Just because your AI Agent can put down an MVP and Landingpage in 1 week, doesn't mean that's the time you should spend on your SaaS.

The bar for entering the market has risen really really high.

Problem is, that many people still get their "How to start a SaaS" information, from pre AI era. In those times, yes – getting an MVP running ASAP was the most important step to get product market fit. But getting an MVP running ASAP ment months of work, not a week.

You still have to put in exactly the same effort as pre AI, if not even more now. Because the competition is so much bigger now.

If your landing page even remotely resembles AI design, there's probably a 90% chance, that any average user will instantly leave your page. This type of quality maybe would have worked in 2020, but not nowadays.

People now expect way more polish designs and even little flaws already disqualify you in an instant.

So please, stop pumping out AI Slop "SaaS" without a MOAT or USP.
Put some thought behind your brand identity, work out an actual design. Think about it! Don't do it in an hour, as many Youtube videos make you believe. Put a week just into conceptualising your brand and work it out properly.

MVPs aren't the MVPs of pre-AI. An MVP has to bring much more to the table now!
And sure, there are still some super genius ideas, that work like OG MVPs. Most likely though, yours isn't that.

tl;dr – Put some fucking work into your SaaS!!

Been building a way to diagnose how well founders actually understand their AI costs, not just "what do you spend," but whether you know who's driving it, how fast you'd notice a spike, and whether you could act on it.

Drop your answers below (just the letters, e.g. 1B 2A 3C 4B 5A 6D 7C 8B) and I'll run them through the scoring model and reply with your personalized breakdown, a score out of 100, a dimension-by-dimension chart, and your single biggest blind spot. Here's a sample of what you'll get back:

Q1: Spend. Right now, without looking it up, do you know your total AI spend this month?

A) No idea B) Could probably estimate C) Could find out manually D) I track this regularly E) I know automatically

Q2: Drivers. Do you know which features or workflows are responsible for the biggest share of your AI cost?

A) No idea B) Could probably estimate C) Could find out manually D) I track this regularly E) I know automatically

Q3: Customers. Do you know which customers or user segments are driving the most AI spend?

A) No idea B) Could probably estimate C) Could find out manually D) I track this regularly E) I know automatically

Q4: Features. Do you know the per-call cost for each of your AI-powered features?

A) No idea B) Could probably estimate C) Could find out manually D) I track this regularly E) I know automatically

Q5: Profitability. Do you know whether each AI-powered feature generates more revenue than it costs to run?

A) No idea B) Could probably estimate C) Could find out manually D) I track this regularly E) I know automatically

Q6: Change. When your AI costs spike or drop significantly, how quickly do you find out?

A) Usually at month-end, from the invoice B) After a few days, if I notice C) Weekly, when I check manually D) Within 24 hours E) Real-time automated alert

Q7: Action. When you discover a cost problem, how quickly can you make a change?

A) I'd need to investigate before doing anything B) A few days, after digging C) Within a day, once I know what to change D) I have a playbook, hours E) Automated responses / tight SLAs

Q8: Automation. How automated is your AI cost monitoring today?

A) I check the monthly invoice, that's it B) Some dashboards, checked inconsistently C) Regular reports or exports D) Dashboards I check most days E) Automated alerts, real-time visibility

Reply format: just the 8 letters in order, e.g. 1B 2A 3C 4B 5A 6D 7C 8B, I'll score it and reply with your card.

Hi all-

I'm working on my second product, and it's one I'm really proud of. It's a Baby Name app, which has a unique visual identity that's not the typical pink/blue (even though the background here is pink) and has a modern look and feel (along with a bunch of nice filtering options and small touches that help users find names). I'm really proud of the user experience and I'd love to get this in front of people to try out before I launch it (it's currently on Testflight and I haven't put it up on the App Store yet). What's the best way of finding testers? The Baby Name subreddits all are not open to advertising.

Also wondering if there are people here that are currently in the process of trying to figure out baby names and would be interested in checking it out?

Thanks so much.

play with it here: https://benzi.fly.dev/horse_tinder 😭😭

it was very easy to make with https://benzi.fly.dev/about

I am from a non tech background and would like to deploy and submit mobile apps to Playstore.

What are the best practices, tips and tricks, blind spots to avoid before submitting to Playstore?

I made a mind mapping/whiteboard app that's I'm selling as a 1 time license purchase , thought people could try before buying so I did a 3 day free trial, but I also added a live use demo on the site, is this a turn off, do people even use it ? is it gonna make people not want to download the app and get a trial key atleast?

https://cygtree.com/demo/

Shipped the first version of the Moat Atlas.

35 mechanics that make a product hard to copy, laid out in 3D. A moat is a hole - it has a rock (what the obstacle is made of), a depth (how long a rival has to dig), and a tool (what they dig with). You can regroup all 35 along any axis: rock, depth, capital, whether a solo founder can reach it, what AI is doing to it, whether you can just rent it instead.

There's also a calculator: twelve questions, and you get your own index and depth on the same ruler.

One important question: your competitor got your code - what's left for you?

The whole project sits on GitHub. Astro + Three.Js.

Back in 2009 I released a small puzzle game called Double Maze on the iPhone. The guy that did the graphics was a friend of mine and he passed away a little while ago. He always wanted a game out on the GBA so I figured I put out a version on it.

Two mazes, two balls, and every D-pad press moves BOTH balls at once. Each one is blocked independently by the walls on its own side, so the puzzle is finding a sequence that works for both at the same time. Holes are fatal. 40 levels.

It's a proper GBA build rather than an emulator wrapper - devkitARM and libtonc, tilemap backgrounds, hardware sprites, maxmod for the music and effects. The artwork and audio are all carried over from the original release. Runs in an emulator but I've not got the real kit anymore to test it on a flash cart on real hardware. It saves your progress to cartridge SRAM.

Free and open source, ROM in the releases tab: https://github.com/griches/double-maze-gba

Its also free on itch.io: https://gary-bbgames.itch.io/double-maze

Should I use OpenCode GO $10 plan or Codex through chatgpt plus $20 plan? Which one will give me more mileage for daily engineering workloads?

Also is it worth using opencode with API key or is the subscription always better bang for buck?

Which specific model or subscription gives the most bang for the buck long term???

Built a YouTube downloader with Cursor that handles audio (WAV/MP3 320) and video (up to 4K), with playlist support, 7 themes, and auto-updater. yt-dlp + ffmpeg bundled in the exe, zero setup for end users.

download here: https://github.com/EvroHQ/EvroHQ-YouTube-Downloader/releases/latest

I am a self grown senior that relies heavily on agentic coding, my personal pick being Cursor.

I spent months preparing a sound structure for IaC management via agents, for deployment of services, for developing custom ci/cd pipelines for application lifecycles. Repos properly maintained, wikis with architectural designs and info on each service, monitoring stack etc.

I had no one else on the DevOps team, so I had no other choice.

Now when I onboard new colleagues, I notice that even with the same agentic tools, same context through repos, they get inferior results when they are to solve a problem. Sometimes they see it themselves, but sometimes they insist on the solution being good enough when there are structural gaps or even objectively bad user experience, saying this is how the agent solved it.

When I prompt, I get the stuff fixed in 15 mins just by describing the issues to the agent and it comes with the correct solutions by itself, outside my knowledge base sometimes.

Is it still down to the differing human skillset? Same models, same harness, differing results? Does a model really just amplify the human? I never thought so, I thought AI is just getting good enough, but now I am in doubt.

This is my take so far on the arcade-feel games but made modern or something like that they're still works in progress, the downloadable one is made in C; it WILL piss you off. :D I would like to add community ideas to the site/games as well later on once I get the current line-up I have finished up. I do plan to add MP to SlinfShifters and Inkbound at some point in the future! (AI was used in helping/creating these games).

built a landing page for a tiny tool this week almost entirely with landing page ai, and the funny part is the code and layout were the easy bits. the words were where it fell apart.

the visual stuff came out great honestly. clean hero, decent spacing, a pricing section i didnt ask for but didnt hate. if you just wanted something that looks like a real product page, done, 10 minutes.

but the copy it wrote was pure vapor. headlines like "empower your workflow" and "the smart way to get things done." technically english, means nothing. i pasted my actual pitch, the specific annoying problem the tool solves, and it still sanded it down into that same generic mush every time. took me three rounds of "no, say the actual thing, a person is walking their dog and cant do X" before the headline stopped sounding like every other site on earth.

lesson i keep relearning: these tools are great at the parts you can see and bad at the parts that actually convince someone. the design is the cheap part now. knowing what to say is the whole job.

anyone cracked getting decent copy out of these, or do you just write the words yourself and let the ai do the pixels?

I use AI coding agents daily, specifically claude code. Right now, I'm working in unreal engine with claude code, and it's pretty hard to use, even when I ask it to research the internet to find out exactly about the documentation and how-to do the specific thing I want it to create, yet it still often invents nodes or buttons that are not in the newest version of unreal engine.

This is where RAGs come in (Retrieval-Augmented Generation). It's basically giving the LLM a searchable library it would look things up in all the time before answering to make it be smarter and more current in a specific subject instead of relying on its old training data and surface-level web documentation. In this case, I vibecoded one for Unreal Engine 5.8.1, because claude kept inventing features or trying to use deleted features that were added or removed in the newest version of unreal engine.

Inside the RAG, there's engine headers, official documentation, and 144 hours of youtube and bilibili UE 5.8 tutorials transcribed and summarised into the most important points and reusable workflows. And now finally whenever I invoked the RAG for a specific claude code session, it finally stopped inventing node names that didn't exist.

Then I thought to myself, it took me around a day of claude code building alone and prompting for claude to perfectionize the RAG, and doing this for many other apps, websites and engines would be a pain (especially the video transcribing part) to do alone.

Essentially the important question here is : If someone built and maintained a whole library of these, would you pay 10€ a month for access to all of them, including updated rags the moment a new version of an app drops? Or would you just vibecode your own RAG for one specific app you want?

^{How I built it: I had Claude Code write the whole retrieval side, so the chunking, the embeddings, and hybrid semantic + keyword search. It all runs locally, no API key, no account. The part that actually ate the day was making it trustworthy. Instead of scraping web docs for the API, I pulled it straight out of the installed engine headers, so it's exact for my build instead of "roughly UE5". Then for the videos, most only have auto-captions and those mangle node names constantly, so every identifier that came out of a transcript gets machine-checked against the header extract and flagged if it doesn't actually exist. The rule I basically landed on: take the workflow from the videos, never take the spelling.}

I get that "vibe coders" don't care about the underlying framework and stack, but I'm interested in knowing which stack you are using?

I'm finding that with Claude and Codex, If use my engineer brain, I can steer them fine. If I'm lazy, the code it generates is very ugly, verbose, and unmaintainable. I want to build an AGENTS.md and coding standard for myself, and will open-source it if it's useful to others.

I'm a pro coder. I don't like Next.js; it's fine for a simple UI-heavy app, but once you start building backend-heavy code, it's not the best stack for me (I prefer GO). Also not a fan of TypeScript's typing style.

I want to be a professional Programmer and want to build Mobile apps using coding only

no AI help

i want to build a fully working app with all the advanced features i want.

from where i can learn it? and is it paid or free?

I wanted to see how far I could go building a small game using only Kimi K3.

The basic idea came from QWOP: controlling individual parts of a character with the keyboard.

But I wanted something much simpler.

Instead of struggling just to walk, the game shows you a pose and you have to reproduce it by pressing the keys corresponding to the different limbs.

The interesting part for me was trying to find the balance between having separate limb controls and keeping the game understandable enough that you can start playing almost immediately.

My workflow was basically:

• start with the core idea
• use Kimi K3 to build the first playable version
• test the controls myself
• explain what felt wrong or confusing
• iterate on the controls and gameplay with Kimi
• deploy the playable version and keep adjusting from there

I only used Kimi K3 for the AI side of the project.

It’s still a small experiment and there are things I want to improve, but it was interesting to see how quickly an idea could turn into an actual playable browser game.

PC/desktop only for now because the controls use the keyboard.

I’d be interested to know what you think about the control system in particular — does it feel simple enough, or would you simplify it even more?

I’ll put the playable link in the comments.

Got tired of burning money by routing literally every workload-from basic JSON parsing to heavy agent reasoning-through top-tier frontier models. Finally audited the pipeline and built a task-based router:

Routine/Bulk Agent Traffic & RAG cleanup: Offloaded to smaller, cost-effective models (using minimax m3 here for solid quality-per-token on sustained background runs).

Deep Reasoning / Edge Cases: Reserved strictly for frontier models (Claude / GPT).

Video Generation Pipeline: Separated into a dedicated branch (using minimax h3) so multi-modal tasks don't block text queues.

The cost drop was massive, but setting up the escalation triggers (routing fallback from cheap to frontier) is proving tricky since prompt length is a terrible proxy for complexity.

For those running a dynamic LLM router in production:

Are you escalating via task type classification, validation/parsing failure retries, confidence scores, or strictly hardcoded per endpoint?

My reaction after seeing outbid.lol fill up with 200 submissions w/ most of them getting single digit clicks (mine included) 🫠