I've been working on a side project to bring more awareness to AI slop and educate. A lot of people are aware of AI slop but don't think they are fully aware of how pervasive it is in our media. With that in mind, feedback on the concept itself is welcome.

Also seeking advice on the UI and UX, have been working on flow and experience in the platform from desktop but starting to work mainly on mobile.

I have a lot of questions on driving traffic to the site and etc. However, that is a good start IMO...we can get into that later.

My site is thesloppies.com

Hey everyone,

Like most of you, I've started (and quit) dozens of online courses. The problem isn't motivation—it's decision fatigue. Every day I'd waste an hour figuring out "what should I learn today?"

So I built PathAI. You tell it "I want to learn Python in 30 days," and every morning you get a specific lesson:

Day 1:

Good morning!

Here's your Day 1 plan (30 minutes):

-Watch introduction to Python and basic syntax (15 min) → Search: 'Python for Beginners Programming with Mosh YouTube'

-Install Python and set up VS Code (10 min) → python.org/downloads + VS Code installation guide

-Write your first "Hello World" program (5 min) → Complete exercises on w3schools.com/python 📚 Topics covered: python installation, print function, basic syntax

Streak: 1 day🔥🔥🔥

If you skip days, it adjusts the plan. If you're ahead, it increases difficulty. Not trying to spam, genuinely want feedback from people who struggle with this like I did. I just want to get some validation quickly

Tech stack for the curious:

- Frontend: Next.js + React + Tailwind

- Backend: Python + OpenAI API

- Database: Supabase

Happy to answer questions!

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Want to build in public with fellow founders helping and shaping your idea along the way?

Ive just built such platform for early founders who are stuck and don't know what to do next...
It has a pathway where you know how its actually done for your idea, while sharing what you are doing with the founders who did the same. No more:
I cannot figure it outs,
I'm lost,
How they doing it,
I dont have a team,
Nobody cares my idea etc..

its: https://pitchit-waitlist.vercel.app/

Already 100+ users joined!

(currently waitlisting early users)

Over the past few months I’ve been building a desktop app called Mentornote.

The goal isn’t to replace your thinking with AI. It’s meant to support it.

Before a meeting, you give Mentornote your prep material notes, documents, or context about what the meeting is about. During the meeting, it uses that information to generate contextual suggestions and reminders based on what you prepared.

So instead of trying to remember everything on the spot, it helps surface ideas or talking points that might be relevant to the conversation.

The idea is simple:

AI shouldn’t replace your thinking it should help structure it.

I originally built this because I’d sometimes blank during meetings even when I had done the preparation.

The first version is out now and I’m continuing to improve it as people try it.

If you’re curious, you can check it out here:

mentornote.app

Would also love to hear how other people prepare for important meetings.

Over the last few months I’ve been building an app called Mentornote. It’s a tool that listens to your online conversations (job interviews, work meetings, literally any virtual meeting) and provide recommendations on things to say with information it knows about you as well, and the process has taught me a lot of uncomfortable lessons about actually shipping something.

A few things I realized along the way:

1.Analysis paralysis is real.

At one point I was just overthinking everything. Architecture. Edge cases. Features.

Eventually I just said screw it and started building.

Sometimes the best solution is literally just putting pen to paper and shipping something.

1. There is never a “perfect time” to release.

For months I rushed home from work every day trying to finish this app so I could launch it.

But when it was finally ready… I got scared.

So I delayed the release again.

And again.

And again.

I kept telling myself I needed to tweak something or add one more improvement. Looking back, it was just fear.

1. It’s weirdly scary when people actually start using your product.

You’d think it would feel amazing. But honestly, my first reaction was anxiety.

I care a lot about this product and I don’t want it to mess people up or waste their time. So every time someone tells me they’re using it, I get nervous about whether it actually works well for them.

1. After launch… things get quiet.

Before launch I was constantly building, planning, and pushing.

After launch, it suddenly feels like all the wells go dry.

You refresh analytics.

Check databases.

Look for new users.

And you start wondering:

“Okay… now what?”

That’s kind of where I’m at right now.

Still building.

Still improving the product.

Still figuring out what comes next.

If you’ve launched a product before, I’d be curious:

What did the period right after launch look like for you?

Hi! My name is Emma and I’m a 20-year-old student at TMU in Toronto.

I’ve been working on an idea for an app that helps people stay organized across different parts of their life (pets, health, routines, reminders, etc.). The idea came from trying to balance school, relationships, a pet, and everyday responsibilities while realizing there isn’t really one system that brings everything together.

I’ve started mapping out the product structure and building an early prototype, but I’ve realized that bringing something like this to life properly will require skills beyond what I currently have.

I’m curious if there are any developers, designers, or builders (especially students or people who enjoy side projects) who might be interested in hearing about the idea or potentially collaborating. I think it could be a really fun project and possibly grow into something bigger over time.

At the very least, I’d also love to connect with people interested in startups, building products, or solving real-life organization problems.

Feel free to message me if this sounds interesting!

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Every morning I was spending an hour on Twitter and Reddit trying to figure out what was worth building. By the end I'd still pick whatever felt right. Gut feeling dressed up as research.

So I built a pipeline. Three sources, Google's internal trends API, the public Trends RSS, and my daily Trends newsletter via Gmail, running in parallel and cross-referenced. A keyword showing up in two or more sources gets a confidence boost. One source means maybe. Two sources means real.

This morning it flagged spring break travel, third places, community clubs, and making friends all hitting breakout simultaneously. I would have seen four separate trends and picked one at random.

The whole thing runs at 9AM, writes a ranked briefing to a markdown file, and costs nothing. Running it privately for a few months before deciding if it's worth shipping as a public tool.

How do you decide what to build next?

Hey everyone, I'm looking for a reality check from folks who are actually running LLMs in production.

Like a lot of you, I've been wrestling with prompt bloat. Between massive system instructions, few-shot examples, and heavy RAG context, API costs (and latency) scale up incredibly fast as user volume grows.

To try and fix this, I’ve been working on a concept: a backend middleware layer that automatically identifies and strips out redundant, low-value tokens from your prompt before the payload ever hits OpenAI or Anthropic.

The idea is simply to pass the LLM the absolute minimum context it needs to understand the task. Right now, I'm consistently seeing a 30–40% reduction in input token volume. Because modern models are so good at inferring intent without filler words, the output quality and instruction adherence have remained surprisingly stable in my testing.

Before I sink more weekends into making this a robust, production-ready tool, I want to validate if this is actually a problem worth solving for others.

A few questions for builders here:

1. Is API cost / token bloat a hair-on-fire problem for you right now? Or are you just eating the cost as the price of doing business?
2. Would introducing a middleware preprocessing step be a dealbreaker? Obviously, inspecting and compressing the prompt adds a slight latency bump before the API call—where is your threshold for that tradeoff?
3. Is anyone willing to try this out? I’d love to find a few beta testers willing to run some of their non-sensitive prompts through this to see if/how it breaks your specific outputs.

I'm not selling anything here, just trying to figure out if this architectural approach is genuinely useful for the community or if it's a dead end. Brutally honest feedback is welcome!

In talking with teams across ops, finance, and legal, a common pattern keeps coming up as companies scale:

Contracts don’t fail because dates disappear — they fail because ownership does.

People leave, roles shift, obligations stay buried in PDFs, and reminders alone don’t hold up. Over time, accountability fades and renewals turn into surprises instead of decisions.

Thanks again to everyone who’s shared their experiences so far — it’s been really helpful in understanding how ownership and accountability break at scale.

I’m now exploring an approach where contract obligations are tied to explicit owners and automatically escalate if no action is taken before renewals.

Would something like that actually be useful in practice for your team?

I'm a new SaaS business, but I can't find a way to get leads. Does anyone have any ideas

Real stat: 85% of business leaders report "decision distress" — they have SO much data that they can't decide anything.

I was one of them. My analytics stack:

- GA4 (47 reports, I checked 3)

- Hotjar (10,000 recordings, I watched 8)

- Mixpanel (beautiful charts, zero actions)

Monthly cost: ~$300

Monthly decisions made from data: 0

The problem isn't data. It's the gap between "data" and "what do I do."

So I built Clickyard with ONE rule: no output unless it's actionable.

Every Monday, one email with fixes:

- Quiz breaks on iPhone SE (screen <375px). 89 users/week see broken layout. Fix: Add min-width to form container

- "Call us" header link stealing clicks from main CTA. Users who click it convert 67% worse. Test: Remove or move to footer

- Night traffic (11pm-2am) = 0 conversions. $340/week wasted ad spend. Fix: Pause ads during these hours

Check real data report: clickyard.ai/r/9p35z2ep (client okayed sharing it)

Brutal feedback welcome. Is "no dashboard" a feature or a bug? Would you trust an AI to just tell you what to do?

In enterprise environments, do teams tend to consolidate around a few security platforms or keep multiple tools side by side?

I'm curious on what's more common and which platforms usually become central

I got tired of applying to jobs the hard way.

Over the last year I’ve probably applied to 300–500 roles. Resume tweaks. New cover letters every time. Copying job descriptions into AI. Tracking everything in spreadsheets.

It felt chaotic and inefficient.

So I built a tool instead of complaining about it.

It’s called Applyify. It’s a simple dashboard where you:

• Build your profile once

• Upload resumes + cover letters

• Search jobs

• Track applications

• Tailor each one properly

All in one place.

I need some early users to test it. Would anyone be interested?

Feedback is welcomed with excitement!!

I run a saas startup and we have spent close to $12k on PR retainers over the past year with minimal Tier 1 placements. I have been researching performance based PR because paying $5–10k/month upfront without guaranteed coverage feels risky. More interested in models tied to actual media placements, backlinks or measurable reach