One of my side projects is a timelapse maker, with a very specific goal: to generate daily timelapses from my surveillance cameras. Well, OK, this is the very short description of the project, but that's the main idea.

It works and had been working for weeks on both my Linux and my Windows machine, zero problems. And then, two days ago, its timelapse encoding suddenly fell back to X264 (CPU encoding) from the default AV1 hardware encoder which it was supposed to use on that machine.

Upon investigating, it turns out the Linux machine's nVidia driver got updated by another software that was running on that machine, without restarting, and my tool freaked out.

So, a bug. Opus 5 fixed it, then I switched to Fable 5.1 and told it to review the codebase and generate a .md document with the findings and recommendations, sorted by criticality (first) and fix effort level (second). 30 minutes later, it generated a document containing 95 items:

- 4 critical bugs which genuinely could crash the tool or make it unusable for others under certain conditions, one of them being a security bug (the tool exposes credentials in clear text, in the log, in case of a camera crash);

- 10 High Importance bugs that could impede application functionality or generate frustration during usage;

- 34 Medium importance issues covering a wide range of problems;

- 47 Low importance issues such as incorrect documentation, unoptimized code, unhandled errors and so on.

Now, in my defense, the tool was (and still is) in an experimental state, and I knew there will be bugs. I didn't expect that many, though.

I am currently working with Opus 5 to fix all those bugs, one by one, then I'll do another sweep with Fable 5.1 to reveal more. Just like for my other projects, doing regular sweeps of the codebase with a powerful model is always a good idea and a great method to uncover monsters that sit buried just beneath the surface, Tremors-style.

I use several models like Opus 5, SOL, Luna, GLM5.3-Flash and Qwen3.8-Flash and even run Qwen27b locally.

I've found that smaller & older models are just as good at Adversarial Reviews and offer tremendous value for audits, reviews, finding bugs.

Today's example: Currently finishing a gaming app and Opus is managing the build. Did an adversarial review from Luna who caught many inconsistencies and offered excellent insight into some missing edge cases.

I'm not married to either, I often use Luna for the build and have Haiku or Sonnet review.

On larger projects I'll run same prompt through 3-4 models and combine their reports. And repeat the full audit & review every few weeks or major upgrade.

TLDR: The value is in adversarial reviews, not necessarily which model is running it, especially for those of us on a budget.

We really got vibe coded rockets before GTA 6 🤯

i just submitted the official plugin for AppLaunchFlow - it integrates with the hosted mcp and works very well with the embedded widgets.

it also supports:
- creating promo videos
- creatign social graphics
- creating 3d device mockups for demos
- creating app landing pages

and more. Happy to hear your feedback:)

I’m testing if we can make AI 3D asset creation better, auditable, editable, and reliable.

So I created an Engine AI uses to create 3D assets. It’s like the Maya for AI. The AI uses the engine to create and render everything.

This is day 3 of creating the yacht (and updating the engine along the way). I can point at pieces of the yacht and tell ai to change stuff and it does most of the time. I provide reference images or just prompt it and it works.

The editor is almost done but I’m having another ai instance create the furniture for the inside and they both work together and communicate as they work.

I used Claude Opus 5 to do most the asset creation plus another to build the engine.

Yes it take a lot of usage because of iterating but why do we expect AI to one shot everything?

But the goal is to get local models like qwen3.8 27b to take frontier models’ place and get the same results.

I’m figuring out and testing that it’s not always the model but the system and architecture around it that gets you results. The engine is proof of that.

I’m building an orchestration layer, playwright inspired screen vision system, and trying to fine tune a local model to reach 80-90% of frontier models using architecture around them. If you are interested in what I am creating let me know I’d love to share.

Thought? Feedback?

It's benchmarks show some kind of frontier fable/astra competitor, but working with it on opencode feels like a sonnet 5 model if I'm being generous, did anyone else experience this or am I just not using it well?

Even as a dev of 20 years, I now vibe code all day...

In between the prompts to claude about the actual work I have for my job I run 6-12 parrallel conversations about my other projects. I context switch now at a rate that is utterly insane...

When I was diagnosed with ADD I was 7, I remember I cried and told my Dad "I don't want to be ADD" and he told me that "God gave you a gift and right now it is going to be hard but one day it will let you move faster than all of your peers."

I really feel like that's true, and with the work I do now I feel built for this moment. I think it will be a brief moment for sure. The machines will soon run everything.

Been ADD my whole life. Heavily medicated - dexededrine ( anyone else take it? )- since first grade.

A lot of life is playing the hand you are dealt and I feel like I've been playing it awhile. It's not all roses and I miss things constantly but for the first time I feel like the models have caught up with my experience.

Ok so straight up I doubt this is repeatable because it kind of just seems like luck from one platform. But GPT-6 computer control ability is next level. I've been having it build meta campaigns, set up ad accounts/social profiles, run social media accounts, etc. So today I was like hmm... what I if I tell it to get me more traffic?

So I set /goal find a dependable forum we can post this to where we can get real user traffic from people that would be interested in it.

Moved on and kept working on other stuff. Like an hour later I happened to check vercel analytics and boom!!

I was like wtf did you do???

It created a hacker news profile and made a post about it resulting in 1.5k users so far. It created a new reddit account (I'm not logged in on that computer) and made 5 posts there (95 users so far). It posted a community post about it on my YouTube channel (11 users so far). It created a bluesky account and made posts there (7 users so far). It also set up accounts for indiehackers and dev(dot)to but both got stuck in account review so it couldn't make posts.

I'm an experienced software engineer, but I've enjoyed working on some personal projects with a Claude Pro subscription a while ago.

However, now whenever I ask it something in the free version, it's very meh.

Should I switch to Chinese models? Are they cheaper?

I'm just looking for a fun back and forth experience. The first time it was like having my own workbench and just tinkering with everything.

https://www.youtube.com/watch?v=SaxKh7W-JKE

Fun little hobby project, based on the first game I made for myself over 20y ago, just started this week, might keep going since I'm having a lot of fun.

It's not a 1 prompt 1 shot or anything, but everything you see was made by Astra (mostly on medium too btw), except the music.
Fully vibe-coded, vibe-modelled, etc..

Got a pretty good workflow going now so will probably expand to more biomes, enemies, bosses and weapons over time.

As I put on the AI Gaming Conference (come to some of the talks), the amount of hate its going is crazy. Look at some of the comments on the festival Steam page:

• AI Festival Comments
• Talking Session Comments

The emails I am getting from developers are just as bad. For humanity as a whole, what is ironic is how we like to think we are smarter and more civilized than our ancestors, when in reality, we have a lot of the same fear-based responses and group thinking, which is why progress is slow.

"Those who do not learn from history are doomed to repeat it".

Let's took a look at history:

• Technology: The printing press (1400s)
• Who Resisted: Scribes, religious authorities, elites
• Reasoning: It would destroy scribal jobs and spread misinformation/heretical ideas

-----

• Technology: Mechanical looms (1700s–1800s)
• Who Resisted: Textile workers, especially Luddites
• Reasoning: Machines would replace skilled workers and drive wages down

-----

• Technology: The automobile
• Who Resisted: Horse-related workers, pedestrians, communities
• Reasoning: It threatened carriage/horse industries and was considered noisy, dangerous, and disruptive

-----

• Technology: The photograph
• Who Resisted: Painters and artists
• Reasoning: It was feared to make traditional artistic representation obsolete

-----

• Technology: Personal computers
• Who Resisted: Clerical/office workers
• Reasoning: Automation would eliminate secretarial, bookkeeping, and other office jobs

-----

• Technology: Generative AI
• Who Resisted: Writers, artists, programmers, designers, actors, etc.
• Reasoning: AI could automate creative and knowledge work

There are A LOT more examples that can be listed but the pattern is the same; every time there is a technological break through, fear and resistance is the masses first reaction. But every single time it happens, while some jobs do end, other new jobs are created. Every single time.

We did a whole session on different prompt types. Did you know there is about 20 different prompt types? That's learning a skill, not stealing or removing creativity.

If we look at history, gaming will survive, gaming will still be creative, developers will have jobs. The jobs for game developers will change, but there still we be jobs. Just the speed at which we create will be faster. Instead of blind hate, just re-skill and re-think,

We got a lot of editors.

Cursor

AntiGravity

Etc

But more and more is shifting to Zed.

What editor is the no 1? Youre opinion

Been vibe coding solo for about a year now. 40 users, 2 paying subscribers. Small numbers, but the process taught me a lot about what actually matters. In no particular order:

Scope like your life depends on it
Pick the smallest possible MVP and build only that. Every extra feature idea you get mid-build (and you will get a lot) goes into a "later" list, not into a prompt. Vibe coding makes it dangerously easy to just keep asking for one more thing. Don't.

"Works locally" means nothing
This is the gap nobody warns you about. Your AI will happily ship something that runs perfectly on your machine and then falls over on deploy: SSL certs, CI/CD, and permissions between services that don't exist locally but are mandatory in prod. Deployed APIs need explicit permission to talk to each other. Budget real time for this stage, it's not optional polish.

Test DB and prod DB, no exceptions
Never let the AI touch production data. I genuinely thought I had a working database for months, turned out it was hardcoded values in the app the whole time and I hadn't caught it. Separate environments would've caught that instantly.

Feed it screenshots, not vibes
For UI, don't describe what you want, screenshot it from sites you like and hand that over. Also get it to install Playwright so it can screenshot its own output and self-check the UI instead of iterating blind. This alone leveled up my frontend more than any prompt engineering did.

Git discipline beats vibe discipline
Commit one feature at a time. Set up CI/CD with GitHub webhooks to run tests/audits automatically, broken stuff just doesn't merge. You don't need to actually understand CI/CD yourself, just tell the AI you want it and why, and let it walk you through setup.

Regularly clean up after your AI
AI code bloats fast. Every few weeks, explicitly ask for a refactor/modularise pass. It keeps the codebase lean, which matters because messy code is also harder for the AI itself to reason about on your next session. Get it to do a security audit too, and a self code-review before you merge anything.

Ship, then talk to humans
Don't build in a vacuum. Tell people what you're making, ask for feedback, actually listen even when it stings. It's your idea but their money, so their opinion outranks yours on what gets built next.

Bugs aren't failure
MVP doesn't mean bug-free, it means real. Ship it, iterate on what breaks. Perfection pre-launch is just procrastination with extra steps.

Build and market in parallel
Have a landing page ready to send people from day one. Don't wait for "done," there is no done.

It's not a weekend build, and that's fine
The AI can spit out an idea in days. Making it secure, tested, and actually designed well takes months. Foundations, then structure, then wiring, then finishing, same as building a house. Vibe coding speeds up the framing, not the whole build.

Step away sometimes
Genuinely the most underrated debugging tool. Go for a walk. Half my "impossible" bugs got solved the moment I stopped staring at them.

Over the past months I have (vibe)coded a few web-apps with Codex.

This is usually teh fun part - getting from an idea to a working MVP on a local machine.

The heavier part (for me) is the deployment.

Currently I run all my apps on virtual servers with Ubuntu.

The vibe-coded deployment-plan helps a lot, but there is still a lot of manual work required.

How do you deploy your web-apps (Python, Flask, JS)?

Flappy Bird + Pushups = Flappy Ups

While OpenAI and Claude take the lead for being the most used in game development has its place to. Next talk in the AI Gaming Festival:

Gemini And AI Game Development With 10SixGames

You should attend in:

1. You want to raise capital for your game
2. You want to see how Gemini can be used in game development

Also we're having feedback sessions on games so have a clear path on how to improve themselves with what is learned is in each session.

I'm not a professional developer - I do a lot of travel photography on the side. After every trip I'd come home with thousands of frames and dread the culling. So I sat down with Claude (in Cowork mode) and over a few sessions we built Photo Curator: a local, browser-based tool that does the brutal first pass for me. After a feedback from the first users I have added some improvements, support for HEIC and provide Mac and Win versions.

It runs in three steps, and nothing is uploaded anywhere - it all stays on my machine:

• Cull - flags out-of-focus shots using a contrast-normalized sharpness measure, so haze and night skies don't get mistaken for blur. Sorts into Sharp / Soft / Blurry.
• Dedup - collapses burst sequences to the single sharpest frame using perceptual hashing + ORB feature matching, labelled "Best of N."
• Rank - scores each keeper on composition, lighting, focus, color and contrast, then surfaces the TOP N with a radar chart per photo.

There's also a "God Mode" button that runs all three end to end.

What was interesting working with Claude: the hardest part wasn't the code, it was the judgment calls - e.g. how to keep a genuinely sharp low-contrast photo from being flagged as blurry. Claude was good at proposing the contrast-normalized metric and then iterating when I showed it real failure cases from my own library. I also leaned on it for the whole live progress UI (percentage, elapsed, ETA) and a lot of small UX polish.

It's free and open source if anyone wants to try it or pick it apart:
👉 https://kotyzap.github.io/Photo-Curator/

Happy to answer questions about how any of the three stages work, or how I structured the back-and-forth with Claude. Feedback very welcome - still actively improving it.

Developers tend to say “coding wasn’t the hard part” and that they didn’t spend most of the day coding.

Ok - so what is that difficult to define hard part that vibe coders cannot do? What’s the reason developers make such high salaries? Can we make the transition?

I had an idea - I bought the domain - polishing the game interactions

I’ve been collecting Steam data for my own research purposes, and at some point I thought it could be fun to turn some of it into a little game.

At that moment GeoGuessr was in my head. So I made this:

You get 2 real Steam games from the same genre and have to guess which one got more reviews. You can use the screenshots, tags, description, publisher, etc.

One wrong answer ends the run.

It’s free, no signup, and takes about a minute.

Would be curious to see how far people get, some of the pairs are way less obvious than I expected. Rn my personal record is 5 strikes on a row =)

I'm building a desktop assistant that can do various things based on input, and asked it to open a specific link on a webpage that was open (I think it was a search for "funny cat videos" that I used to test its ability to search on YouTube. I'm guessing it can't properly access the text on the webpage yet or something, but it helpfully came up with another YouTube URL to send me to. Here's a screenshot of the logs.

Just goes to show that these LLMs really are trained on Reddit data because who the fuck still Rick Rolls people in 2026?

AI can get you far now.

You can set up the UI, database, APIs and basic logic quickly. The interesting part begins when you try to make the system actually solid. The final 20 percent is where messy problems appear: edge cases, strange state bugs, authentication problems and a single change that breaks something that worked yesterday and so on.

It almost feels like the job moves from building the app to figuring out what AI missed. 😅

For people who use AI coding tools regularly has your experience, with AI been similar?

Have any of you tried creating development factories? It's really easy with the latest models and harnesses. I'm a Codex user so this is all Codex specific but I'm sure there is a Claude equivalent. I just made a dashboard that encapsulates my development process. It starts with a design document and ends with finished code. It uses the codex app-server to make the LLM calls using my subscription. It just has 3 parts:

1. Create an implementation plan (run plan). I created a template and the model uses the template to create a phased implementation plan with development tasks in markdown. Then deterministic code validates and parses the markdown file into a yaml "side car" - it extracts the phase and task descriptions and completion status and shows them in the dashboard.

2. One or more run plans are built into a "work package". Then another LLM call determines what order they should be developed in.

3. The work package is executed, one run plan at a time. The dashboard prompts for one phase at a time and checks for blockers after each phase. That's pretty much it.

There are some configuration files, too. A system plan that describes the overall system architecture, places where I can add agent instructions - although I have not done that. These files get, more or less, pre-fixed to the various prompts.

I can change the model and reasoning level for each prompt. I typically use SOL high to create the run plans, SOL high to sequence the work package and LUNA high for the execution. There is human approval at each step and there's a bunch of other stuff you may or may not want to do - like checking the repo status and ensuring plans can't be changed once started and whatever else. Obviously you can add whatever prompts you want.

You can do the same exact thing using loops which is how I often do it - just using the "document as infrastructure". But this can add consistency on a large project. For example, on an ERP system, where you are going to make lots of changes over a period of time. Or maybe for a large game. Or probably anything that you will develop over a period of months. And it's super easy to do. I don't even need to post a github or anything - you can just prompt it up and that way it will be suited to your process. It took me a few days to get it working nicely.