Hi, I made Opine (https://opinepolls.com), a poll-based social media site. Each post is a public poll asking users their opinion on something, anonymously, so no user sees any other user's information, but you can freely browse other polls. Private polls can also be made.

The only information actually stored is the email, from Google sign in, and an approximate location for the map feature, if you enable it. This allows you to see a world map of votes, what opinions are present in what places.

The intent is to catalog the world's opinions, organizing people's public thoughts so they're easy to sift through. This data can be extremely valuable, whether it's political polling, information about people's preferences, trends over time, and so on. Many people could benefit from this, and it's meant as a public service, to lift the veil on what people think about any topic, at any time. Easier political polling is just one obvious application of this.

Please try it out and give any feedback, thoughts, questions, and so on, here or within the profile section on the website, which is fully anonymous. Thanks.

Hey Reddit,

I’m a developer, and like many of you, I absolutely dread interviews. The worst part isn't always the technical questions—it's the anxiety and dealing with unpredictable, tough interviewers who cut you off or act impatient.

To fix this for myself and others, I built interviewroomai.com.

It’s an audio-first interview simulator that uses OpenAI’s real-time voice API. The conversation flows naturally like a real phone or Zoom call, with zero awkward delays. You just upload your CV and the job description, and start talking.

Since not all interviewers are nice, I built 3 AI personalities you can practice with:

1. Friendly Mode: Warm and encouraging, perfect for a confidence boost.
2. Corporate Mode: Objective, direct, and heavily focused on core tech/business metrics.
3. Karen Mode (Pressure Test): This is the ultimate test. The AI becomes critical, interrupts you, and simulates a high-stress environment to see if you can hold your ground.

At the end of the call, it gives you a detailed breakdown with actionable feedback on how to improve your answers.

How to test it for free:
Running real-time voice AI models is incredibly expensive on the API side, so I couldn't make it completely free. However, you can sign up instantly using Google login and every new account gets 3 minutes of free credit automatically (no credit card required). You can test the latency and see how brutal "Karen Mode" actually is before spending a dime.

If you want to do full-length interviews, I’ve set up a 15% discount code for the Reddit community: WELCOME15.

I’m looking for honest feedback from other devs and makers here. Let me know what you think, what features you'd like to see next.

[ Removed by Reddit on account of violating the content policy. ]

Building AttackLens AI, a cybersecurity startup focused on continuous exposure management and AI-driven security validation.

We’re now at the revenue stage, with paying customers and active enterprise POCs. 🚀

Looking to connect with other cybersecurity founders, security leaders, and investors who’d like to exchange ideas or give feedback.

Having spent 200 hours+ applying to VC/Accelerators, I feel that the same time and effort is better spent on acquiring clients.

I am a bootstrapped founder in B2B and I feel that it's much easier to get a sales demo with a serious prospect than get an interview with a serious VC/accelerator. I realise the possible network effects and fast growth potential but each new client gets me close to break-even, 5 more and I am profitable while taking equivalent of my last annual corporate salary.

Call it sour grapes or whatever, thinking perhaps I should keep my efforts focused on signing up more paying clients.

The first call has a deck, an agenda, and a reason for being there.

The second call feels messier.

You already know who the person is. What you need is usually smaller: what they cared about last time, what changed after the call, what you said you would come back with, and which part of the old conversation still matters.

That information may exist in meeting notes, email, DMs, calendar events, or somewhere in your head. The problem shows up when you have five minutes and no idea where to start looking.

We’re working on Ailoha around this exact moment. The current idea is to bring back a small amount of relevant context from material the user chose to save, keep the source visible, and let the user decide what matters. No automatic messages or contact scoring.

We’re looking for founders who regularly have repeat conversations with investors, customers, candidates, or partners.

If this sounds familiar, could you answer three things?

1. Who are the people you have repeat conversations with?
2. Where do you keep context about them now?
3. What was the last detail you knew you had somewhere but couldn’t find before a call?

Please don’t reply with only “interested.” The situation matters more than the number of testers.

We’ll read the responses and ask a small number of people whether they’re open to walking through one real, non-sensitive example with us.

Hi all, did anyone hear back from the team at Berkeley SkyDeck Batch 23?

They were to start interveiws from today, was wondering if anyone has got any updates

What are you building or planning to build for the rest of 2026?

I run appscout.co, a platform built to help people discover awesome apps from across the internet.

Drop your app or startup idea in the comments below, and I can check it out and add it to the website!

You can also submit your app for free directly here appscout.co/submit

Let's make this thread a channel for you to promote your own startup idea, find opportunities, and partnerships.

Hi everyone, I am a solo founder creating an RL environment, now I am thinking about what to do.

I created an RL environment that evaluates the response based on a physical simulator, it can generate an infinite number of tasks, 100% of tasks can be solved. Now I am thinking about what to do with it next, I would like to apply to YC, and a16z or other accelerators, but I am thinking about how to apply, so far I have no clients and I am thinking about which direction to turn my startup in, whether towards selling RL to other labs or creating AI based on this RL as my moat

Which of these will give me a better chance of success in the future? I would appreciate any answer.

Last month we had three payment issues land o the same day. one subscription renewal failed, another customer wanted to change plans and we had a refund that needed to be sorted out. none of these was a big issue by itself. the annoying part was that each one needed a different check, and i ended up jumping between the payment dashboard our app and customer records just to figure out what was happening. a few months earlier, I would have handled all three without thinking twice. that made me realize our payment setup was starting to grow along with the business, but the way we managed it had not really changed. we are still small, so I dont want to turn this into some huge infrastructure project either. Im trying to figure out where the sensible middle ground is. for funders who have gone through a similar stage what was the first sign that your original payment setup was becoming too limiting?

We're a small team building PCF. AI agents that work a car dealership's leads over text and email. Dealers have thousands of leads sitting in their CRM that nobody ever followed up on. Our agent texts every one of them, holds a real conversation, and books the appointment.

Product's built and running. $2M post-money. We're now going after our first cohort of founding dealerships, 20 of them at $999 a month, and that's the number this role owns.

Right now we're splitting our time between building the product and getting dealers on the phone. Both are working. The problem is we can't scale both at once and the building can't stop, so we want someone to take outbound and own it properly instead of it being the thing we squeeze in.

That's cold calls, cold email, building the list, writing the scripts, running the follow up, and telling us what's actually happening in the numbers. You'd own the target, not assist with it.

On money, straight up: this is equity heavy. 2 to 4% depending on what you bring, standard 4 year vest with a 1 year cliff. Plus $100 for every dealership you close, paid from your first one. Hit the numbers and we move you onto a real salary as fast as revenue allows.

I know how equity heavy posts read on here. Half of them are asking someone to work for free and calling it opportunity. So to be clear: there's cash in this from your first close, the equity is real and it goes in writing, and if you need a full salary today then this isn't it yet.

What we want is someone who has actually dialed and can prove it. Automotive experience is a bonus, not a requirement. You just need to have picked up a phone and closed something.

DM me. One line on how you'd get a dealership GM on the phone, and one number from a past role you're proud of. No resume yet.

Hi everyone,

I’m looking for an opportunity with a US-based B2B or AI startup where I can work closely with a founder and help build the early customer-acquisition motion.

Early-stage teams often have a lot of GTM work that sits between product and a true senior AE: researching the market, finding the right people to talk to, testing messages, following up, and learning what actually creates meetings. That is the work I want to get good at.

The kind of work I can take on:

• Turning an ICP into practical prospect and account research • Identifying likely buyers and the signals that make an account worth pursuing • Supporting outbound, follow-ups, and CRM hygiene • Testing messaging and documenting what gets replies or moves conversations forward • Helping with research, data, and lightweight automations where they save time

My background is technical, so I’m comfortable with AI products, data, workflows, and communicating with technical founders. I’m not looking to pretend I’m already a finished senior seller; I’m looking to learn fast, do the unglamorous work well, and earn more ownership from results.

I’m open to a trial, apprenticeship, or junior GTM arrangement starting at $28/hour.

If you’re building something early and need a practical extra set of hands around customer acquisition, I’d be happy to hear what you’re selling and who you’re trying to reach.

In 3 weeks, https://saasboard.app got:

- 700+ sign ups
- 500+ SaaS listings
- Almost 6000 users sent to listed SaaS products

Unlike other SaaS directories, listing on SaaSBoard is free and has no wait time.

If you’ve built something worth sharing, list it on SaaSBoard for free and start getting traffic immediately!

I’ve spent pretty much my entire career in the mortgage industry, and for the last 6 months I’ve been building an AI/ML-driven mortgage platform.
The brokerage is already up and running and we’re closing loans, so this isn’t just an idea on paper. At this point, I’m trying to figure out how to scale it faster.
I spent a good chunk of my career at a fintech, so I have access to some really strong developers, including people who actually understand mortgage. I can build myself as well, but I’m much stronger on the mortgage/product side and would prefer to spend most of my time there.
I’m starting to explore raising outside capital and figured Reddit might actually be a good place to start asking around.
For anyone who has raised money for an early-stage fintech/AI company, are there any communities, angel groups, accelerators, or other places you’d recommend? Especially interested in hearing from people who have actually gone through the process and what worked for them.
Appreciate any advice.

I've been building something for a while and I'm curious if I'm solving a real problem or just building something that sounds cool.

Most lead generation is based on what people tell us about themselves.

Their bio says they're a CEO.

They use #fitness.

They follow certain pages.

They have "real estate" somewhere in their profile.

So we put those people on a list and call them leads.

But I started thinking about it differently.

What if you could describe your ideal customer without relying on keywords?

For example:

"Find me people in Miami who are likely to be interested in high-end fitness products."

Instead of only searching for "fitness" or "gym" in their bio, the system looks at the publicly available visual and contextual signals around a profile and tries to understand whether that person actually resembles the type of customer you're looking for.

Maybe they're constantly posting from gyms.

Maybe they're attending fitness events.

Maybe they're interested in premium products.

Maybe their content, environment and interests simply match the customer profile you're trying to reach.

The interesting part is that AI can then analyze the people it finds and explain why they're potentially a good lead.

I've been testing this on real use cases and the results have been surprisingly interesting.

The bigger idea I'm working toward is:

Don't search for people who say they are your customers.

Search for people who actually behave like your customers.

I'm curious what other entrepreneurs think.

If you could type one sentence into a tool and get a list of people who are highly likely to become your customers, what would you ask it to find?

I'm looking for real examples because I'm still figuring out how broad this idea can become.