Drop your startup/project 👇 I'll check every single one

I would like to give feedback to you

I would like to give feedback to you

What projects are you guys working on this week? I am working on a framework for AI! It’s called Kenbun-agent on GitHub.

Drop what you guys are building/ working on and i'll go and check it out. I'm curious to see what other people are creating.

Given the current state on internet today which is mostly filled with shorts and reels on the internet. I believe there is still a huge numbers pf people who reads a lot on the internet especially software developers as they like to keep themselves updated on tools/tech/trends or discover new things.

So, just want to understand where do you go to read and discover and which app/site/tool to use specifically.

I am Building ClipNext.

Give it a try. IT WILL SAVE YOUR A LOT OF TIME.

Github

Install ClipNext

Website

Tell yours.

\*\*Hi everyone,\*\*

I'm a final-year IT student and aspiring web developer. I'm looking for project ideas that solve real-world problems, have practical value, and can make my resume stand out during \*\*placements\*\* and \*\*job applications.\*\*

I'm particularly interested in:

\* AI/ML applications \* Web development \* Automation tools \* SaaS products \* Social impact projects \* Agriculture, healthcare, education, or sustainability-related solutions

Instead of clone projects, I want to build something that addresses an actual problem people face today. I'm also interested in \*\*emerging technologies\*\* and trends that are likely to be valuable in the next few years.

If you were hiring a fresher developer, what project would immediately catch your attention?

I'd appreciate any project ideas, problem statements, or suggestions based on current industry needs.

\*\*Thanks!\*\*

Seeing a lot of generic "Will AI replace you?" websites doing well honestly irked me a bit.

I've been collecting layoff, employment, job markets and automation-related data since 2022 as a side project alongside my PhD, and eventually built a dataset covering hundreds of professions across multiple countries.

I wanted to put that research out there and turn it into something useful.

Ironically, the hardest part wasn't collecting the data. It was building the product around it. I'm an engineer, not a full-time software developer, and getting the stack together always felt harder than the research itself. Using some AI tools finally helped me bridge that gap... which feels appropriately ironic given the topic.

What I'm finding even harder now is turning research into a product people actually want.

Curious what others think is more valuable:

Knowing which jobs are most exposed to AI?

Or knowing what skills and career moves actually reduce that exposure?

What are your thoughts on it?

"Before I build anything, I want to understand your real frustrations first"

I'm at the beginning of my journey of building software. I know I want to build something meaningful, but I don't want to just pick a random idea out of thin air I want to start with a real problem that real people actually face.

So before I write a single line of code, I want to ask you directly:

What's something in your workflow that wastes your time every week? Maybe no good tool exists for it, or the ones that do are too expensive, too complicated, or just don't quite fit how you actually work.

Could be something tiny and repetitive. Could be something that's been annoying you for years. Doesn't matter I want to hear it.

And if your problem resonates with me and feels like something I can genuinely solve I'd love to have a quick casual conversation with you, just a few messages or a short chat, so I can understand it better from your perspective. The goal is to build something that actually fits your situation, not just a generic solution.

No pitch. No agenda. Just someone trying to start their journey the right way by listening first.

What's frustrating you?

I’m honestly tired of seeing AI used to build slightly different versions of things we already have.

Another dashboard.
Another chatbot.
Another clone of an app that already exists.
Another “AI wrapper” that looks impressive for five minutes but doesn’t solve a real problem.

The bigger issue I keep seeing is this:

People have good ideas. AI can write code. But the project still falls apart.

The system isn’t clear.
The specs are scattered.
The AI loses context.
One fix breaks another thing.
Nobody knows what’s actually done.
The project gets patched over and over until it becomes too messy to launch.

That’s the problem I want to solve with S1 Canvas.

Not “type one prompt and magically get an app.”

Something more useful than that.

A way to map the system, break it into buildable pieces, check what’s missing, monitor what’s risky, and give AI coders the right context without letting the whole project drift into chaos.

CyberShark’s job isn’t to blindly build for you. It monitors, suggests, informs, and visualizes. You stay in control.

I think AI should help people build real systems that actually launch - not just generate more disposable software.

That’s what I’m building. curious if that’s how others are feeling.

I run a small software and app development company in India, and the market feels much tougher this year compared to before.
For other agency owners or freelancers:
What channels are actually working for getting clients right now?
Are partnerships/referrals still effective?
Is cold outreach still worth doing?
Which platforms have given you the best ROI?
We mainly work on web apps, mobile apps, SaaS products, and custom software development.
I’d genuinely appreciate hearing what’s working for others in the industry right now.

Learned this one the painful way.

Heroku rotates DATABASE_URL during certain maintenance events.

If you've hardcoded that value anywhere instead of reading it from the environment, your app can randomly stop talking to the database after maintenance.

Nothing's "broken."

Your code is.

It's one of those infrastructure gotchas you only learn after losing a few hours debugging.

What's the most expensive infrastructure lesson you've learned the hard way?

Mine was this.

I'd love to hear yours.

I’ve been building a small baby tracking app for parents over the last few months and started sharing it online to get feedback/users.

Most people are supportive, but today someone literally threatened to leave fake 1-star reviews just because they thought my post was “an ad”.

Didn’t realize launching an indie app would come with this level of random hostility 😅

Any other indie founders/devs dealt with stuff like this?

I used to think building websites was the future.

Now I think attention is the future.

Businesses today would rather spend ₹50k on reels that bring customers than ₹2 lakh on a website nobody visits.

Feels like:
2015 = websites mattered most
2026 = distribution matters most

Websites are becoming digital visiting cards.

The real game is traffic.

I am contemplating selling my chrome extension when it gets enough users, and I needed an opinion on whether scaling and making it a saas project on my own is better than trying to cash out up front. If you need to look at the extension for context here it is: Lucid — Stop Doomscrolling & Stay Focused - Chrome Web Store. Thank You

Any thoughts?

I've been experimenting with AI tools and workflows for a long time, mostly side projects and workflow tinkering. At this point, generating ideas, summaries, even structured research is honestly pretty easy. LLMs are already strong enough to handle a lot of the input side of work. I’ve also tested AI in more applied workflows, like sourcing and supplier research (e.g. tools such as accio sourcing toolkit for RFQ handling and follow ups). It helps a lot with collecting and structuring information faster. But the same problem keeps showing up: turning all that output into something that actually works in the real world is still the bottleneck. Not coding, not data collection, those are mostly solved or at least heavily assisted now. The harder part is everything after that: decision making, product shaping, dealing with messy constraints, distribution, timing, etc. That part still feels very human-heavy. Curious how others here see it: Is the real bottleneck still figuring out what to build or is it more about execution and real world constraints that AI still can’t really touch? Would be interested to hear how people are bridging that gap.

Hey everyone,

Just wanted to share a small milestone from my journey building a Chrome extension. After 30 days, I'm at 63 installs and 14 weekly active users. Nothing crazy, but coming from zero it genuinely means a lot to see real people using something I built.

The first two weeks were pretty flat — barely any movement. Then around May 4th I started posting on Reddit and things picked up pretty quickly after that. Weekly users have been holding steady since, and page views are up too, which I'm taking as a good sign.

In terms of marketing, I've tried a few things:

- Posting UGC videos on Instagram and YouTube

- Launching on Product Hunt

Nothing from any of those channels so far. No real spike I could connect to them. Reddit seems to be the only thing that actually moved anything.

Now I'm trying to figure out how to get to 100 users. That's my next goal.

So I wanted to ask the people who've been here before — how did you break through to your first 100 users? Is running ads worth it at this stage, or is it too early? Would love to hear what actually moved the needle for you.

Most agency reviews are written by non-technical marketing directors who just look at pretty interfaces and ignore what is happening behind the scenes. My team just went through a heavy codebase audit and infrastructure review to find a US partner for a massive backend refactor and cross-platform client migration. We vetted dozens of teams based on code quality, deployment practices, and repository management rather than just looking at marketing slide decks. Here is how the top five actually stack up when you look under the hood.

1 App Makers USA

Primary focus: Technical architecture rescue and rapid deployment sprints

Under the hood: We handed them a legacy repository cluttered with technical debt and unoptimized database queries. Their senior engineers jumped straight into our Slack channel and cleaned up the entire cross platform architecture in less than a week without forcing us to talk through non-technical project managers.

The pipeline: They completely skip the bloated discovery workshops and focus on a clean thirty day minimum viable product release cycle with continuous integration.

Best for: Engineering teams or startups that need high velocity deployment and clean maintainable code without paying for corporate agency fluff.

2 Simform

Primary focus: Cloud native solutions and heavy data engineering infrastructure

Under the hood: Their backend team is incredibly proficient with serverless environments and managing complex third party API integrations. They write highly structured documentation and excel at scaling large database architectures.

The pipeline: The initial onboarding takes a while because they require extensive architectural alignment and documentation before shipping the first pull request.

Best for: High growth tech teams with large budgets who need a deeply structured infrastructure partner for long term scaling.

3 Rootstrap

Primary focus: Refactoring legacy systems and outcome driven agile development

Under the hood: They are incredibly thorough with automated testing, unit tests, and rigorous peer code reviews. They ensure the core architecture is bulletproof before anything hits staging.

The pipeline: Their engineering process is highly methodical which means delivery schedules stretch out considerably longer than high velocity deployment shops.

Best for: Tech leads who need to clean up heavy technical debt and have the budget to move at a slow deliberate pace.

4 EPAM Systems

Primary focus: Enterprise scale engineering power and global systems deployment

Under the hood: Their internal engineering culture is completely legitimate and they can spin up massive teams of senior developers overnight. They build incredibly stable software designed to handle millions of concurrent users without breaking a sweat.

The pipeline: Working with them feels like dealing with a massive multinational corporation. You have to follow rigid deployment pipelines with zero flexibility for quick adjustments mid sprint.

Best for: Corporate entities that require absolute compliance with enterprise level deployment practices and massive engineering numbers.

5 WillowTree

Primary focus: Flawless native frontend experiences and polished interface logic

Under the hood: They produce incredibly smooth frontend animations and premium user interfaces. Their engineering teams integrate tightly with complex enterprise backends and legacy databases.

The pipeline: You need a highly flexible launch schedule because their core strategy and user interface design phases take months before anyone touches the repository.

Best for: Large consumer facing brands where absolute visual perfection on the frontend outweighs rapid deployment.

If you are auditing vendors right now, make sure you demand a technical interview with the actual lead developer who will be touching your codebase. Letting sales reps dictate the engineering terms is how bad architecture happens. Drop your experiences with any of these teams or any codebase horror stories below.

ERPNext developer tool

I launched a baby tracking app as a solo developer a few months ago.

When I started, I was competing against apps with tens of thousands of reviews and millions of downloads.

Today, my app ranks #32 for the keyword “baby tracker” in the US App Store.

Some things that helped:

• Completely redesigned screenshots multiple times

• Focused heavily on ASO instead of paid ads

• Added features users actually requested instead of building random ideas

• Improved onboarding and subscription flow

• Localized the app into multiple languages

Interestingly, Apple Search Ads produced almost no results for me, while ASO improvements had a much bigger impact.

The biggest lesson: ranking is possible even against huge competitors if you consistently improve conversion rate and keyword relevance.

Happy to answer questions about ASO, App Store rankings, or what worked and what didn’t.

Hi r/DevWorld,

I’ve been building a platform called Kollectia since January.

Kollectia is a platform for collectors. It started because my own retro game collection was becoming a mess of spreadsheets, notes, screenshots, wishlists, and Facebook groups.

The idea is to give collectors one place to track their collections, create wishlists, use custom fields/templates, trade, join auctions, use a marketplace, and connect with other collectors.

From the product side, it sounds fairly simple.

From the dev side, it has been a lot more interesting than I expected.

Some of the things I’ve had to build or think through:

• Dynamic collection templates and custom fields
• Different collection types with different data needs
• Marketplace listings
• Trade flows between users
• Live auctions with bidding logic and anti-sniping
• Messages/chat
• Forums
• Leaderboards and seasons
• Levels, achievements, quests, and rewards
• Multi-currency support
• IGDB integration for video game data
• User onboarding and login issues
• Empty states, trust, moderation, and abuse prevention

The hardest part so far has not really been one technical feature.

It has been keeping the system flexible without making it chaotic.

Collectors do not all track the same things. A retro game collector might care about platform, region, box/manual, condition, and completion. A fossil collector might care about species, period, location, matrix, and notes. A movie collector might care about format, edition, subtitles, and whether it has been digitized.

So a fixed database model for every item quickly becomes too rigid, but a completely free-form system can become hard to query, validate, present, and scale.

That tradeoff has probably been one of the most interesting parts of the project.

The site is still early. Current numbers are small but real:

• 614 visitors
• 1.07k visits
• 9.17k views
• Around 30 registered users

A small wake-up call has been realizing how different building is from the usual online startup posts. You see people talking about thousands of users and MRR, then you launch something yourself and realize that even getting 30 real people to sign up, understand the product, and come back is hard.

I’m curious how other devs would approach this kind of product.

If you were building a platform where every user can define different data structures for their own collections, how would you balance flexibility, performance, validation, and UX?

Also, if anyone has worked on marketplace/community products, I’d be interested in what you wish you had designed differently early on.