What I learned shipping a tiny FFmpeg desktop app

Mon, 14 Sep 2026 09:52:29 +0000

I kept hitting the same annoyance. Someone sends me a .mov, I need an .mp4, and every free option online wants me to upload the file to a server I do not trust. So I built mov2mp4, a small desktop app that converts locally and never touches the network.

The conversion itself is the easy part. FFmpeg already does it in one line:

ffmpeg -i input.mov -c:v libx264 -c:a aac output.mp4

Wrapping that in something a non-developer can actually use is where the real work lived.

Bundling FFmpeg so nobody has to install it

My first version just called ffmpeg from the system path. That works on my machine and almost nobody else's. Most people do not have FFmpeg installed, and I did not want the first step of my app to be "go install a command line tool."

So I bundled the FFmpeg binary inside the app and pointed the code at the bundled copy instead of the system one. The app got bigger, but the install went from three steps to zero. For a tool aimed at people who just want their file converted, that trade was worth it.

Batch and threading

Once one file worked, people wanted folders. Running conversions one at a time was slow, so I moved to a worker setup that processes several files at once and reports progress per file. The lesson I did not expect: I had to add a clean way to cancel a running job. If you kill the process mid write, you get a half-written .mp4 that looks real until someone tries to play it. Now a cancel deletes the partial output instead of leaving garbage behind.

The part nobody warns you about: unsigned apps

This one cost me the most time. My builds are not code signed yet, so:

On macOS, Gatekeeper blocks the app on first open and hides the real "Open" button behind Privacy and Security settings.
On Windows, SmartScreen throws up a blue "unknown publisher" screen.

Users read that as "this app is broken" or "this app is malware." Neither is true, but the operating system does not give me a friendly way to explain that. For now I wrote a short first launch note in the README and added a small helper so people can get past the warning once. Proper signing is on my list, but certificates cost money and I wanted the tool out the door.

What I would tell past me

The converter was a weekend. The packaging, the cancel logic, and the "why is my OS scaring my users" problem took far longer. If you are shipping a desktop tool built on an existing binary, budget your time for the wrapper, not the core.

Repo is here if you want to poke at it: https://github.com/MaybeSomeone-arc18/mov2mp4

Here's the website link if you want to use it:
mov2mp4.vercel.app

Local Agent - Desktop.

Sun, 05 Jul 2026 10:30:01 +0000

"Convert a promise you can trust, into a fact that you control!"

In my previous post, CAPTCHA Farming 2.0, I explored how the AI industry has quietly engineered an extraction loop for human cognition, harvesting our problem-solving and reasoning chains to train their proprietary models. I ended that piece with a prediction: the only durable escape from that loop is the rise of local, self-hosted AI.

Today, I am putting code behind that conviction. I'm excited to announce the public preview of Local Agent Desktop.

Local Agent Desktop is a standalone macOS application that gives a locally running LLM real, scoped access to your development environment. It spins up your project inside Docker, utilizes the Model Context Protocol (MCP) to execute tools, and runs an autonomous write-and-verify loop to build and test software—all without a single byte of your proprietary data leaving your machine.

Promises Change, But Code is LAW

For enterprise entities, defense contractors, and security-conscious engineering teams, using cloud-hosted frontier models introduces immediate third-party risk. When you send proprietary code to a cloud AI, you are fundamentally relying on a vendor’s Terms of Service to protect you.

But terms change. Privacy policies shift overnight. Geopolitical regulations force sudden API blackouts. Vendor terms are commitments, not guarantees; they are subject to the vendor's own legal and regulatory environment.

A fully local environment removes these uncertainties entirely. It converts data-handling from "a promise you're trusting" into "a fact you control." Promises may change, but code is LAW. When your model, your agent, and your execution environment are physically isolated on your hardware, data sovereignty is enforced by architecture, not by a contract. You don't have to trust anyone's attestation—you can prove it yourself.

The Speed Bottleneck and the "Spectral" Horizon

I want to be transparent about where this technology is today. Running an autonomous AI agent loop locally on consumer hardware is computationally heavy. If you download the demo today, you will notice that speed and responsiveness are the primary bottlenecks.

This is exactly the problem my ongoing research into spectralisation is designed to solve. As mentioned in my last post, I am developing a spectral equivalence approach to LLM architecture—a tensor-level compression strategy designed to drastically reduce the compute footprint required for long-context reasoning.

To be clear: this spectral technology is not yet applied to today's demo release. The current product is a proof-of-concept for the sovereignty and architecture of local agents. Integrating spectral compression is the next critical step to making this local architecture run at the speed of thought.

The Vision: A Sovereign CI/CD Pipeline

If we can solve the compute footprint, the ceiling for this architecture is massive. What you are looking at in this demo isn't just a secure coding assistant. It is the foundational layer for a completely autonomous, local CI/CD pipeline.

Imagine an AI agent that can pull an issue, write the code, spin up a secure Docker container, run your test suite, execute a hard-scoped OWASP ZAP security scan, and finalize the PR—all with absolute zero 3rd-party risk.

This demo is the first step toward that future. It is an invitation to developers, enterprise security teams, and researchers to test it, break it, and help shape what comes next.

📥 Download the macOS ARM64 Demo App (Dropbox)
💻 Explore the Repository on GitHub

Let's build the sovereign web. If you are interested in collaboration, enterprise pilot access, or discussing the spectral architecture roadmap, reach out.

Coder Legion - Recent posts tagged desktop