as a mini collectible, complete with accessories I actually use every day. There are lots of model styles, so maybe this is the start of the Tech Legends collection. Next time I’ll convert this to a 3D model that I can print on my 3D printer. Time to turn them into shelf-worthy greatness.

Linux Device Mapper WriteCache (dm-writecache) performance improvements in Linux Kernel 5.8

Linux Device Mapper WriteCache (dm-writecache) performance improvements in Linux Kernel 5.8

The Linux ‘dm-writecache’ target allows for writeback caching of newly written data to an SSD or NVMe using persistent memory will achieve much better performance in Linux Kernel 5.8.

Red Hat developer Mikulas Patocka has been working to enhance the dm-writecache performance using Intel Optane Persistent Memory (PMem) as the cache device.

The performance optimization now queued for Linux 5.8 is making use of CLFLUSHOPT within dm-writecache when available instead of MOVNTI. CLFLUSHOPT is one of Intel’s persistent memory instructions that allows for optimized flushing of cache lines by supporting greater concurrency. The CLFLUSHOPT instruction has been supported on Intel servers since Skylake and on AMD since Zen.

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Persistent memory (PMEM), especially when accessed via technologies like CXL, promises the best of both worlds: DRAM-like speed with the durability of an SSD. When you set up a filesystem like XFS or EXT4 in FSDAX (File System Direct Access) mode on a PMEM device, you’re paving a superhighway for your applications, allowing them to map files directly into their address space and bypass the kernel’s page cache entirely.

But here’s the crucial question: after all the setup and configuration, how do you prove that your application’s data is physically residing on the PMEM device and not just in regular RAM? I’ve run into this question myself, so I wrote a small Python script to get a definitive answer using SQLite3 as an example application. However, before we proceed with the script, let’s examine how you can verify this manually.

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Resolving commands 'Killed' on GCP f1-micro Compute Engine instances

When I want to perform a quick task, I generally spin up a Google GCP Compute Engine instance as they’re cheap. However, they have limited resources, particularly memory. When refreshing the package repositories, it’s quite easy to encounter an Out-of-Memory (OOM) situation which results in the command - yum or dnf - is ‘killed’. For example:

$ sudo dnf update 
CentOS Stream 8 - AppStream                                                                                                  8.3 MB/s |  18 MB     00:02    
CentOS Stream 8 - BaseOS                                                                                                      13 MB/s |  16 MB     00:01    
CentOS Stream 8 - Extras                                                                                                      69 kB/s |  16 kB     00:00    
Google Compute Engine                                                                                                         20 kB/s | 9.4 kB     00:00    
Google Cloud SDK                                                                                                              24 MB/s |  43 MB     00:01    
Killed

dmesg has a lot of information about the situation, but the key line to confirm dnf caused the OOM event, is:

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