u/penguinothepenguin

Inspired by the higher/lower game, but for current topics of discussion, it also features a leaderboard.

Let me know what could be improved here!

https://preview.redd.it/rokklo0l5nih1.png?width=2208&format=png&auto=webp&s=93a8632ab67042bfab08c68bfa500cc08050ac6d

What Was Bigger

Playable Link: whatwasbigger.com

Platform: Web

Description: A higher/lower style game for trending memes on the internet. Was super curious about what memes and topics are actually discussed on the internet since it's inevitable that people in different surroundings are exposed to different content. I know that the project is not that large, but I would love to hear your thoughts. Thank you.

Free to Play

I’m so sick of seeing super cheap slop titles across the eShop, but after doing a little research on what Nintendo has tried to do, it seems that the problem is almost unsolvable. 

The initial reason why we see a bunch of low-effort/corn/misleading titles was the eShop’s ranking system. They would rank the titles by the number of sales. And naturally, $1.99 ($20 games with 90% discounts) were indeed getting sales just because no one treated them as a serious purchase. This is exactly how we got trashy charts/discounts sections. 

After realizing this issue, Nintendo thought it was a good idea to sort the titles by total revenue. That means a $1 game needs 60x as many sales to rank as a $60 game. And it feels like this is a deeper issue since this completely buries good indie games. 

I’m working closely with Forum to build a new kind of ranking where you can put money on what game will rise and fall, so there is a natural want to be early to good indie titles. Therefore, I might be a little biased toward how bad I think eShop is. 

People who naturally discover good indie titles just cannot do it anymore on the Switch’s native marketplace. Of course, there are ranking websites like Deku Deals and Better eShop that solve this partly. However, it is still sad (and interesting why can’t they just fix the algorithm?) that people are not able to actually discover stuff on eShop. 

Does anyone find browsing eShop an enjoyable experience? 
For people who are consistently good at discovering fire indie titles, how do you do it?

I love wearing super popular scents as well as more niche ones. But I know multiple people who almost exclusively wear fragrance from fairly unknown brands, and I've been trying to figure out reasons why.

For me, wearing a scent no one else recognizes feels like being more knowledgeable about the space than someone else and being early to a scent people will talk more about in the future. For those of you who live in the niche end of things:

• How do you discover brands like these?
• Besides the actual scent, what else do you love about lesser-known fragrances?

I've been working on a small project on the idea of being early to a niche cologne, kind of like forum.market but for scents. Part of why I'm asking.

I've been a fan of Rate Your Music, and this website has an overall rating for an album and then separate ones for every song on that album. So a 3.5 album can have a 4.2 song carrying it. I wonder why nothing like that exists for actors.

If you want to find out how good a movie is, there are a dozen different ratings and scores, but if you're curious how good/popular an actor is, there is basically nothing. And of course, rating how good an actor is as a person is kinda messed up, but I don't see a problem with judging their performance in that movie, or their overall popularity (Forum is for the popularity aspect, it seems).

I remember the Hollywood Stock Exchange was a thing a while ago, and they used actual algorithms to quantify how popular a movie/actor/director is. But the website looks like it hasn't been touched in over a decade, so I wonder what the issue was with that, because it is super interesting to look at this kind of information.

Does anything like this exist today?

A site where you rate individual performances rather than whole films. Maybe something with RYM structure?

Any modern version of what HSX was doing, like popularity rankings for actors that account for everything that actor has done?

If you write with AI you already know the tells: the throat-clearing opener, the tidy rule of three, "it's not just X, it's Y."

But I was curious to see statistically what models actually produced the most slop, so I made my own opensource benchmark: theslopindex.com

Here's how I came up with the benchmark.

1) The Baseline:

Slop can only be measured compared to stuff that already existed. So I got corpus of data for various areas of writing (email, social, chat, and essays) so that each has a human baseline.

2) Tasks

I then hand-wrote 112 written scenarios for the models to egenerate outputs to across email, Slack, social media posts, and essays (a cold email, a schedule change, a launch tweet, an argumentative essay, etc). Every model gets the identical scenarios at default settings, several samples each: and you can see all the exact outputs in my Github repo.

3) Axes

Now for how to decide to measure slop we settled with 5 dimensions.

- Conciseness (one of the most annoying parts of AI writing is how it takes 6 paragraphs to say 2 sentences)

- Templating (AI often reuses the same sentences/styles across unrelated scenarios)

- Rhythm (Variance in sentence/paragaphs, humans often switch this up while models stay p similar)

- Tells (Over used vocab and construction for stuff like "delve", "it's not just X, it's Y")

- Human Preference (I think this is most important as everything else are just heuristics for this)

Note how we DELIBERATIVELY don't have any LLM judging, I think it'd be pretty stupid to have LLMs judge LLMs

Now for the results

What really surprised me is how human preference influenced the rankings heavily. When looking at only the "mechanical" part. Fable is actually #2 on the benchmark, but when I included human preference it drops to last.

And I think this is indicative that as the models more recently have become more benchmark optimized, they've actually produced more slop than less. Which is where good prompting, harness, and more matter.

But either way would love to hear all of your thoughts :)

Everything is open: method at theslopindex.com/methodology, outputs and code linked from there.

https://preview.redd.it/zw6ckyro3ieh1.png?width=2160&format=png&auto=webp&s=9ccdac698134eb375002ec414e6e880e474c26f4

For context this post was made by a creator of slashy.com an AI-native email client that writes drafts that sound like you, not ai slop :)

https://preview.redd.it/vy0ql8ny1ieh1.png?width=2160&format=png&auto=webp&s=86bc00cf1802f13b088669ae47cb4025ce22cf08

Hey guys I made an arena where you can pick which models have more slop: https://slop-game.vercel.app/

Here's the repo: https://github.com/hgaddipati1118/slop-index

Hey guys!

I made a little ranking website comparing models by how much ai slop they produce.

Would love to get some votes from people to help with judging: https://slop-game.vercel.app/

Right now it seems GPT 5.6 is the least slop-like, and Minimax is the most

https://preview.redd.it/hcwcfywu7fdh1.png?width=1878&format=png&auto=webp&s=8d6fab175fa878d570d91b26c06b467bc37fa504

Everyone's shipping AI writing tools, AI meeting notes, AI CRMs. But the actual inbox — where knowledge workers still spend 2-3 hrs/day — mostly got "smart reply" chips and a summarize button bolted on. Nothing that changes the shape of the work.

The idea I keep circling: an AI email client that actually does the manual labor, not just assists it —

- Learns your writing voice from your full sent history, so drafts sound like you, not ChatGPT.

- Keeps per-recipient memory that compounds (knows the context of every ongoing thread).

- Triages what's actually urgent vs. noise, and tracks the follow-ups you forget.

The bet is that "assist" tools lost because they still leave you doing the work. The win is a client that clears the tail of manual 1:1 email for you.

Where I want this sub to push back:

1. Trust — would you actually let AI draft/send in your voice, or is email too high-stakes to hand over?

2. Moat — Google/Microsoft can bolt this into Gmail/Outlook tomorrow. What makes a standalone client defensible?

3. Willingness to pay — is inbox pain a "nice to have" or a real $20-30/mo problem for you?

4. Switching cost — email client is sticky. What would actually make you move?

Genuinely want the "this won't work because…" takes.

So I'm building Slashy (slashy.com) — an AI email client that tries to do the manual labor, not just assist it:

I had an idea staring at my inbox one morning that email was running my life instead of the other way around. I then was like, I'm basically a personal assistant for my own inbox.

Hence I spawned Slashy.com . It's an AI email client that learns how you write, drafts your replies, and handles the busywork — it's been a passion project I've had over the last couple of months.

Heres how it works:

Connect your Gmail, let it learn your tone from how you actually write.

Answer a few quick questions and set up your memories so it knows who matters and how you like to sound.

... thats it.

The app will automatically draft replies in your voice, sort your inbox by importance, research whoever emailed you before you reply, and nudge you when someone ghosts a thread. The AI has gotten really good at matching how I write, but it's still always evolving, and you can edit or rewrite anything that doesnt look right.

The part I actually love — I barely open the app anymore. You can run your whole inbox from your iMessage (just text it "draft a reply to Sarah saying Thursday works" or "what's on my calendar tomorrow"), from a Slack DM, or straight from Claude/Cursor over MCP. New contact it doesn't know yet just shows as Unknown, tap it, add a memory or correct the draft once, and it never gets it wrong again.

I genuinely just use this every single day, I've built weeks of history and it's wild to go back and see how much email it's quietly handled for me. If you give it a try let me know!

Also if you do try it please let me know any feedback you have! I'd love to make it better.

**fyi it's a paid tool with a free trial so I won't pretend it's free, and heads up a couple keyboard shortcuts are still being remapped so one or two might feel off the first session, already fixing that, but in case you sign up and notice. & it's SOC 2 and never trains AI on your data 😄

Hi, I am the founder of a startup. I have been growing very fast for past couple of months as We are already a 2 person team and one intern with us, but the number of support mails and follow‑ups are blasting our inboxes and draining our time.

I was reserching and come here to search. How you manage your mail

If hiring an EA will Work or Using Mail Client like superhuman or Slashy work for you

I've been researching accelerators for our small AI startup and wanted to share where I've landed and hear from people who've actually been through one. From everything I've gathered, Y Combinator still seems to be more about the network and the brand than the money — alumni keep telling me the real value is the doors it opens for years afterward, not the three months itself. Techstars sounds more hands-on with mentorship,but the quality seems to swing a lot depending on which city or vertical program you join. And the AI-specific programs look great on paper, but they feel crowded now, where just saying "we use AI" isn't enough and you really need traction to stand out.

The thing I keep hearing across all of them is that getting in has less to do with the idea and more to do with founder signal — how fast you ship, your traction slope, and whether you can explain your wedge in one clean sentence.

So I'm curious for those who've done it: was it actually worth the time and equity, and which one would you apply to if you were starting today?

Would love honest takes rather than the usual listicle answers.

Google redesigned every Workspace icon this week, Gmail, Drive, Docs, Calendar, the whole set, swapping the flat look for glossy AI-era gradients. The internet immediately roasted them: too shiny, too generic, hard to tell apart. Everyone's arguing about the gradients. I think the gradients are the least interesting part, and there's a lesson in here that's way more useful if you're building something.

Google told us exactly why it did this. The redesign is tied to its AI strategy, the new Gemini-era visual language. Read that plainly: Google changed the icons to signal that email is now an AI product. Not to make email an AI product. To signal it. The gradient is basically a press release you install on your phone.

Here's the tell. The icon got a whole new visual era. The inbox underneath got nothing. Open Gmail after the redesign and it's the same reverse-chronological pile it's been since 2004, every message weighted the same, newsletters next to your boss next to a receipt, all of it demanding the same manual triage from you every morning. They gave the envelope an AI gradient and didn't make one part of the actual job lighter.

This is the oldest move in business, and the reason it matters to anyone here is that founders do the exact same thing at small scale constantly. When a product can't or won't change what it fundamentally does, it changes how it looks and calls it progress. New logo. New landing page. A "2.0" that's the same product with a different font. It feels like momentum, and it lets you announce transformation without doing the slow painful work of actually transforming the thing people use.

The contrast that makes this obvious is what AI-native actually means. There's a difference between bolting AI onto an existing product (a gradient, a "summarize" button, a chat box in the corner) and building the product around AI from the first principle. The AI-native version of email isn't a prettier inbox, it's an inbox that does the reassembly for you, pulls the thread and the calendar and who the person is into one place, drafts the reply with that context, and leaves you to approve it.

That's the thing I'm building with Slashy, and I'm not claiming we've nailed it, only that it's a fundamentally different bet than restyling the icon. One changes what the product does. The other changes what it looks like and hopes you read it as the same thing.

The reason Google can get away with the surface version is the same reason it's dangerous for the rest of us to copy. Google has two billion locked-in users, so it never has to fix the real experience, it just has to look current. You don't have that moat. If you're pre-traction and you catch yourself redesigning the logo or rewriting the homepage for the third time, it's worth asking honestly whether you're improving the product or avoiding it.

The lesson I keep coming back to: watch what you reach for when something feels off. If your instinct is to change the surface, the brand, the colors, the name, it's usually a sign the core is either fine and you're procrastinating, or broken and you don't want to look at it. Google's redesign was procrastination at scale. They made email look like the future and left the actual experience stuck in 2004.

Genuine question for the founders here: what's the most expensive "surface" project you've shipped, a rebrand, a redesign, a relaunch, that you later realized was you avoiding the real problem? And how did you catch yourself?

Background: I write a lot during the day, mostly email and scheduling, and I was losing the first 90 minutes of every morning to it. I'd been using Claude for drafting but in the dumbest possible way, copy the email out, paste it into a chat, paste the reply back. So I spent a few weeks actually wiring it into the inbox properly and figuring out what works.

Here's what I figured out that nobody really says:

The copy-paste loop is the whole problem. The value of an AI on your email isn't that it writes faster, it's that it can see the context you'd otherwise gather by hand. The second you're copy-pasting, you've thrown that away, because you're still the one digging up the calendar, the prior thread, and who the person is. Connecting it directly so it can actually read those is the difference between a toy and a real time save.

Context beats cleverness. A model guessing about your week writes confident nonsense. The same model that can see your calendar and your last three emails with someone writes the reply you would have written. Most of what feels like "the AI isn't smart enough" is actually "the AI can't see anything." Fix the access, not the prompt.

On the how, since this is the part that stumped me: I ended up connecting Claude through AI- native MCP like Slashy, which is what let it actually read my mail and calendar instead of me pasting things in. The mechanism matters less than the principle, MCP is just the thing that gives the model real access, but that's the piece that turned it from a chat

I copy into, to something that already has the context when I ask.

Give it a job, not a goal. "Manage my inbox" produces garbage. "Draft a reply to this using the thread and my calendar, and I'll approve it" produces something useful. Narrow, specific tasks with you in the loop work. Open-ended autonomy doesn't.

Keep yourself on the send. This is the one I'd push hardest. Let it read, draft, summarize, and prep all day, but do not let it send anything on its own. Email is irreversible and one wrong message costs more than all the time you saved. Draft-and-approve is the setup that actually survives past week two.

The biggest win wasn't speed, it was the context-switching. Once it could assemble who-this-is, the last thread, and my availability into one place, I stopped opening three tabs per reply. That round trip, twenty-plus times a day, was where the morning was actually going, not the typing.Still tuning the exact setup. Curious if anyone here has genuinely integrated an AI into their inbox in a way that stuck, versus the ones who tried it and quietly went back to doing it all by hand?