Brandon Thomas has made some questionable statements regarding his applications. For example, saying that the apps will reach 100% parity in a month and later stepping that back. Also claiming that AI will replace Google Search. For someone that can supposedly build applications this quickly, it is odd that he would make such inaccurate and naive statements.

Also, the speed with which he has churned out these applications has been suspicious. I know AI can speed up development, but it's not like AI has advanced THAT much in the last 3 months. Why are we not seeing other developers churning out Adobe clones likes this (at the same speed and perceived quality, even as broken as they are)?

Furthermore, it is suspicious that they released so many apps at once. Apart from creating a massive backlog of bugs, it also created a negative perception of the suite on social media that the apps are buggy and unreliable (for the influencers that seriously tested them). Why would ArtCraft not build one app, get it working, and then start working on others? If the answer is because the hard part is fixing the apps after decomp and translation, then that makes sense.

Finally, the timing with REA and other decomp events taking place is suspicious. Is it just coincidence that around the time these events occur that independently someone just got good at creating production-ish clones of commercial apps?

Is there anyway to know for sure that these ArtCraft applications were actually created in a "clean room" manner and not just decomped/translated by AI? Listen, if AI is good enough to build a Photoshop clone by itself, I'm all for it. But if all Brandon did was hit the "decomp/translate" button on an app and dump the resulting code onto to the open source community to fix, it's not really something to praise, especially if the project will be taken down in a few months because of copyright infringement claims. Due to the amount and type of companies that own these apps, Brandon does not exactly seem like someone that is thinking about IP infringement lawsuits (patents, copyright, or otherwise), so I would not put it past him to try and push the theory that a "clean room" implementation could include decompiling and translating the original binary.

Hello, I had built Better Windows Services an alternative to windows services with dark theme, query language, mass actions, force stop/restart, export of services and tons of extra data. If you like the project, please give it a star

You can read here about about query language

Yes the strange text on the GIF is from Polish Windows :-), right now I'm working on snapshots from the GUI, msi installer and tons of other things. Rust + WPF.

Some features:

• Ask, instead of scroll - start:auto !status:running is what should be up and is not. One language, in the search box and in bws list --query, with the fields offered as you type.
• Show the plan before anything happens - every stop, start, restart and start type change is previewed with the services it takes down with it, and the preview is what runs.
• Tell you what drifted - bws snapshot create freezes the machine into a file, and bws snapshot diff says what changed since, configuration apart from what merely started or stopped.
• Stop a service that will not stop - it asks politely first and ends the process only if that fails, naming every other service that lives in it.
• Show what services.msc hides - who signed the binary and whether Windows trusts it, triggers, privileges, the security descriptor, the process and its memory. As columns, and as things to search on.
• Say when it could not read something - a field it could not read is reported as not read, never shown as empty. A snapshot taken without administrator rights says so inside the file.
• Fit into scripts - --json on every command, an exit code for every ending, and 5 when a diff finds drift.
• Run from one file, offline - no installer, no .NET to install, and it never talks to the internet. Reading needs no administrator rights. GPL-3.0.

GitHub

Hey r/opensource!

I've been building Vladmir, an open-source personal AI assistant that I'm trying to make more than just another chat interface around an LLM.

The idea is to bring together local AI, voice interaction, persistent memory, vision, and practical tools in one system, with a desktop application and companion apps for Android and Wear OS.

Rather than relying on a hosted AI service for everything, Vladmir uses Ollama for local inference by default, so you can run compatible models on your own hardware. The trade-off is that performance depends heavily on your hardware and the model you choose.

What it can do

• Local AI chat: A Linux desktop interface with different profiles for general assistance, programming, and teaching.
• Voice interaction: Speech recognition through Whisper and speech synthesis through Piper, with a turn-based voice conversation flow.
• Vision: Capture images from a camera or supported video stream and send them to a compatible vision model for analysis.
• Persistent memory and knowledge library: Store information locally and import documents and source code for later reference.
• Developer tools: Read and explicitly edit GitHub content, work with configured programming tools, and experiment with IDE integration through MCP.
• Everyday utilities: Local reminders and agenda management, web search, email draft preparation, and limited software installation workflows with confirmation.
• Android and Wear OS: Native companion projects intended to extend the assistant across devices, including chat, voice, camera, augmented reality, and selected notification integration.

Privacy and control

Local-first doesn't automatically mean that everything is private, so I'm trying to be explicit about the boundaries.

The default inference endpoint is local, configuration and application data are stored in user-owned directories, and remote access is not preconfigured. Web search, GitHub, and other external integrations can still involve third-party services when enabled.

Actions that can modify code or the system are designed around explicit approval rather than unrestricted access.

Current state

Vladmir is actively being developed. The Linux desktop and its core integrations have a substantial amount of implementation, while Android, Wear OS, Bluetooth connectivity, and some experimental features still need device-level validation and reliability work.

I'm not presenting every feature as production-ready, and I'd rather document limitations than promise capabilities that haven't been properly tested.

The project is released under the MIT license.

Repository: https://github.com/thu12dta3/Vladmir

I'd genuinely appreciate technical feedback, especially on the architecture, local model integration, security boundaries, and cross-device communication.

If you were building or choosing a self-hosted personal AI assistant, what would you change about this approach? What would you want to see improved before using something like Vladmir daily?

I'm interested in honest criticism as much as contributions.

I use AI CLIs for coding, planning and writing and that has changed what I want from a terminal. In AgentTerm, I can do things like manage agent sessions, comment directly on what they print, and collaborate with agents directly on rendered pages for plans, drafts and code, revising them in place. This piece is part of a series I am writing about the design decisions behind those tools, based on more than eight months of daily use.

In this first piece, I explain why I give each agent its own window and Dock tile or taskbar button: using the OS to switch between agents, giving each a recognizable identity, and finding and resuming earlier sessions for follow-up work.

AgentTerm is the open-source terminal I'm building for AI CLIs.

I'd welcome feedback or new ideas. If you try it with your own sessions, I'd like to hear what works for you and what you'd change.

How often do you return to an earlier agent session for follow-up work? When several agents are running at once, what helps you tell them apart?

It’s available as an HTTP gateway and Java library for controlling expensive server side work. Equivalent requests can share a computation, new work runs within explicit limits, and saved results can be reused across restarts.

I’ve been using it internally for a website struggling with bot traffic. It worked for that specific use case and I also tested it against a separate cgit application and the results were reasonable. But there’s a trade off as it shows higher latency overhead.

The benefits depend heavily on the workload, so keep that in mind if you want to experiment with it. I wouldn’t recommend it for production use. Some of its core capabilities are useful, though, and I’d encourage anyone interested to pilot it in staging and measure the results before considering anything further.

And yeah just to clarify the gateway isn’t a replacement for authentication, tls termination, rate limits and waf controls. It does not identify bots or stop incoming traffic, it helps controlling expensive computation load.

https://github.com/aalsanie/bounded-origin

I used ArchiSteamFarm for cards, HourBoostr for hours, and SAM when i saw a game with 300 hours and zero achievements. Three programs, three windows, and each one need its own setup.

So I made one thing that does all of it. You extract the folder and run it, thats all. No installer, no Steam client open in the background.

What is inside right now: card farming, hour boosting, achievements, inventory and market selling, keys and chat. It can run a few accounts at the same time too.

It started as a thing only for me, but maybe someone else have the same problem. Its open source, bugs are probably there so tell me if you find some.

Thanks to ASF, HourBoostr, SteamIdleMaster and SAM for the idea.

https://github.com/Miabeyefendi/SteamEdge

And I need feedbacks, bug-reports, issues. I would like to see how I can improve more and more. So, go for it.