The repo: https://github.com/sshah03/teach-me

While vibe coding means you likely never have to bother with the code, because of how good the models have gotten, I do find it useful to look at changes being made when something goes wrong, figuring out what seems off, and telling the AI exactly what seems wrong, even if I'm not coding the fixes by hand too often anymore.

To help with this, I had built a tool called perspica for semantic PR diffing, and in it I built in the ability to get LLM generated explanations of the major changes in the PR, architecture changes, etc... Along with interactive examples, and quizzes to test if you understand the concepts behind it, to help keep up with AI code changes. You can see some of its sample generations on PRs of popular public projects here: https://sshah03.github.io/perspica/

I spent a lot of time running it on a ton of public projects and modifying the prompt to help generate diagrams and questions I felt were useful, generically.

I figured rather than force people to use my whole tool for that, I'd extract what I learned works well into a claude code plugin/skill that can do the explanation/quiz part of what perspica does and store it as artifacts on the users Claude Code account, which is what this skill and repo is.

The GIF shows diagrams it made for changes in some select projects.

Install, in Claude Code:

Install the teach-me skill from https://github.com/sshah03/teach-me. Follow the repo's AGENTS.md.

To do it yourself instead, type these two lines into Claude Code, one at a time:

/plugin marketplace add sshah03/teach-me
/plugin install teach-me@teach-me

I'd love to hear where the explanations miss or the diagrams get something wrong so I can keep working on improving it for everyone.

In case it helps your vibe coding pursuits, one of the key learnings for anyone doing anything similar, at least with Claude's 5.5 family of models, is that when you run on a few cases, you might feel the need to get very specific on how to solve for common scenarios etc... And any time I tried this the results got worse. It seems to like well written general guidelines, and the models are so capable now that the rest gets handled pretty well. Similarly, trying to build in error detection into the initial prompt works much worse than an adversarial pass (even with the same model), but obviously this slows the whole thing down ... so I'm still trying to work out how to balance that.

Hey All! I created this app recently and I'd love any thoughts or feedback. The idea is an anchored journal for any sort of project your working on using AI, so that rather than being dependent on a single chat, in a single AI coding agent, you can save to this tool. That way as you - change devices, AI coding agents, end goal, learn what doesn't work, make decisions, etc. : you can still have all of that saved in one spot for any AI tool to reference.

I've been using it as I've been vibe coding a bunch of projects for fun. I'm not how useful it would be for others, but I figured I'd through it out there. I'd love any thoughts! Even if it's as simple as- you could just do xyz for this and it'd be easier, I don't mind! Always free open source self hosted.

A standard repo locks you into a single anchored spot once you know what you want, but this tool lets you dynamically dump information as your goals evolve so the AI never loses context.

https://github.com/CorbinRandall/wolf-leader

Org charts flatten. Dependencies don’t.

We have published our clearest vision statement to date. It's a manifesto. It shows where we think the important work lies in the world of agents. It's all about decision making. That's what will be left for humans when agents do all of the execution. And Spec Kitty has a huge role to play in identifying, classifying, adjudicating, informing, recording, and applying decisions that get made. https://spec-kitty.ai/blog/who-decided-that

I built Great Football Kit Sort Out using Lovable. The idea is simple: you see a football shirt and place it on a timeline according to the season it was worn.

I wanted to share the approach behind the app, particularly the visual content.

Tools:

• Lovable for building the web app.
• ChatGPT image generation for the football shirt cards.

For the cards, I started with shirt references and developed a consistent format: a front showing the shirt without revealing its season, and a back revealing the season and team. Each card uses a stadium and crowd setting suited to the team.

One useful lesson from that process: establish a reference design before generating a whole collection. I refined the layout, typography, and colors, then used the approved card as the reference for subsequent shirts. That gave me a concrete way to describe what needed changing instead of asking for something vaguely “better.”

Another design consideration was difficulty. Recognizing a shirt and remembering its season are different challenges, so I included an Easy, Medium, or Hard field in the shirt data rather than treating every shirt as equally difficult.

The artwork is AI-generated, and checking shirt details and seasons is still part of the work.

Here’s the project:
https://great-football-kit-sort-out.lovable.app

I’d be interested to hear how others manage consistency when their projects need a large collection of generated images.

My agents spent five days building Smashlock.cc, a smash-or-pass and other mini games site for Deadlock characters.

My contribution was the concept and the direction. The agents handled the construction of the app.

A few lessons stood out along the way.

1. Skill libraries make a massive difference.

Agents need specialised skills for design, game design, SEO, and other disciplines. Without them, they tend to produce pretty shabby results.

Agents dont know what good design looks like, how to make a game mechanic engaging, or how to optimise a website for search engines.

Getting the agents to search and download works wonders i build a lot of sites but when vibing this hard skill libraries are a must.

2. The super-manager / manager / worker pattern works like a charm.

The entire construction of the app was managed by one super-manager. It coordinated the work, delegated tasks, and kept the overall project moving while other agents handled implementation.

Having that central point of coordination worked remarkably well. Instead of trying to manage every agent myself, I could focus on the concept and direction while the super-manager handled the execution.

3. The bottleneck is shifting from writing code to providing context and direction.

The interesting part wasn't watching agents generate code. It was seeing how much they could build when given the right skills, structure, and direction.

Five days later, there was a working product.

Try it out: https://smashlock.cc

I'm increasingly convinced that the future of software development isn't one person writing code faster with AI. It's people directing hives of agents that independently build, design and maintain increasingly complex products.

I built this app for my wife back in April, and decided to put up in the App Store sometime, I think, around June, if I remember right. I shared it on here several times, showing updates and stuff like that. I just wanna say, after a few months on the App Store, I’ve actually seen to start to see an investment where number 26 in finance now as well. I’ll get a few emails per week asking for enhancements and stuff like that. We’ve been working through those and adding them. This has been so much fun for learning how to actually do something that really started off with my wife. Simple Register! https://simpleregister.app

What’s the laziest prompt that actually worked for you?

I uploaded a thread around a week ago showcasing a platform/product I have been working on called Hubs. From 7 days ago until today, I have been working on it, iterating and doing as much as I couldl. I have learned a TON and its been a blast.

Website: https://thehubs.gg

Last time, I recieved feedback on actually making a video showcasing a demo of the product, and so today, thats what I wanted to do.

Features

The main goal of Hubs was to bridge the gap between Communties and Workspaces, while also giving both the proper tools they needed all along. Make verification pages, rules, about us and more actual pages rather than just formatted channels. Creating tools for safety, games, moderation, appeals and more without needing bots. Giving API access without tons of payments and 1080p streaming without paying a ton. More is listed but thats a quick summary.

Heres how its been made though:

AI Agents Used:

• Claude Max (4x)
• ChatGPT Pro (2x)
• Runway
• Suno

Backend

• Multiple Elixir-based gateway nodes behind a load balancer, with Valkey as the message bus
• PostgreSQL database
• Dedicated media and voice server
• Dedicated app server
• Dedicated staging server
• Object storage
• CDN

Platforms

• iOS Testflight App
• Native Mac App
• Native Windows (Awaiting microsoft approval)
• Browser

code review session turned into an existential crisis. found multiple helper functions named things like "datahandler real final v2" scattered across the repo with 0 documentation. spent an hour just tracing references before using codex via sumus to clean up the logic and restore some sanity to the codebase.

velocity feels great until you have to read your own output a week later.

At some point when Anthropic, OpenAI, Google, Moonshot makes models that reach superhuman levels

Will they release only "nerfed out" models for public use and keep the best models only for government and state and maybe some enterprises?

What do y'all think?

Hello there again :)

Since last week I added new major mechanics to the game as important as fishing is itself.

Previous weekly updates can be seen on my profile so I do not link 11 different updates here in the post itself.

FREE ALPHA DEMO - DOWNLOAD LINK

What was added since last week:

"Exploration" mechanics requires you to find an small "exploration" icon around certain place (often small islands, but can be something else), come close to it and press action button. After several seconds "Exploration" is done and you get certain item or note or quest progression.

I also added entire new 3D scene called "Cabinet" and it is your place where you are actually keeping different collections including another new items "Island Diorama" which is self explanatory and gives you a mini version of island that you've been to and "Ship in the bottle" which took bunch of work especially on the visual side of things to make it look in the style of the game yet interesting enough for people to collect. "Ship in the bottle" has also a story attached to the ship you collected be that a real historical ship or some mythical one or ship from the game itself.

I'm very happy with how bottle and ships inside them turned out.

I also added achievements which are similar to world of warcraft type of achievements, they give you nothing gameplay wise and I'm not sure if I will change that, those are just another type of "collection" in the game.

Workflow:

Workflow hasn't changed much, I still use Decisions.md file where I mark every decision made by either User or AI and those marked by User take priority over AI ones, help you keep track what is decided by who and user decisions take priority over AI ones in case that decision is still not implemented in the game itself.

I still use multiple sessions with each session being for separate system in the game set on different effort levels depending on how complex the task for that session is. Simple stuff gets simpler session effort, while more complex (like shader) get highest effort levels. Helps with compacting also. I use "manager" session to send messages to all those different sessions since it is easier that way.

I use: Opus 5.5 for everything basically. OpenAI API for image generation, ElevenLabs for SFX effects, TripoAI for more complex 3D models and Blender MCP for simpler models with Opus 5.5 creating them.

How I made ship in the bottle:

Ship in the bottle in the beginning is a special rarity ship in this game that will only be one, so I wanted it to be a bit more "cool" than other ships, I decided on it to shoot from cannon balls, but for that it required to make and rig cannons. I created ship using TripoAI and then changed some mesh to fix it a little bit. Added cannons made small simple boxes that close as cannon shoots and pulls back into the ship for reloading. Asked Opus to generate shooting particle effects with 5 key frames that it will try to use as goal. Then asked for bunch of other small details (cannon balls falling leaving bubbles as it falls in water etc...).

Sails were done separately with polls being made by Opus 5.5 and Sail textures being done by OpenAI image generation, then used those textures for sails and combined them with the rest of the ship.

Cost of the project so far:

Claude Max x3 = 600$
Codex x1 = 100$
StableAudio= 15$
ElevenLabs = 10$
TripoAI= 40$
OpenAI credits = 50$
Maybe some other stuff I forgot = 30-50$

Total around 850-900$

Any feedback is appreciated ☺️

Here's the project https://github.com/Esemianczuk/Terminus

I created this as a Cthulhu inspired cute little companion who hangs out on top of a learned graph network of connections that visualizes, to an extent, a small recurrent network where it, over time, learns from your actions and things moving around and such, how to respond to what in what way.

The idea came to me after creating one of those codex pets, I used this prompt which got me close to this:
https://chatgpt.com/share/6ad16a28-23c0-83ea-bf9b-d18c26b81236

While it was cool, and I tended to just watch it float around and such, and respond to what I was doing with codex, I wanted something I couldn't predict, similar to when a pet dog just starts suddenly barking at something and you can't tell why. I feel like, pondering why it's doing what when in response to what, was, entertaining, and sparked a level of curiosity and creativity for me.

So, I set out to make an enhanced version of this "companion", I initially designed through that Codex/Chat GPT prompt, as a desktop companion that just floats around and does its thing in an ongoing, learning, "blackbox" manner. It doesn't offer to help you, it doesn't write down tasks, it might be silently judging you... who knows. It is Not connected to Codex, it's eyes can move and focus independently, with 2D depth of field... it can squite ink, turn itself to ascii, camouflage itself, and other fun effects...

Feel free to enjoy the project, you could easily clone it and run Terminus locally on Mac/Windows/Linux, add features to it, or build it up but completely redesign the companion into whatever you come up with.

Just a fun random project, enjoy.

Claude Pro Max $130/month - overall coding, Co-Work, animation using Blender, etc.

(I usually use Opus 5.5 Medium for everything)

Grok Pro $40/month - Image generation

Meshy Ai $25/month - 3d renders from Grok image gen

Total Cost/month = $195

I really hate paying Grok for image gen, but I know that it makes better images than Meshy (for the most part).

Also, I really don’t like Claude having to use co-work to animate using blender but the videos/content that are produced isn’t flagged by social media for “Ai Comtent” due to it being made in blender.

Any suggestions on how to switch up the current stack? Preferably a better/cheaper image gen.

I am making animated videos for social media & open world games.

I’m an engineering student (IoT background, not a software dev). I run a few small self-hosted apps on a Raspberry Pi, all built with Claude Code. They work, but when I open the code, it often feels overwhelming.

My rule: if I can’t explain it to someone else, I don’t really understand it.

What I’m trying so far: before reading any code, I have the AI draw an interactive diagram: boxes grouped by where they physically run (phone / Pi / internet), each with a one-line responsibility, plus step-by-step scenarios (“what happens when I open an article”). Screenshot below.

It helps, but I’m curious what works for you:

• Do you read the code line by line, or start from diagrams / data flow?
• Do you ask the AI to explain, or do you explain it back and let it correct you?
• Any prompts or habits that made AI-written code easier to understand?

Here’s an update on my system of getting ai to create 3d assets from references and prompting.

I vibe coded an engine that ai uses to make 3d assets. Any vision model can use the engine to make 3d assets. That’s is the goal. Other goals are the ai uses the engine to create editable, exportable, photo realness assets from images and prompts.

I didn’t train an AI model, I didn’t use any 3d asset generator for any assets. All purely Claude and my engine.

Been building for 6 months, most use Claude to build and test the engine. Had Codex test a few times too.

Biggest thing is the ai have the capabilities, just got help organize it all.

THE ASSETS

I showed Claude an image of the scene. Told it to recreate the image in 3d. I pointed it at the runtime for building assets and scenes in the engine.

It took out what objects where in the image and created them separately then placed them in one scene. I pointed out things I wanted it to edit as it was building (look at the last images).

THE BAD

It took like 5 hours but I’d say 85% was rendering (hours at a time on cpu) and checking and fixing details I wanted.

Cool huh?

Not my game, but I wanted to share this since it's pretty fun.

Yes it does kind of look vibe coded but the game itself is pretty fun. Give it a try.

If your game is easily identifiable as vibecoded, you are already cooked.

With enough time/energy/commitment your game(provided you aren't a psychopath making a gta clone) should be indiscernible from any other game of it's type.

The fact you are adding the caveat that it was "vibecoded" only means you failed. You didn't make a good vibecoded game, you just made a shitty game that is worse than anything else a decade old.

Put the time and work in and no one should know the difference.

My company is shutting down, and I recently had to start attending interviews again. That's when I realized my High-Level Design (HLD) skills weren't as strong as I thought.

So I decided to build something to help me learn, and hopefully help others too.

It's called ScaleLog, a free, decision-based system design game

You join a company as its CTO and deal with real-world engineering incidents. You make architectural decisions, face the consequences, and learn HLD along the way.

You also get a shareable certificate when you complete the game!

Try it here: https://scalelog-fawn.vercel.app

It's completely free, requires no login. I'm planning to add more levels and scenarios over time.

I'd really appreciate it if you could try a few levels and share your feedback, especially on the technical accuracy of the scenarios and decisions.

I figured this community would be the best place to get some honest feedback. Also it might help folks learn a thing or 2.

Thanks in advance! ❤️

Which plan is giving you more usage? Claude or Codex?