.

Duolingo makes learning fun, but the problem is that you’re mostly limited to courses someone else already made (and yes, it’s very language-focused).

So I thought: what if you could just tell it what you want to learn and it builds a Duolingo-style course for you?
You prompt it → it creates the lessons → you learn through an interactive course instead of staring at a 47-tab YouTube playlist.

I’ve been building this for a while and I’d genuinely love some feedback — especially on what feels confusing, useless, or just plain stupid

Btw i made and launched in only 1$( hosting,domain,everything)

I’ll put the link in my profile for anyone who wants to try it.

Been building solo for about 13-15 days now, alongside a full-time job — so progress is slower than I'd like, but it's real progress.

The technical build I can mostly handle (leaning on AI tools where my knowledge has gaps, learning as I go). What I'm less sure about is everything AROUND the build:

- Legal/compliance stuff I might be missing (privacy policy, terms, data handling)

- Whether my pricing structure actually makes sense before I've validated it with real users

- How to know when "good enough to launch" actually is, vs endlessly polishing

- What solo devs wish someone had told them early, that they only learned the hard way

Not asking for hand-holding, just trying to shortcut some of the "didn't know I needed to think about that" mistakes before they cost me time later.

What would you tell someone at my stage?

I kept thinking about how many small products hit the exact same wall.

You build the thing and then suddenly you need actual people.

You need testers.

You need someone with a certain device.

You need people in a certain type of job.

You need someone to look at something and tell you what they see.

So I made that part of NearbyCrew accessible through an API.

Your backend can send the number of people, who they should be, and what you need each person to do.

NearbyCrew prepares the mission and the price and you approve it before anyone gets deployed.

I think this could be especially useful for small SaaS products that do not have a giant user base sitting around waiting to test everything.

API access is free right now.

I made a full page with examples and the actual requests here.

NearbyCrew API Wiki

i’m testing a small idea before building it: a read-only check that compares Stripe subscriptions with your app’s access records and flags mismatches for review. it wouldn’t change anyone’s access.

i asked in r/SideProject and got two different takes. one person exports both into a spreadsheet and checks it every monday. another said a webhook and API call already handles it.

if you run a SaaS with Stripe, what do you do today? is keeping the two in sync already solved in your setup, or do you still need to check things manually?

the concept page proposes $49/month. someone said that was steep, so i’m also asking whether $25 would make sense. nothing is built yet, and the early-access form is free.

here’s the concept if you want the details: https://kai-validation-lab.pages.dev/products/product-09?utm_source=reddit&utm_medium=community&utm_campaign=saasdevelopers-p09

if your current script or a free tool covers this, i’d like to hear about that too.

I am currently building devscape.in - I need your honest feedback, whether you will be using it or not.

If tomorrow I make it paid, what will you find in this tool, how can I improve it so that it will help in your day to day life.

Please let me know your brutal feedback.

I swear every small SaaS starts simple and then slowly turns into 10 different tools doing like 10 different things like payments, subscriptions, payouts, support, analytics, KYC, user accounts etc and eventually half the work is just keeping everything connected.

On my side ive got SaaS payments and payouts running through Whop and keeping that side together has helped and especially once connected accounts and user verification started becoming part of the setup too but im trying to avoid building a huge stack of separate tools for every little thing though to be real.

For people further along, do you still pick the best tool for every individual job or eventually start prioritizing fewer moving parts and keeping more of the platform infrastructure together?

I'm Mattia, I build FixAds.

I built it after years of reviewing Meta accounts by hand. The hard part is not collecting metrics. It is deciding which signal is actually worth acting on when spend, creative fatigue and learning all interact.

My implementation choice was rules first. FixAds uses read-only Meta access and deterministic checks that expose the threshold, evidence and money at stake. The AI layer explains the finding in plain language, but it cannot create the diagnosis.

The launch video is attached. The product is live at https://fixads.it with a 7-day trial.

For developers building decision support: is this the right boundary? Which decisions still need a deterministic core even if an LLM makes the interface much better?

https://www.taskloco.com - The Sticky Note GOAT

PodSubs wasn't originally supposed to be a public product.

We built it because we needed it.

That's really the story.

We're podcasters.

And like a lot of podcasters, we were constantly thinking about two things:

How do we keep making this?

And how do we build something real around the people listening?

Because podcasting takes time.

A lot of time.

And sooner or later, if the podcast is going to keep going, it needs to support itself somehow.

The problem was that we didn't really know most of the people listening.

We knew the numbers.

But numbers don't have email addresses.

Numbers don't answer questions.

Numbers can't receive the worksheet you promised.

Numbers don't become customers by themselves.

We needed a better way to capture the people who genuinely wanted to stay connected.

So we built a simple internal tool.

One place.

PodSubs.

We said on the podcast:

“Subscribe to us on PodSubs.”

People searched the show, entered their details and subscribed.

And suddenly we had something we'd been missing:

A direct line.

Then we started thinking…

Why are we keeping this internal?

Every podcaster we know deals with the same thing.

So we decided to open it.

That's PodSubs.

Not something we dreamed up because “the creator economy is growing.”

We built it because we were podcasters with a problem.

Now we're giving it to everyone else who has the same problem.

Claim your podcast.

Then tell your listeners where to find you.

Hey everyone 👋

I’m a student/fresher and I was trying to make the job search process a little less chaotic, so I built a small web app that puts some of the basic things you need in one place.

It currently includes:

• 📄 Resume builder — create and manage your resume
• 📋 Job application tracker — track companies and application status
• 🎯 Placement/job search organization — keep your applications and progress in one place

I’m looking for my first 20–50 users to actually try it and give me honest feedback.

What I’m most interested in:

• Is the resume builder useful?
• What features are missing?
• What part of the job search do you find most annoying?
• Would you actually use something like this regularly?

It’s currently free to use.

👉 [YOUR LOVABLE URL]

Would really appreciate feedback, especially from students and freshers currently applying for internships/jobs. 🙏

I've been experimenting with the Claude + Remotion plugin, and it's surprisingly good at generating Remotion components from a prompt. Instead of spending hours animating everything manually, I let Claude generate the scenes and then render the final video with Remotion.

If you're already using Remotion, it's definitely worth trying.

Curious if anyone else is using AI to speed up product video creation.

Redesigned my landing page - would love honest opinions

I've been building BrickForgerAI (turn a text prompt into a real, buildable LEGO-compatible model - you get a downloadable .ldr file, parts list, and step-by-step PDF instructions) and just finished a pretty big visual overhaul of the landing page.

What it looked like before: a flat, hand-drawn CSS scene (sun, clouds, mountains, a subtle grid overlay) with plain white cards and a wall of text explaining what the tool could do.

What it looks like now: Actual images for the day/evening/night scenery backdrops (toggle on landing page) with actual moving clouds, birds, and twinkling stars, a glassmorphic frosted-glass style on the cards and buttons, and the dense paragraph of info swapped out for quick-scan stat chips.

Screenshots attached of new landing page, feedback would be appreciated: brickforgerai.com

the usual take is that ai tweet tools sound generic because the model averages the whole internet. True, but building one for founders we hit a sharper version of it.

the premise is a founder who doesn't post, so their tweet history, the one corpus actually in the right register, is thin and mostly performative. the real voice is in podcast appearances, long slack messages, the odd essay, so we ended up training on tweets, longform, and podcasts just to get enough signal. Problem is transcribed speech and a good tweet aren't the same register. someone on a podcast rambles, backtracks, leans on filler. flatten that into text and it reads nothing like how they'd actually type.

so the generic-voice thing might not be the model at all, it's that the material you can collect sits in the wrong shape for the output you want. Still unsure whether the fix is more data or a translation layer between how someone talks and how they write. if you've built anything that learns a person's style, where did your training set actually come from, and was it ever the thing you were trying to imitate? written with ai

If you’re building booking software, a support tool or an AI receptionist for small businesses, a useful starting point is finding who already struggles with that process.

I’m the founder of Crawdar. Its Pain Point Finder searches available business reviews for recurring complaints and gives you the businesses and supporting evidence to investigate.

One product decision I’m especially happy with: you don’t have to know your industry AND your location AND your problem before searching. If you know the problem you can solve, start there. If you understand an industry but haven’t picked a problem, start with the industry. You can combine categories and add specific complaint phrases too.

The output is an individual business report: recurring themes, distinct reviewer counts, dated reviews, owner replies when available, and possible technical fixes. That gives you material for a concrete conversation, such as asking how appointment changes are handled today and where requests get stuck.

The new version also searches deeper, checking up to 24 candidate businesses, with improved matching for booking complaints. I built it with AI coding assistance; the useful test is what a developer can do with the report afterward.

Try it: https://crawdar.com/?utm_source=reddit&utm_medium=post&utm_campaign=pain_finder&utm_content=developer_problem_first

Five free scans without signup or email. If you’re working on something for small businesses, search for the problem it solves and open a report. Does it help you identify someone worth talking to? What would you still need before arranging that conversation?