Just did it, thanks again… quite new user here didn’t know it’s possible😅

good catch! it is indeed licensed under the MIT license. i made a mistake in the post title/description writing GPL-3.0, but the repo is correct. thanks for pointing it out!

Says MIT license on github. May want to fix that.

Contenuto

Removed by mod

you are a senior developer, start to transform your view in a senior architect. With AI there’s no more need of developers. An architect ius needed, and if it haas a solid dev backround as yours projects will change view. Technology is always changing and it’s hard to stay at pace. But if you look from an higher perspective your project your experience will only help the AI to do the Job for you

The most important thing developers forget is planning. I am senior and used to delegate dev to Junior Devs. If you have not enough experience in software architecture you are missing the most important thig: You cannot start developing. You must start planning, first of all require your agent to plan the steps for the target mission. Than examine the plan produced, ask to divide int single in testable units. Most AI Vibe programmers start with develop directions. That is wrong. The longest part of the job is to prepare the Agent to perform correctly

I wrote my first service worker, for a PWA application… Since then I could never write an app without. It’s truly needed if you (as me) don’t like useless store apps, e.g. for Android. But When you make a PWA for the Desktop taht truly makes sense !

Wow this is a resource! Got several older desktop and laptops to revive! Down with the programmed obsolescence!

The surveillance landscape has shifted dramatically since 2016. Today, we don’t just have passive state surveillance tapping cables; we have massive, voluntary corporate surveillance through the centralization of AI. Millions of developers and businesses are willingly uploading their proprietary source code, database structures, and internal spreadsheets to cloud LLMs (OpenAI, Google, Microsoft). All this data is logged, parsed, and stored in central cloud databases. We are essentially building the ultimate corporate intelligence database of all private technical infrastructure, completely voluntarily. If you care about privacy today, the absolute priority should be moving towards local-first execution. If you must leverage cloud LLMs, the only safe way is to use architectures that enforce local data isolation, keeping your actual database rows and files local, and sending only empty abstract schemas to the model for reasoning

The problem isn’t the tool; it’s the lack of engineering foundations. Generalizing all AI-assisted development as ‘vibe coding’ is a massive oversimplification. There is a vast difference between a beginner blindly copy-pasting LLM output into a codebase they don’t understand, and a senior architect using LLMs as a high-powered assistant to speed up boilerplate, local schema generation, or parsing scripts. When you already know exactly how the underlying system operates, how memory is managed, and how to design clean software architectures, the LLM is just a productivity multiplier. You still design the data flow, audit the tool-use sandboxes, and review every single line of code. It doesn’t replace thinking; it replaces tedious typing.

It’s frustrating how legislators still refuse to grasp the fundamental mathematics of cryptography. You cannot have a ‘secure backdoor only for the good guys’. If a scanning pipeline is built into the client, the encryption is compromised by design. This isn’t ‘chat control’ - it’s the systematic dismantling of digital privacy under the guise of security.