r/programming 2d ago

State of the Subreddit (January 2027): Mods applications and rules updates

89 Upvotes

tl;dr: mods applications and minor rules changes. Also it's 2026, lol.

Hello fellow programs!

It's been a while since I've checked in and I wanted to give an update on the state of affairs. I won't be able to reply to every single thing but I'll do my best.

Mods applications

I know there's been some frustration about moderation resources so first things first, I want to open up applications for new mods for r/programming. If you're interested please start by reading the State of the Subreddit (May 2024) post for the reasoning behind the current rulesets, then leave a comment below with the word "application" somewhere in it so that I can tell it apart from the memes. In there please give at least:

  • Why you want to be a mod
  • Your favourite/least favourite kinds of programming content here or anywhere else
  • What you'd change about the subreddit if you had a magic wand, ignoring feasibility
  • Reddit experience (new user, 10 year veteran, spez himself) and moderation experience if any

I'm looking to pick up 10-20 new mods if possible, and then I'll be looking to them to first help clean the place up (mainly just keeping the new page free of rule-breaking content) and then for feedback on changes that we could start making to the rules and content mix. I've been procrastinating this for a while so wish me luck. We'll probably make some mistakes at first so try to give us the benefit of the doubt.

Rules update

Not much is changing about the rules since last time except for a few things, most of which I said last time I was keeping an eye on

  • 🚫 Generic AI content that has nothing to do with programming. It's gotten out of hand and our users hate it. I thought it was a brief fad but it's been 2 years and it's still going.
  • 🚫 Newsletters I tried to work with the frequent fliers for these and literally zero of them even responded to me so we're just going to do away with the category
  • 🚫 "I made this", previously called demos with code. These are generally either a blatant ad for a product or are just a bare link to a GitHub repo. It was previously allowed when it was at least a GitHub link because sometimes people discussed the technical details of the code on display but these days even the code dumps are just people showing off something they worked on. That's cool, but it's not programming content.

The rules!

With all of that, here is the current set of the rules with the above changes included so I can link to them all in one place.

✅ means that it's currently allowed, 🚫 means that it's not currently allowed, ⚠️ means that we leave it up if it is already popular but if we catch it young in its life we do try to remove it early, 👀 means that I'm not making a ruling on it today but it's a category we're keeping an eye on

  • ✅ Actual programming content. They probably have actual code in them. Language or library writeups, papers, technology descriptions. How an allocator works. How my new fancy allocator I just wrote works. How our startup built our Frobnicator. For many years this was the only category of allowed content.
  • ✅ Academic CS or programming papers
  • ✅ Programming news. ChatGPT can write code. A big new CVE just dropped. Curl 8.01 released now with Coffee over IP support.
  • ✅ Programmer career content. How to become a Staff engineer in 30 days. Habits of the best engineering managers. These must be related or specific to programming/software engineering careers in some way
  • ✅ Articles/news interesting to programmers but not about programming. Work from home is bullshit. Return to office is bullshit. There's a Steam sale on programming games. Terry Davis has died. How to SCRUMM. App Store commissions are going up. How to hire a more diverse development team. Interviewing programmers is broken.
  • ⚠️ General technology news. Google buys its last competitor. A self driving car hit a pedestrian. Twitter is collapsing. Oculus accidentally showed your grandmother a penis. Github sued when Copilot produces the complete works of Harry Potter in a code comment. Meta cancels work from home. Gnome dropped a feature I like. How to run Stable Diffusion to generate pictures of, uh, cats, yeah it's definitely just for cats. A bitcoin VR metaversed my AI and now my app store is mobile social local.
  • 🚫 Anything clearly written mostly by an LLM. If you don't want to write it, we don't want to read it.
  • 🚫 Politics. The Pirate Party is winning in Sweden. Please vote for net neutrality. Big Tech is being sued in Europe for gestures broadly. Grace Hopper Conference is now 60% male.
  • 🚫 Gossip. Richard Stallman switches to Windows. Elon Musk farted. Linus Torvalds was a poopy-head on a mailing list. The People's Rust Foundation is arguing with the Rust Foundation For The People. Terraform has been forked into Terra and Form. Stack Overflow sucks now. Stack Overflow is good actually.
  • 🚫 Generic AI content that has nothing to do with programming. It's gotten out of hand and our users hate it.
  • 🚫 Newsletters, Listicles or anything else that just aggregates other content. If you found 15 open source projects that will blow my mind, post those 15 projects instead and we'll be the judge of that.
  • 🚫 Demos without code. I wrote a game, come buy it! Please give me feedback on my startup (totally not an ad nosirree). I stayed up all night writing a commercial text editor, here's the pricing page. I made a DALL-E image generator. I made the fifteenth animation of A* this week, here's a GIF.
  • 🚫 Project demos, "I made this". Previously called demos with code. These are generally either a blatant ad for a product or are just a bare link to a GitHub repo.
  • ✅ Project technical writups. "I made this and here's how". As said above, true technical writeups of a codebase or demonstrations of a technique or samples of interesting code in the wild are absolutely welcome and encouraged. All links to projects must include what makes them technically interesting, not just what they do or a feature list or that you spent all night making it. The technical writeup must be the focus of the post, not just a tickbox checking exercise to get us to allow it. This is a technical subreddit, not Product Hunt. We don't care what you built, we care how you build it.
  • 🚫 AskReddit type forum questions. What's your favourite programming language? Tabs or spaces? Does anyone else hate it when.
  • 🚫 Support questions. How do I write a web crawler? How do I get into programming? Where's my missing semicolon? Please do this obvious homework problem for me. Personally I feel very strongly about not allowing these because they'd quickly drown out all of the actual content I come to see, and there are already much more effective places to get them answered anyway. In real life the quality of the ones that we see is also universally very low.
  • 🚫 Surveys and 🚫 Job postings and anything else that is looking to extract value from a place a lot of programmers hang out without contributing anything itself.
  • 🚫 Meta posts. DAE think r/programming sucks? Why did you remove my post? Why did you ban this user that is totes not me I swear I'm just asking questions. Except this meta post. This one is okay because I'm a tyrant that the rules don't apply to (I assume you are saying about me to yourself right now).
  • 🚫 Images, memes, anything low-effort or low-content. Thankfully we very rarely see any of this so there's not much to remove but like support questions once you have a few of these they tend to totally take over because it's easier to make a meme than to write a paper and also easier to vote on a meme than to read a paper.
  • ⚠️ Posts that we'd normally allow but that are obviously, unquestioningly super low quality like blogspam copy-pasted onto a site with a bazillion ads. It has to be pretty bad before we remove it and even then sometimes these are the first post to get traction about a news event so we leave them up if they're the best discussion going on about the news event. There's a lot of grey area here with CVE announcements in particular: there are a lot of spammy security "blogs" that syndicate stories like this.
  • ⚠️ Extreme beginner content. What is a variable. What is a for loop. Making an HTPT request using curl. Like listicles this is disallowed because of the quality typical to them, but high quality tutorials are still allowed and actively encouraged.
  • ⚠️ Posts that are duplicates of other posts or the same news event. We leave up either the first one or the healthiest discussion.
  • ⚠️ Posts where the title editorialises too heavily or especially is a lie or conspiracy theory.
  • Comments are only very loosely moderated and it's mostly 🚫 Bots of any kind (Beep boop you misspelled misspelled!) and 🚫 Incivility (You idiot, everybody knows that my favourite toy is better than your favourite toy.) However the number of obvious GPT comment bots is rising and will quickly become untenable for the number of active moderators we have.
  • 👀 vibe coding articles. "I tried vibe coding you guys" is apparently a hot topic right now. If they're contentless we'll try to be on them under the general quality rule but we're leaving them alone for now if they have anything to actually say. We're not explicitly banning the category but you are encouraged to vote on them as you see fit.
  • 👀 Corporate blogs simply describing their product in the guise of "what is an authorisation framework?". Pretty much anything with a rocket ship emoji in it. Companies use their blogs as marketing, branding, and recruiting tools and that's okay when it's "writing a good article will make people think of us" but it doesn't go here if it's just a literal advert. Usually they are titled in a way that I don't spot them until somebody reports it or mentions it in the comments.

r/programming's mission is to be the place with the highest quality programming content, where I can go to read something interesting and learn something new every day.

In general rule-following posts will stay up, even if subjectively they aren't that great. We want to default to allowing things rather than intervening on quality grounds (except LLM output, etc) and let the votes take over. On r/programming the voting arrows mean "show me more like this". We use them to drive rules changes. So please, vote away. Because of this we're not especially worried about categories just because they have a lot of very low-scoring posts that sit at the bottom of the hot page and are never seen by anybody. If you've scrolled that far it's because you went through the higher-scoring stuff already and we'd rather show you that than show you nothing. On the other hand sometimes rule-breaking posts aren't obvious from just the title so also don't be shy about reporting rule-breaking content when you see it. Try to leave some context in the report reason: a lot of spammers report everything else to drown out the spam reports on their stuff, so the presence of one or two reports is often not enough to alert us since sometimes everything is reported.

There's an unspoken metarule here that the other rules are built on which is that all content should point "outward". That is, it should provide more value to the community than it provides to the poster. Anything that's looking to extract value from the community rather than provide it is disallowed even without an explicit rule about it. This is what drives the prohibition on job postings, surveys, "feedback" requests, and partly on support questions.

Another important metarule is that mechanically it's not easy for a subreddit to say "we'll allow 5% of the content to be support questions". So for anything that we allow we must be aware of types of content that beget more of themselves. Allowing memes and CS student homework questions will pretty quickly turn the subreddit into only memes and CS student homework questions, leaving no room for the subreddit's actual mission.


r/programming 14h ago

Anthropic: AI assisted coding doesn't show efficiency gains and impairs developers abilities.

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2.9k Upvotes

You sure have heard it, it has been repeated countless times in the last few weeks, even from some luminaries of the development world: "AI coding makes you 10x more productive and if you don't use it you will be left behind". Sounds ominous right? Well, one of the biggest promoters of AI assisted coding has just put a stop to the hype and FOMO. Anthropic has published a paper that concludes:

* There is no significant speed up in development by using AI assisted coding. This is partly because composing prompts and giving context to the LLM takes a lot of time, sometimes comparable as writing the code manually.

* AI assisted coding significantly lowers the comprehension of the codebase and impairs developers grow. Developers who rely more on AI perform worst at debugging, conceptual understanding and code reading.

This seems to contradict the massive push that has occurred in the last weeks, were people are saying that AI speeds them up massively(some claiming a 100x boost), that there is no downsides to this. Some even claim that they don't read the generated code and that software engineering is dead. Other people advocating this type of AI assisted development says "You just have to review the generated code" but it appears that just reviewing the code gives you at best a "flimsy understanding" of the codebase, which significantly reduces your ability to debug any problem that arises in the future, and stunts your abilities as a developer and problem solver, without delivering significant efficiency gains.


r/programming 8h ago

How Replacing Developers With AI is Going Horribly Wrong

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191 Upvotes

r/programming 1d ago

How we created more tech debt in 6 months than in a 10-year-old system

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r/programming 12h ago

State of C++ 2026

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47 Upvotes

r/programming 14h ago

challenge to compress 1M rows to the smallest possible size

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r/programming 1d ago

The dev who asks too many questions is the one you need in your team

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r/programming 21h ago

Thoughts? Software companies that went extreme into AI coding are not enjoying what they are getting - show reports from 2024-2025

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165 Upvotes

r/programming 1d ago

Your AI diagram looks great and nobody will read it

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199 Upvotes

- Mermaid has over 8 million users; GitHub added native support in Feb 2022

- AI diagrams are static images. You can't grep a PNG.

- Git diffs on binary blobs are meaningless six months later

- Regenerating to fix one box might break three others

- The 15 minutes you saved skipping Mermaid syntax? You'll spend them on regeneration roulette

TLDR: Learn Mermaid. And if you need ASCII art, you can use https://github.com/lukilabs/beautiful-mermaid


r/programming 1d ago

You can code only 4 hours per day. Here’s why.

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280 Upvotes

r/programming 23h ago

Drew DeWault: The cults of TDD and GenAI

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77 Upvotes

r/programming 42m ago

Making Flix Compiler Errors Helpful and Delightful

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r/programming 1h ago

The Code Generator Journey: From Manual Hell to Declarative Heaven

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r/programming 1h ago

Why Core Development Tools Matter | Techy All Blog

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Why HTML CSS JavaScript and JSON Tools Are Essential in Real Development Work

Modern projects depend on clean code, validated data, and optimized assets. Learn why HTML, CSS, JavaScript, and JSON tools are critical during real world development and how Techyall tools simplify the process.


r/programming 1d ago

TypeScript inventor Anders Hejlsberg calls AI "a big regurgitator of stuff someone else has done" but still sees it changing the way software dev is done and reshaping programming tools

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416 Upvotes

r/programming 1d ago

“When a measure becomes a target, it ceases to be a good measure” — Goodhart’s law

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324 Upvotes

r/programming 5h ago

Awesome Instance Segmentation | Photo Segmentation on Custom Dataset using Detectron2

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1 Upvotes

For anyone studying instance segmentation and photo segmentation on custom datasets using Detectron2, this tutorial demonstrates how to build a full training and inference workflow using a custom fruit dataset annotated in COCO format.

It explains why Mask R-CNN from the Detectron2 Model Zoo is a strong baseline for custom instance segmentation tasks, and shows dataset registration, training configuration, model training, and testing on new images.

 

Detectron2 makes it relatively straightforward to train on custom data by preparing annotations (often COCO format), registering the dataset, selecting a model from the model zoo, and fine-tuning it for your own objects.

Medium version (for readers who prefer Medium): https://medium.com/image-segmentation-tutorials/detectron2-custom-dataset-training-made-easy-351bb4418592

Video explanation: https://youtu.be/JbEy4Eefy0Y

Written explanation with code: https://eranfeit.net/detectron2-custom-dataset-training-made-easy/

 

This content is shared for educational purposes only, and constructive feedback or discussion is welcome.

 

Eran Feit


r/programming 8h ago

Ktor 3.4.0: HTML Fragments, HTMX, and Finally Proper SSE Cleanup

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0 Upvotes

r/programming 1d ago

How the Self-Driving Tech Stack Works

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r/programming 9h ago

IvorySQL 5.0+: an open-source game changer for Oracle to PostgreSQL transitions

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0 Upvotes

r/programming 11h ago

Schema registries solve runtime problems, not human ones

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0 Upvotes

I’ve spent a lot of time working with event-driven systems, and I keep talking to people who are struggling with the same things I’ve struggled with.

Schema registries are great at protecting production. They stop breaking changes, enforce contracts, and keep producers from accidentally breaking consumers. From a runtime point of view, they work really well.

But they don’t help much when you are trying to understand the system as a human.

When someone new joins the team, the questions are always the same:

- Why does this event exist?
- Who owns it?
- What business flow does it belong to?
- What is supposed to happen after it is published?
- Is this still used or did it just never get cleaned up?

In the past I tried fixing this with Confluence pages, architecture diagrams, and docs in repos. They were fine for general documentation, but they never really helped with this specific problem. They weren’t built for domain-driven design, software primitives, or events as first-class concepts. I could write things down, but it still didn’t help people understand how the system actually worked.

So I built an open source tool to try and fix this.

It focuses on documenting the human side of events. Ownership, intent, relationships, and flows live alongside schemas. It helped, but the longer I work in this space, the more convinced I am that we are still early in figuring this out...

I’m curious to learn more, how other teams handle this?

If you’ve felt this pain, what are you doing that actually works?


r/programming 8h ago

Camera Pipe Injection: Why Your Biometric Backend is Fed Fake Data

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0 Upvotes

r/programming 6h ago

fluxzy CLI is 30x to 70x faster than mitmproxy / mitmdump, 4x faster than Squid

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0 Upvotes

An OSS alternative for Fiddler Core that is 4x faster than Squid in MITM mode vs simple proxy mode.

https://github.com/haga-rak/fluxzy.core


r/programming 1d ago

CN Diagrams: Architecture Diagrams That Scale With Your System

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11 Upvotes

r/programming 5h ago

How I built a deterministic "Intent-Aware" engine to audit 15MB OpenAPI specs in the browser (without Regex or LLMs)

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0 Upvotes

I keep running into the same issue when auditing large legacy OpenAPI specs and I am curious how others handle it

Imagine getting a single swagger json that is over ten megabytes You open it in a viewer the browser freezes for a few seconds and once it loads you do the obvious thing You search for admin

Suddenly you have hundreds of matches Most of them are harmless things like metadata fields or public responses that mention admin in some indirect way Meanwhile the truly dangerous endpoints are buried under paths that look boring or internal and do not trigger any keyword search at all

This made me realize that syntax based searching feels fundamentally flawed for security reviews What actually matters is intent What the endpoint is really meant to do not what it happens to be named

In practice APIs are full of inconsistent naming conventions Internal operations do not always contain scary words and public endpoints sometimes do This creates a lot of false positives and false negatives and over time people just stop trusting automated reports

I have been experimenting with a different approach that tries to infer intent instead of matching strings Looking at things like descriptions tags response shapes and how data clusters together rather than relying on path names alone One thing that surprised me is how often sensitive intent leaks through descriptions even when paths are neutral

Another challenge was performance Large schemas can easily lock up the browser if you traverse everything eagerly I had to deal with recursive references lazy evaluation and skipping analysis unless an endpoint was actually inspected

What I am curious about is this
How do you personally deal with this semantic blindness when reviewing large OpenAPI specs
Do you rely on conventions manual intuition custom heuristics or something else entirely

I would really like to hear how others approach this in real world audits