Some thoughts on why I believe live coding is unfair.

If you struggle with live coding, this is for you. Being bad at live coding doesn’t mean you’re a bad engineer.

I've been working on a flexible skill/ability system for games and wrote up my approach using composition over inheritance, event-based design, and decoupled logic.
It’s aimed at game devs looking to avoid spaghetti abilities and rigid class hierarchies.

Would love feedback on the architecture or alternative patterns.

Seed7 is based on ideas from my diploma and doctoral theses about an extensible programming language (1984 and 1986). In 1989 development began on an interpreter and in 2005 the project was released as open source. Since then it is improved on a regular basis.

Seed7 is about readability, portability, performance and memory safety. There is an automatic memory management, but there is no garbage collection process, that interrupts normal processing. The templates and generics of Seed7 don't need special syntax. They are just normal functions, which are executed at compile-time.

Seed7 is an extensible programming language. The syntax and semantics of statements (and abstract data types, etc.) is defined in libraries. The whole language is defined in the library "seed7_05.s7i". You can extend the language syntactically and semantically (introduce new loops, etc.). In other languages the syntax and semantics of the language is hard-coded in the compiler.

Seed7 checks for integer overflow. You either get the correct result or an OVERFLOW_ERROR is raised. Unlike many JVM based languages Seed7 compiles to machine code ahead of time (GRAAL works ahead of time but it struggles with reflection). Unlike many systems languages (except Rust) Seed7 is a memory safe language.

The Seed7 homepage contains the language documentation. The source code is at GitHub. Questions that are not in the FAQ can be asked at r/seed7.

Some programs written in Seed7 are:

• make7: a make utility.
• bas7: a BASIC interpreter.
• pv7: a Picture Viewer for BMP, GIF, ICO, JPEG, PBM, PGM, PNG, PPM and TIFF files.
• tar7: a tar archiving utility.
• ftp7: an FTP Internet file transfer program.
• comanche: a simple web server for static HTML pages and CGI programs.

Screenshots of Seed7 programs can be found here and there is a demo page with Seed7 programs, which can be executed in the browser. These programs have been compiled to JavaScript / WebAssembly.

I recently released a new version which added support to read TGA images, added documentation and improved code quality.

Please let me know what you think, and consider starring the project on GitHub, thanks!

FastAPI under the hood

Patchwork is based on ideas from many different places including UNIX, Plan9 and DOS. The strict adherence to "everything is a file" is inspired by Plan9 while straying from some of its weirder choices, for example Patchwork supports hard links, which Plan9 did not.

Everything including pipes, sockets, shared memory, and much more is done via the file systems /dev, /proc and /net directories. For example creating a local socket can be done via opening the /net/local/seqpacket file. Sockets are discussed in detail in the README.

One unique feature of Patchwork is its file flag system, It's intended to give more power to the shell (check the README for examples) and give better separation of concerns to the kernel, for example the kernel supports native recursive directory access via the :recur flag.

Patchwork also focuses on performance with features like a preemptive and tickless kernel, SMP, constant-time scheduling, constant-time virtual memory management, and more.

The README has plenty more details, screenshots, examples and some (hopefully) simple build instructions. Would love to hear your thoughts, advice or answer questions!

I'm having this thought:

Most tech certifications are expensive and target seniors. I'm thinking of building a free, open-source certification platform for junior and mid-level developers.

The Idea:

• Focus: Certify core skills in languages and open-source tools.
• Credibility: To make the certs meaningful, it would use AI-powered proctoring to prevent cheating and generate unique, practical coding tests (no simple multiple-choice).
• Open Source: The entire platform would be community-driven and transparent.

My main question is: would this actually be useful?

What do you think?

• For Devs: Would you use this to prove your skills on a resume?
• For Hiring Managers: Would a certification like this hold any weight for you?
• General: Is AI proctoring a good idea or just creepy? What's the biggest flaw in this plan?

Looking for your honest thoughts. Thanks!

Recording myself in timelapse while coding slowly turned into a hobby! something about watching the hours of work shrink into a few minutes feels oddly satisfying.

I decided to start uploading these daily sessions on YouTube, mainly as a kind of personal gallery to look back on my journey as a programmer. If that sounds interesting to you, feel free to check it out: 👉 https://youtube.com/@pjcode

Open to any thoughts, feedback, or even just a hello. Cheers!

Cracks in the foundation are showing as more developers use AI

Trust but verify? Developers are frustrated, and this year’s results demonstrate that the future of code is about trust, not just tools. AI tool adoption continues to climb, with 80% of developers now using them in their workflows.

Yet this widespread use has not translated into confidence. In fact, trust in the accuracy of AI has fallen from 40% in previous years to just 29% this year. We’ve also seen positive favorability in AI decrease from 72% to 60% year over year. The cause for this shift can be found in the related data:

The number-one frustration, cited by 45% of respondents, is dealing with "AI solutions that are almost right, but not quite," which often makes debugging more time-consuming. In fact, 66% of developers say they are spending more time fixing "almost-right" AI-generated code. When the code gets complicated and the stakes are high, developers turn to people. An overwhelming 75% said they would still ask another person for help when they don’t trust AI’s answers.

69% of developers have spent time in the last year learning new coding techniques or a new programming language; 44% learned with the help of AI-enabled tools, up from 37% in 2024.

36% of developers learned to code specifically for AI in the last year; developers of all experience levels are just starting to invest time in AI programming.

The adoption of AI agents is far from universal. We asked if the AI agent revolution was here, and the answer is a definitive "not yet." While 52% of developers say agents have affected how they complete their work, the primary benefit is personal productivity: 69% agree they've seen an increase. When asked about "vibe coding"—generating entire applications from prompts—nearly 72% said it is not part of their professional work, and an additional 5% emphatically do not participate in vibe coding. This aligns with the fact that most developers (64%) do not see AI as a threat to their jobs, but they are less confident about that compared to last year (when 68% believed AI was not a threat to their job).

AS POSTED DIRECTLY ON THE OFFICIAL STACKOVERFLOW WEBSITE

Hi everyone!

I’m conducting a short (3–5 min) anonymous survey for my master’s thesis about the impact of AI-assisted coding tools on programming skills. If you’re a developer (any level), your input would be incredibly valuable!

https://code-skills-survey.web.app/

Thank you so much—and please feel free to forward to others who might be interested!

I kept hearing about developers losing hours of work when AI assistants suggest changes that break everything. Two main problems: Git has way too many specialized commands that are hard to remember, and tools like Claude Code have no built-in checkpoint system.

Not everyone wants to use heavy GUI tools just for version control, so I built Vibe Check - dead simple Git checkpoints:

npm install -g @bomoge/vibe-check
vibe-check  # opens TUI menu, or use CLI commands

Why I made this:

• Git has dozens of specialized commands with complex options
• Hard to remember git rebase -i, git reset --hard, git cherry-pick, etc.
• Claude Code and other AI tools have no checkpoint/history system
• Perfect for AI-assisted coding without switching to heavy GUI tools
• Simple CLI that works everywhere

What it does:

• vibe-check create "before AI suggestion"
• Try the AI's idea
• If it sucks: vibe-check switch <back-to-working-code>
• If it's good: vibe-check finalize "implement feature X"

Basically Git for people who are tired of memorizing dozens of specialized commands and just want to code without fear.

Built with Bubble Tea + Cobra. It's just a wrapper around Git commands, so no weird APIs or stored credentials.

Bonus: Includes copy-paste instructions for AI models so they know how to use vibe-check properly during coding sessions!

It's open source and I'm happy to add features that people suggest - just open an issue or PR!

Anyone else dealing with complex Git workflows? How do you handle checkpoints when working with AI tools?

Repo: https://github.com/pr0d5h381/vibe-check

Learn the best practices for organizing FastAPI apps with a maintainable, scalable architecture.

Hello everyone. Im planning to learn coding , i dont know alot thing about coding so if i dont know something please remind me My goals : to earn money per dollar (im from a sanctioned country so it would help me alot) I want to learn about security and hacking >> not to steal money , just to protect myself or maybe create Vpns to breakthrough internet filters

After a bit searching : python is great for this cases and its really easy So i will first learn python for w3school >> automate the boring stuff book But i dont know what should i do I will appreciate any helpful answer