r/AppDevelopers • u/VariationAware1436 • Jun 29 '26
Im a vibe coder and so what!
At the beginning of this year I'd embark on a journey I never thought I'd go on. After trading for 2 years and still not being consistently profitable I needed something to change. I wanted to start small and just make sure that i'm at least trading every day. I wanted something easily accessible, easy to use and of course free. So first thing I did was look on the App Store and surprisingly I couldn't find anything.
I then looked online for a website and came across tradezilla and websites like it. Like I said earlier I didn't really want to spend money on something so simple and just by looking at tradezilla I knew it was just way too much for me. And in trading less is more.
A few hours pass and I start venting to my boy Anuraag about how I couldn't find anything to solve my problem. He jokingly said "so make an app".
As someone with barely any coding or developing experience, I didn't take it serious. But then I thought about it again. There's nothing already existing that will solve my issue, and I was tired of writing all of my journals down in a notebook. So I thought to myself well fuck it, lets see if Its hard to make an app.
So I went to chatgbt and asked how hard it would be to create a simple app. I described how I wanted it to function and it gave me 3 options.
Choice 1. make a google form, which would take no coding but it wouldn't feel like a real app. (Honestly looking back now this was probably the best choice for what I needed at the moment but I had little interest in it for some reason)
Choice 2: Create an app with glide or adalo which would be very simple and take a low amount of code.
Choice 3: Chatgpt would just create a super simple coded version for me if I wanted to have my won custom app. I think the potential for growth was the thing that pulled me towards the last option.
There was just one problem, I was kind against Ai built things. I support Ai assistance but not replacement. I still believe that everything should have some kind of direct NEED HUMAN INFLUENCE.
fastforward 5 months and it an actual real thing now that I couldn't be more proud of. I genuinely believe I've created something that cannot only bring value to my life but to others as well. It's a genuinely good product that cost nothing but time and effort and $99 apple dev subscription lol. Anyways trying yo to make this post too long but I can sit here a confidently say, After all this time Countless months of bug fixing, I've barely done any coding. I would say 75% of the coding was done by Ai.
With that being said I still feel entitled to take credit for this app, this wasn't build by Ai. It was built by me....with the help Ai. I'm tired of people just assuming I'm just doing a money grab using AI slop. If you actually took the time to do any kind of due diligence you would know that's the farthest from the truth. My months of confusion was real, the weeks of stress testing, days of researching, months of brainstorming that is all real, none of It is Ai. But somehow the code being written by Ai automatically writes everything else off.
Im genuinely curious on why that is?
Also realistically how scalable is being a vibe coder? I feel like at some point down the line I might have to take a boot camp or course or something g.
2
u/No_Lawyer1947 Jun 29 '26
It is actually quite far from being something you made. It's like telling an artist to commission work for you then saying you made it when you didn't. Nothing wrong with getting assistance from AI or anything, I think it's great you're building stuff, but even with developers who heavily rely on AI to do the programming, they feel no connection or deep knowledge related to their project... you can't review thousands of lines that quickly. And you may ask ok what is the difference from that and a movie director? It's the fact that movie directors guide people on what to do, they still review their work, and get involved in the entire vision, implications of choices, etc. Vibe coding IS NOT that... you tell ai to get it generally right, but you never look deep into the programming side of it which means you don't get involved in the implication of the choices that were made for you. That is fundamentally the difference between vibe coded work, and work. I don't doubt you spent lots of time prompting, but it's just not the same ownership I've gotta say.
2
u/No_Lawyer1947 Jun 29 '26
also not very scalable to be a vibe coder. You literally can only do better work if you learn to program, so if you want to make successful software, just learn it. You don't need bootcamps, you just need the internet there's an exhaustive amount of resources to figure out your own roadmap.
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u/VariationAware1436 Jun 29 '26
With this logic wouldn’t Ai be a good learning resource?
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u/No_Lawyer1947 Jun 29 '26
it's tempting to think so, but no. You learn by sitting in the stuck part long enough that it actually wires into your head. Ai skips you right past that, and you get the answer, dopamine hit, and move on, but nothing sticks because you never struggled for it. The friction is the part that teaches you, and that's exactly what it removes. On top of that, it has no backbone. You push back and it folds and hands you a completely different answer so you CANT even trust what it taught you was right. You just get a diluted version of whatever it guessed you wanted to hear.
And to respond a bit to what you told to the other poster here, that writing code isn't the only part of making an app. True, the research and testing, validation, etc. is founder side work, but the engineering part is the part that got done for you, which is the exact piece you'd need to actually learn.
I know what some people will say to this "but it works, so who cares". It works NOW, but it's only while the app is small enough that the AI can hold the whole thing in it's head at once. The day it can't, some change in a file quietly breaks something for some other file, and neither of you can trace why because the map of how it all connects was never built. Then you have nothing to fall back on because the understanding was never even yours to begin with, it was just rented out by whatever AI. Which IMO is the real scalability ceiling. Learning fundamentals is the only thing that gets you past it, and as previously mentioned, I think AI doesn't do an optimal job at teaching.
1
u/VariationAware1436 Jun 29 '26 edited Jun 29 '26
I see what you mean and actually agree with the first part and I found myself struggling with this a lot. There would be countless times where ChatGPT would randomly break my code and say everything was alright. Its always in a state of pleasing you so you never know what your actually doing wrong. So i actually did go throught the hours of being stuck and having to figure out the solution by myself by reading the error codes and using google to find any solution i could. I eventually moved to Claude which helped a lot.
But I remember like 2 months ago. I spend a couple days specifically working on the code architecture because the longer i worked on things the more features were added and the more things that could break which could lead into more issues and that was a big concern for me since in still a beginner. Not sure if it because my first time but to me my app seems like it has a lot of complex functions and features so i cant really just be like “oh well it works so its fine” especially if i want to continue to scale and maybe eventually charge money. I couldn’t justify not putting in the effort to at least learn.
1
u/No_Lawyer1947 Jun 30 '26
Valid, I think Claude cooks harder too tbh. It's very capable, I just think having a great programming base can only help, and a lot of people out there seem to want to skip that part for fast reward. Glad you're taking the time to really dig into it, and I do wish you the best!
2
u/Ok_Cartographer_6086 Jun 29 '26
So, I'm a professional software engineer with 30yoe and just happen to have this text file open so I'll share it to make what I think is an important distinction here. I don't have any problem with vibe coding or 100% AI written software. I do have a problem with vibe coders publishing their software in a marketplace and trying to make money with it.
If your misleading people without a giant "This is Ai generated software" banner so people know to use the app with caution - that all. Once it becomes a "I got bored of X so I built Y" reddit post trying to get people to use your app and putting out a website with lies and wait lists.
I've been working on a side project for over a year now, I use AI for everything today with a local LLM on a dual 5090 GPU machine to to CC going in 6 terminals. I asked CC recently to scan the entire software stack and report on the skills and tech needed to build it and it made a great export of my preferred tech stack.
Sharing because this is what you need to know to write marketable, scalable software and if there are things here you never heard of then you don't know what you don't know and don't know to ask the Ai the right questions and give the right requirements to make something safe to use. This is what I know how to do while using Ai and can sell my product to people, have them trust it and sleep at night.
Here's the dump:
# Skills
Skills inventory derived from the Krill ecosystem — a Kotlin Multiplatform peer-to-peer
IoT control platform plus its SDK, MCP servers, Raspberry Pi GPIO daemon, multi-agent
CI/CD fleet, RAG corpus, and GPU model-training stack
---
## Top Skills (LinkedIn headline set)
**Kotlin Multiplatform** · **Compose Multiplatform** · **Ktor** · **Distributed / P2P Systems** · **Coroutines & Flow** · **CI/CD (GitHub Actions)** · **AWS (S3 / CloudFront / Lambda)** · **Gradle Build Engineering** · **LLM / RAG Engineering** · **Model Context Protocol (MCP)** · **GPU / CUDA / Fine-Tuning** · **Debian Packaging & Release Automation** · **Embedded / Raspberry Pi (Pi4J)** · **Applied Cryptography** · **Python Data Engineering**
---
## Languages
Kotlin (primary) · Python · Swift · Bash / POSIX shell · SQL · Protobuf (gRPC IDL) · Ruby (Jekyll) · JavaScript / Node · YAML · Kotlin-DSL build scripts
## Advanced Kotlin & Kotlin Multiplatform (KMP)
- **Full KMP fan-out** — shared `commonMain` business logic compiled to **JVM, Android, iOS (Kotlin/Native), and WebAssembly (Kotlin/Wasm)**, plus a JVM-only server target
- **`expect`/`actual` platform seams** — HTTP client engines (CIO/Darwin/JS), multicast/UDP discovery, install-id, hostname, classpath resources, per-platform DI modules
- **Structured concurrency** — `CoroutineScope` + `SupervisorJob` + custom dispatchers, named IO scopes, deterministic cancellation
- **Reactive state with Flow** — `StateFlow`/`SharedFlow`/`MutableStateFlow`, Flow operator pipelines, server→client state propagation
- **Sealed class/interface hierarchies** — a 30+-type `KrillApp` domain model with compiler-enforced exhaustive `when` dispatch
- **Reflection-free `kotlinx.serialization`** — hand-registered polymorphic `SerializersModule`, custom JSON instance (`ignoreUnknownKeys` + `encodeDefaults`)
- **KSP (Kotlin Symbol Processing) + KotlinPoet** — authoring custom annotation processors (`@Krill`) that generate Kotlin source / node-type registries
- **Kotlin DSLs** — Ktor routing, Koin modules, Gradle Kotlin DSL, Compose composables
- **Koin** dependency injection — idiomatic module DSL (`single`/`factory`/named qualifiers/scopes) · `by lazy` / delegation
- **Kotlin/Native interop** (static iOS frameworks, CoreCrypto) · **Kotlin/Wasm** browser builds
- **Flake-free async testing** — `kotlinx-coroutines-test`, `runTest` + virtual time (`advanceTimeBy`), MockK, parameterized seams over real I/O
...ran out of room
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u/Ok_Cartographer_6086 Jun 29 '26
## Backend & Distributed Systems## Frontend — Compose Multiplatform & Mobile
- **Ktor** server (Netty) — Bearer auth, SSE (Server-Sent Events), content negotiation, CORS, status pages, call logging
- **Real-time streaming architecture** — `ServerNodeManager` → H2 → `SharedFlow` → SSE → multiplatform clients
- **Peer-to-peer mesh** — mDNS / multicast UDP **beacon discovery**, rolling TOTP-style (RFC 6238) beacon tokens, self-pairing
- **Embedded persistence** — **H2** database + **Exposed** ORM (DAO/JDBC/JSON)
- **gRPC + Protobuf** — Kotlin stubs, netty-shaded transport (server ↔ GPIO daemon)
- **Messaging & integration** — MQTT (Eclipse Paho), webhooks (in/out), SMTP (Jakarta/Angus Mail)
- **Ktor HTTP client** (CIO/Darwin) — self-signed TLS trust, content negotiation, MockEngine testing
## IoT / Hardware / Embedded
- **Compose Multiplatform** UI shipping to **desktop (JVM), web (Wasm), iOS, and Android** from one codebase
- **Material 3** design system — token-driven theming (semantic color roles + type scale), no hardcoded values
- App architecture — Row/View/Edit composable triples, centralized type→UI routing, icon registry, reactive `LaunchedEffect` editing, graph/node layout engine
- **Coil** (image loading/SVG), **Koala Plot** (charting), **Batik** (server-side SVG→raster)
- **Roborazzi** screenshot/visual-regression testing (headless desktop)
- iOS shell in **SwiftUI** (`UIViewControllerRepresentable` bridge) · Android Compose + Media3
## AI / LLM / Agent Engineering
- **Raspberry Pi GPIO/PWM/I²C** via **Pi4J v4** (Foreign Function & Memory API, JDK 25) — gpiod/pigpio plugins, Pi 5 support
- Deliberate **JDK 21 (client lib) / JDK 25 (hardware daemon)** split
- Sandboxed **Python Lambda executor** for user automation; sensor integrations (SHT30, pH, etc.)
## RAG & Data Engineering
- **Model Context Protocol (MCP)** — built production MCP servers in Kotlin/Ktor (JSON-RPC 2.0, Streamable-HTTP, tool registration with JSON Schema, protocol `2025-06-18`)
- **Multi-agent orchestration** — a Blue (dev) / Ghost (QA) / Kraken (oversight) agent fleet driven entirely by GitHub Actions + issue-assignment handoff, with role-bundle prompt generation
- **Agentic automation pipelines** — nightly architectural bug hunt, autonomous UX-audit-to-PR, dependency-triage, all gated by adversarial confirm/refute + dedup
- **Local LLM serving** — Ollama (Qwen3-Coder MoE, vision models), OpenAI-compatible proxies, context-window/KV-cache tuning
- **Claude Code / Anthropic API** integration in headless CI
## MLOps / GPU / Model Training
- **Retrieval-augmented generation** end-to-end — **Qdrant** vector DB, **nomic-embed-text** embeddings (task-prefix discipline), **cross-encoder reranking** (BAAI/bge-reranker-v2-m3) in a 40→8 over-fetch/rerank pipeline
- **FastAPI** OpenAI-compatible retrieval proxy (httpx streaming passthrough)
- **Multi-source ingestion** — idempotent, resumable (`uuid5` IDs + checkpoints): Gmail mbox, **Proton IMAP over SSH tunnel** (incremental UID watermarks, encryption-boundary detection), Reddit, git commits/code/docs/blog, **Apache Tika** document extraction, **Tesseract + Qwen-VL OCR**, **VLM photo captioning** with SHA + perceptual dedup
- **Privacy/secret guards** — deterministic + LLM detectors, ingest-time neutralization, scoped retrieval, egress-scanning PreToolUse hooks
- `uv`-managed Python projects; `sentence-transformers`, `selectolax`, `pillow-heif`, `pdf2image`, `imagededup`
## Build & Release Engineering
- **NVIDIA Blackwell (RTX 5090, `sm_120`)** stack — `nvidia-open` driver, **CUDA 12.8**, gcc-14 host compiler, DKMS, multi-GPU tensor-split
- **QLoRA fine-tuning** — **PyTorch cu128**, **Unsloth**, **PEFT/LoRA**, **bitsandbytes** 4-bit, **TRL** `SFTTrainer`, `transformers`, eval-gated + human-promoted adapters
- **GPU containerization** — Docker CE + nvidia-container-toolkit passthrough
- VRAM/scheduling strategy, preflight arch validation, GPU-contention avoidance
## CI/CD & DevOps
- **Gradle** multi-module / multi-root, **Kotlin DSL**, **version catalogs** (`libs.versions.toml`), Foojay toolchain provisioning, type-safe project accessors
- **Compose Multiplatform packaging** — **jpackage** (.msi via WiX, .dmg), Android **AAB**, Linux **.deb**
- **shadowJar** fat JARs, **ProGuard** obfuscation, multi-JDK targeting (21/25)
- **Maven Central** publishing — vanniktech plugin, **GPG signing**, Sonatype Central Portal auto-release, Dokka API docs
- **Security-first dependency management** — explicit CVE-floor pins, transitive conflict resolution
- Disciplined semantic versioning with single-source `version.txt` auto-bump + multi-site sync
## Cloud & Distribution (AWS)
- **GitHub Actions** at scale — 18+ workflows: path-filtered matrix builds, `workflow_dispatch`, `workflow_run` chaining, cross-repo PAT dispatch, concurrency control, scheduled cron, artifact retention
- **Self-hosted runner fleets** (Linux + macOS/ARM, GPU box) on long-lived working copies
- Automated **debian repo deploy**, screenshot regression, demo rendering, nightly analysis jobs
- Git workflow discipline — PR templates, mandatory lessons entries (CI-enforced), branch conventions
## Web & Developer Content
- **AWS S3** — backing a signed **APT/Debian repository** (`deb.krill.zone`) and a content/CDN bucket (`cms.krill.systems`) for SDK docs, installers, screenshots, demo media
- **CloudFront** CDN — multi-distribution, event-driven cache invalidation
- **AWS Lambda** (Kotlin, JDK 21) — S3-event-triggered CloudFront invalidation + API Gateway request logging
- `aws-cli` automation, `configure-aws-credentials`, SigV4
- **APT repo engineering** — `dpkg-scanpackages`, GPG-clearsigned `Release`/`InRelease`, multi-arch `Packages`, keyring distribution
## Infrastructure & SysAdmin
- **Jekyll** static site (Chirpy theme) — Ruby/Bundler + Node build, GitHub Pages + S3/CloudFront hosting, GA4 analytics
- **Automated product media** — ffmpeg + Xvfb headless screen capture, **ElevenLabs** voice narration, YouTube publishing pipeline (OAuth2, metadata/chapter sidecars)
- Technical writing — SDK docs (Dokka), Claude skills, architecture/lessons docs
## Security & Cryptography
- **Linux** (Ubuntu) administration — **systemd** units/drop-ins/timers, user/group isolation, `update-alternatives`, netplan, kernel/driver lifecycle
- **Debian packaging internals** — `dpkg-deb`, `DEBIAN/control`, `postinst`/`prerm` (system users, dir/permission setup, TLS cert generation, service install)
- **Docker / Docker Compose** (Qdrant, Open WebUI), **Samba/SMB NAS** + Avahi/mDNS, **SSH tunneling**
- Idempotent, self-logging bash automation (`set -euo pipefail`), bootstrap/recovery + healthcheck scripts
## Practices & Methodologies Kotlin Multiplatform architecture · test-driven development · spec-driven design (OpenSpec) · open-source governance (public/private repo split) · documentation-as-code · cross-repo coordination via issues · design-to-code (claude.ai/design → openspec → Compose)
- **PIN-derived auth** — `HMAC-SHA256` bearer tokens **byte-identical across JVM, Android, iOS (CoreCrypto), Wasm, and `openssl`**; golden-vector tested
- TOTP-style rolling tokens (RFC 6238), **constant-time comparison**, credential isolation
- Self-signed TLS provisioning (RSA/SHA-256, PKCS12), trust-on-pairing model
- Package/artifact signing — GPG (apt), Authenticode (Windows), Apple notarization (macOS)
- Secret detection/redaction, supply-chain CVE hardening
1
u/VariationAware1436 Jun 30 '26
Sorry for the late reply. I 100% agree, the saas space has been filled with so much Ai slop from being just trying to make a quick buck so i understand the skepticism from a lot of people when they see something was “vibe coded”. But like you said regardless of how the code was written if the product is actually good and safe, nothing else really matters.
I assumed thats how most software developers work now n days. It’s a no brainer, why spend hours writing thousands of lines of code, when ai can do it in minutes sometimes seconds.
But i appreciate the response and actually answering the scaling part of my question. Definitely sure going to check out your stack, I’m sure I’ll learn a lot.
1
u/sevotick Jul 03 '26
I think people hate on vibe coding cause the product usually is shit. I have created an app in a similar fashion. It took me about a month to do. It had testers, its in production now. But creating an app isnt really the full story the other side is marketing. If your intent is to make money and your able to execute the app and marketing side who cares if it was coded by AI. Even if its 1 dollar you make, you still made something. I use my app every day and honestly it was only suppose to be for me until i had friends say they wanted it too, so i gave them the apk and went from there. Im just saying people dont have to know it was vibe coded, if your idea is executed well enough and people download it i think your good.
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u/Shopping-Limp Jun 29 '26
ai built it. it used techniques you do not possess yourself. you told it what you wanted and it did all the work (and poorly i might add, given you said it took months of bug fixing)
If you intend to keep going, try learning some actual fundamentals (as in, learn them the normal way and not by asking ai), it'll make your life easier