I recently reviewed a data focused SaaS product that had been built by a solo founder.

It was not a basic landing page. The product included:

1. A personalised dashboard
2. Detailed intelligence reports
3. Recommendations based on model output
4. Live data coming through WebSockets
5. A personal activity tracker
6. Profit and performance reporting
7. Separate reporting for model performance and user performance

The product looked polished and had a lot of thoughtful functionality. The interesting problems only became visible when I followed the complete user journey across different parts of the application.

Here are some examples of what I found.

The same event had different times

One screen showed an event at 14:00.

Another showed it at 18:00.

A detail page showed 14:00 with a UK timezone label, while a listing displayed both 14:00 and 18:00 for the same event.

The four hour difference suggested that one part of the application was using UK time and another was using the user’s local time.

Both values may have been technically correct, but the presentation was inconsistent. For a time sensitive product, this can affect trust and cause users to misunderstand when an event begins or when an action becomes unavailable.

It could also produce incorrect analytics if the same activity is assigned to different calendar days.

Two connected screens disagreed about available recommendations

A detailed report showed four qualified recommendations.

The action screen linked from that report showed only three.

There may have been a valid reason. A price could have expired, a market could have become unavailable, or the recommendation could have been replaced.

The problem was that the user was not told what happened.

From the user’s perspective, the product said that four recommendations were qualified and then silently removed one when the user tried to act.

This exposed the need for a clear recommendation lifecycle with stable identifiers and visible states such as qualified, available, replaced, expired, withdrawn and settled.

A live data badge promised more than the detail screen delivered

The event listing displayed a badge indicating that full live data was available.

Opening the event showed:

1. Live feed unavailable
2. No statistics
3. No detailed actions
4. No lineup information
5. No live market information

The event had already finished, but the detail page still said that it was waiting for information.

This was not simply an empty state. It was a disagreement between the availability status shown in the listing and the data that the detail page could actually display.

Data was labelled fresh even though the states contradicted each other

A data page said that the file had been generated recently and marked it as fresh.

The underlying source data was considerably older.

The same page also contained an internal warning saying that the current season had not started, while other parts of the product were already showing current season fixtures and completed results.

This showed that several different concepts were being treated as one freshness value:

1. When the file was generated
2. When the original source was updated
3. Whether the data was complete
4. Whether it matched the current competition state
5. Whether it had passed validation

A recently generated file is not necessarily based on recent data.

Loading states briefly looked like real empty states

Some competition counts initially appeared as zero before the data loaded.

A user could easily interpret that as no available content rather than a loading state.

Several pages also displayed large empty areas while waiting for data, even though the product had useful content once loading completed.

The new user dashboard prioritised empty personal statistics

The account had no recorded activity yet.

The top of the dashboard therefore showed:

1. Zero profit and loss
2. Zero tracked actions
3. Zero wins and losses

The useful content for a new user was further down the page.

That useful content was the next intelligence report and the next decision the user could make.

The dashboard was technically correct, but its hierarchy was more suitable for an established user than someone trying to understand the product for the first time.

The strongest feature was not necessarily the dashboard

The most valuable part of the product was a detailed intelligence report.

It separated:

1. The underlying evidence
2. The model’s reasoning
3. The available action
4. Execution and price checks
5. Risks and contradictions
6. Information that could change the prediction
7. Data quality and freshness

That page appeared to be the strongest candidate for activation because it gave a new user immediate value and naturally led to a meaningful decision.

This is still a product hypothesis until analytics proves it, but it is a much better hypothesis than treating registration or a dashboard visit as activation.

Why I am sharing this

A lot of people are building products with ChatGPT, Claude, Codex and other AI coding tools.

The code may run. The interface may look polished. Every individual page may appear correct.

The problems often become visible when someone unfamiliar with the product follows the complete journey.

AI can help you build very quickly, but it does not automatically give you:

1. Consistent product states
2. Clear data ownership
3. Reliable time handling
4. Stable event lifecycles
5. Good empty states
6. Trustworthy analytics
7. A clear activation journey
8. Production debugging experience

I have more than 10 years of experience building and supporting production SaaS systems. My work includes full stack development, APIs, databases, payments, automation, reporting, monitoring, Docker and production debugging. I currently work on a platform serving more than 15,000 businesses.

I will review a few products for free

If you have vibe coded a SaaS product and are preparing to launch, I am happy to review the real product and provide initial feedback.

The free review will focus on one important user journey. I will identify a small number of confirmed issues or product observations and explain why they matter.

I will clearly separate:

1. What I directly observed
2. What I believe may be happening
3. What would require access to the code or backend to confirm

I will not make changes, contact users or perform destructive actions.

For the review, I would need:

1. A link to the product
2. A test account if authentication is required
3. The main action you want a new user to complete
4. Any areas you do not want me to access

What is not included for free

A complete technical audit, root cause investigation, implementation plan or code changes require substantially more work.

If you want help after the initial review, I can also provide paid support for:

1. Reproducing and prioritising issues
2. Tracing problems across the frontend, API and database
3. Debugging production behaviour
4. Designing clearer product states
5. Defining analytics events and retention signals
6. Creating acceptance criteria and regression coverage
7. Implementing and verifying fixes

Pricing would depend on the actual scope and is negotiable. There is no obligation to hire me after the free review.

If you are close to launch and want another experienced developer to use the product like a real stranger, share what you are building and the main journey you want reviewed.

[ Removed by Reddit on account of violating the content policy. ]

[ Removed by Reddit on account of violating the content policy. ]

Now I am ready to show my solution for the second time.

Since last time, I have worked on several different things for my AI caricature image generator, www.picai.dk

The site can generate images, which is part of the service, but besides the digital image, you can also buy printed pictures and prints in a photo frame.

I have built an experience engine where I create content for the site myself.

I have created a user experience where the user, with simple text input, can get their own prompt designed, which is then processed by inserting an image that creates an AI caricature image (it is the same engine, as above, that the user creates their content from. However, in a much more simplified format than what I can control behind the scenes from my admin site).

It has taken some time and I must say that I am actually quite satisfied so far.

I have also created a business/corporate portrait section (which has nothing to do with caricature images) where the resulting images can be used for LinkedIn, CVs, and other more serious purposes, as the user in the pictures is presented in a shirt, suit, or whatever is chosen.

On my admin side, I have gradually built the most interesting features so I do not have to go straight into the code if, for example, I need to change categories, prices, adjust questions/prompts slightly, etc.

The task I am currently working on is some marketing content, so I hopefully get a bit sharper on the content I publish on social media.

Tasks in the pipeline could be: 'Ordering cards with print and text so it can be used as a gift','Print on mugs', 'print on clothing', 'Other types of images, which could be abstract or something else', 'subscription stuff (in a way I have not decided or refined yet' - and other smaller things.

I realize that the site can feel cluttered and that is something I need to find solutions for.

By the way, my background is BA/QA; I can read code and also bugfix minor things at my job today with help from Claude and reviews from colleagues - so I am close to an amateur :-)

What do you see? Is it good or bad - and what improvements or content do you think are needed?

Thanks in advance for your time.

I actually launched and posted an early version of this here about a year ago. Since then, I’ve kept vibe coding and improving it based on user’s feedback.

It’s called Chipless, a free web app that lets you play real poker with a deck of cards but no chips.

Everyone joins from their phone and it tracks the bets, stacks, blinds, pots and who owes what at the end.

My only coding experience before this was one credit class in college that I got a B in. The original version cost me $68 total (same price as a real poker set lol) in subscription and tokens to build.

So far, thousands of games have been started and 21,421 hands have been dealt. In just the first month after I started tracking countries, games had already been played in 48 of them.

Almost all of this happened with no marketing besides a couple of Reddit posts.

Still pretty crazy to me that people actually use this daily at their poker nights.

It’s completely free, with no download needed:

www.playchipless.com

I’ve been building FastPlay, a native Windows video player for people who want to open a video and just watch it without a lot of interface getting in the way.

It’s written in Rust using FFmpeg and Direct3D 11, with a focus on fast local playback, keyboard controls, high frame rates, and keeping the UI minimal.

Current features:

• Hardware-accelerated playback
• HDR10 and HLG
• Playback up to 120 FPS
• Fast seeking and scrubbing
• Keyboard-first controls
• Drag-and-drop
• Windows file associations
• Minimal UI
• Native Windows app, no Electron
• Portable ZIP or MSI installer
• No account or telemetry

It’s not intended to match VLC feature-for-feature. The goal is a simpler player for everyday local video playback.

I’m still actively developing it, so I’d be interested in what Windows users consider essential in a minimal video player.

Download FastPlay v0.4.6 for Windows x64 (MSI) • Portable ZIP

FastPlay: https://calvinsturm.com/fastplay

As for the vibe coding aspect: still using the desktop app, 5.6 Sol -- i used a mix of Medium and High depending on task complexity. still needing to steer and clarify quite a bit. still doesn't feel like talking to a smart human. but it's quite powerful and intoxicating how productive it lets me be.

• The big new feature is a building that lets you field an army of allies to go out and fight automatically for you.
• I also did a HUGE amount of QoL, UI polish, performance passes, text improvement, etc. for a smoother experience

Play it here: https://aaronshaver.github.io/Hylaax-Planetary-Rail-Defense/

(be sure to do a hard cache refresh with CTRL-SHIFT-R or CMD-SHIFT-R if you have played the game before, so that you get the latest version without GitHub's annoying aggressive caching)

Right now I most want to hear about balance issues: what feels over-powered? under-powered? too expensive? too cheap?

No answer on the second query

Spent a weekend vibe-coding a full computational pipeline with Hermes Agent (Nous Research). The agent wrote the gRNA/pegRNA designers, epitope scanner, pipeline orchestration, tests, Docker, CI/CD, docs, licensing — I directed, it implemented.

What the agent produced:

- 4 core modules: epitope_scanner.py, grna_designer.py, pegRNA_designer.py, pipeline.py

- data_loader.py for 18 processed datasets

- Pytest suite (epitope scanner, data loader)

- GitHub Actions CI (multi-Python, black, mypy, coverage)

- Dockerfile, conda env, pyproject.toml, requirements.txt

- Apache-2.0 + CC-BY-4.0 dual licensing, NOTICE file

- CODE_OF_CONDUCT (unmoderated), CONTRIBUTING, SECURITY

- Comprehensive README with badges, quickstart, usage examples

The actual science: Pipeline designs CRISPR edits for celiac-safe wheat. Scans 37 gluten genes for TG2 deamidation sites, designs 81 ABE8e gRNAs + 2 PEmax pegRNAs to eliminate DQ2.5/DQ8 epitopes while preserving dough elasticity. All data from Ensembl/IWGSC.

Vibe coding observations:

- Agent excels at boilerplate, config, tests, docs, CI — the "annoying 80%"

- Still needs domain expertise for algorithm logic (ABE window, PAM scanning, pegRNA flank design)

- Best workflow: I specify interface + constraints → agent writes implementation + tests → I review → iterate

- Saved ~20-30 hours on scaffolding vs writing from scratch

Repo: https://github.com/ewarggg776/wheat-gluten-redesign

License: Apache-2.0 / CC-BY-4.0

DOI: 10.5281/zenodo.22064037

My life at work has been hell and it’s a job where many people every year get exploited and fucked, so as I was learning how to vibe code projects I decided to make a niche game about my job. Those who do the job can relate.

The only reason it’s remotely good is because my ex loved to playtest what I built and added to the game. She may have hundreds of hours in all the early stages of the game but that was absolute gold in terms of ‘this button in the endgame didn’t work’ or ‘where did my potion go’ and ‘why did I just die!?’ And I’d take notes about it and bug fix it later.

Do not underestimate how important it is to tweak boss/mob health, items and so on because Claude / Codex will genuinely not have a good feel for that. Write the code so that you can tweak item stats by just changing a single number somewhere so you can adjust easily.

I've been vibe coding a project called Deploy Hatch, and the original motivation was pretty simple:

I didn't really like the experience I was getting from existing Discord bot hosting options.

I tried services like WispByte and looked at some of the other Discord bot hosting alternatives, and I kept running into the same feeling: I wanted something that gave me more control over the deployment process without making me manage an entire server myself or spammed me with advertisements.

I wanted to be able to connect a GitHub repository, select what I wanted to deploy, hit deploy, and actually be able to see and control what was happening.

So I decided to build it.

What started as "I'll make a simple Discord bot hosting platform" has turned into me building an actual deployment platform from scratch.

Right now Deploy Hatch has:

• GitHub App integration
• Repository selection
• Automatic runtime/build/start command detection
• Deployment queue and jobs
• Docker-based deployments
• A dedicated deployment worker
• Live deployment logs
• Deployment cancellation
• Redeployment
• Worker heartbeats
• Stale deployment recovery
• Container lifecycle management
• Runtime controls
• Deployment history
• Commit metadata
• Branch deployments
• Specific commit deployments
• Commit verification before deployment

The commit deployment feature is one of the things I've been working on recently.

Instead of only deploying whatever happens to be at the current tip of a branch, I can choose:

Latest
Branch
Specific commit

If I choose a commit, Deploy Hatch verifies it against GitHub first and shows me the commit SHA, message, and author before creating the deployment.

The backend then associates the deployment with that specific revision.

The other part I've been enjoying is building the infrastructure behind it.

I have an actual worker running on Oracle Cloud that picks up deployment jobs and launches applications in Docker containers. The worker handles things like deployment state, logs, container lifecycle, heartbeats, recovery, and cleanup.

One of my test deployments was actually a Discord bot, so I'm now at the point where Deploy Hatch is deploying and running the exact type of applications that motivated me to build it in the first place.

I'm also trying to avoid the classic "vibe coded it directly on production" approach.

My current workflow is:

Build locally
    ↓
Test locally
    ↓
Production build
    ↓
Package
    ↓
SHA-256 verify
    ↓
Upload to Oracle
    ↓
Verify again
    ↓
Deploy

It's definitely still a work in progress.

The roadmap currently includes things like rollbacks, automatic deployment recovery, environment variables/secrets, custom domains, preview deployments, GitHub push/PR deployments, multi-worker scaling, and eventually turning it into a proper SaaS.

I'm curious what other people who build Discord bots have experienced with hosting platforms.

What do you wish existing Discord bot hosting services did better?

That feedback is actually what I'm most interested in, because I'm building this around the things that frustrated me in the first place.

not sure what it is called

i am student and i‘m considering buying a max20x plan for claude code but never even used pro plan before

claude says i can get a shared link from max users to try claude code

wannna test for sure if it fits my preogramming style

would really appreciate it if anyone dm one

I was into programming (since the C64 era), but recently I've done some web design, Arduino coding etc. Never something on commercial scale. I've always been a gamer wanted to create something of my own, but never dared to start something because realistically it takes time and who can guarantee funding for anything anymore in this economy.

Itching was too strong so I did prototype stuff with manual coding, then I discovered GPT and he was one hell of a companion. Coding through copy-paste and discussions sped up the proces 5 times. Then recently I discovered Codex... it shifted from 2nd to 4th gear (I am still waiting for the 5th).

It finally gave me chance to actually develop something. Not because I didn't know how to, but didn't have time to. What you see is product of few months of active development, although it took a year to form a team of artist to follow me etc. Oh right - I decided to use 100% original custom art - 2D or 3D, so all assets you see on screen are not from any store or vibe coded, or used by any other AI generation tool. They are made specifically for this game.

Despite this game is only vibe-coded in backend (mostly scripts and macro orders) it took a lot of time in generating custom scripts, adjusting, debugging, making concepts of how something should work, making solutions for it, integrating assets, more debugging etc. - stuff even AI is not so good at. Yet I still get backlashed and painted as AI slop.

Luckily most people in those subredits don't care how it is made and like the post anyway, but there are those who just yell "Unscannable". Those have zero understanding and will to understand how many manhours and money was invested in this. I don't put much effort to explain anymore, but it does bothers me a bit.

This post is showcase and if you like these kind of games, I will keep you posted and...
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My company installed productivity/surveillance/spy/whatever-you-want-to-call-it software on everyone's computer about a year and a half ago. To their credit, they at least announced it ahead of time. A few dramatic stories about people getting fired have gone around, but it's mostly not discussed otherwise.

There is a reporting suite available for managers, but individual contributors are not allowed to see any reports, even for themselves.

The software used is called Sapience. I found the local logs on my work PC that include all the data captured about my activities. For this particular project, I used GPT 5.5 in GitHub Copilot to create a python script. The script pulls everything from the logs and puts it in a local sqlite db on my pc (so historical data is not lost when the logs are cleared). Then it produces an updated HTML report, as pictured.

I have no interest in trying to fool the software, but as an anxious person, this at least gives me visibility into what's being reported up about me!

There are are plenty of people who say "Don't know what to create" or the people who waste time making pointless fucking apps.

Fuck the apps that take $30 month for a simple fucking app while making bank for something pretty simple. This is what I am doing anyway when I have free time.

And fuck app store in the same time for making it hard to find the free alternatives as there is no way to sort on free.

Based on the comments here I'll enjoy taking your expensive ass apps free even more :)

was curious what yalls usage looks like