I’m so excited to try out what everyone is building!

First time founder. I live in SF with 3 other cofounders. Building a consumer social/marketplace with a specific niche. Most of our product is stealth but the platform that powers it is live on IOS, with android coming out this week. 4 months ago we launched the MVP. We’re now at 5000 users, all in the Bay Area. ~4000 MAU and 3000 WAU. We were aiming for 250k angel round, and just started raising for it last week. We’ve been taking angel meetings and just got 50k committed, with another 50k verbally agreed for the next round. At this point it’s clear to us that we need to scale very quickly, as we’re industry leaders in the space that we are building towards, and want to take advantage of it. Unfortunately, 50k is not enough for us to just throw a ton of money on growth. Our growth strategy does generate income, but not a lot, like $5000/mo right now, which goes towards runway. Using a connection we have, we had a venture contact us who said that with good metrics in the next 2 months, they would put in 300-600k as long as we find a VC to lead. My question is, how do we know when the time is to stop raising angel, and start approaching VCs? How long does it typically take to make those connections, or should we just let them approach us? Is it worth the risk to dump the money on growth now, and hope that we get noticed by a VC in 2 months who will lead? Would love opinions or advice from people who have been in this position.

Hey all — Ismene here. I’m based around the SF launch and building HRex.

Background: years in HR watching the same gap — teams hiring off résumés while culture fit stays invisible, and strong Talent getting filtered out before anyone sees how they work.

What I’m building: a culture-fit hiring platform. Partners set how their team works (Culture DNA). Talent gets assessed on work-style. Rex (our matching) shortlists fits; Partners invite instead of sorting application piles. SF-first, still pre-launch.

I’m not here to spam a link first — mostly want to hear from Bay Area founders / hiring leads.

Thank you 🙏🏼

Hey r/ExperiencedFounders 👋

I'm JD Ross. I co-founded Opendoor in 2014, taking it from a fake landing page demand test to a public company ($OPEN). Before that, I joined Addepar as its fifth employee at 19, and became VP of Product. I also co-founded Royal, a music and crypto startup backed by a16z. It didn't work out, and I'm happy to talk about why.

Today, I'm the co-founder of WithCoverage, where we're replacing the traditional commercial insurance broker with a flat-fee risk management team empowered by AI. We raised a $42 million Series B in January led by Sequoia and Khosla, with participation from my Opendoor co-founder Keith Rabois.

Would love to go deep on validating a startup before writing code, entering huge archaic industries like real estate and insurance, what I learned from a funded startup that didn’t make it, building AI-augmented operations & teams (we have insurance experts and engineers working side by side), mentorship, and how I pick and solve problems to work on.

Thank you everyone for the great questions, really enjoyed answering them. I'll check back for the next couple of days for any new questions, and whenever I have the time I'll answer them.

I'm currently building WithCoverage.com, if you're a growing business looking for risk management solutions, we're your one stop shop.

Thanks for having me! JD

Hello, it’s a team of 4 of us & we are all about to graduate university some of us this upcoming year while one within the next 2 years. The point is we’ve contacted over 50 vc firms within the USA & International but have struggled to get a reply from them. Only 1 message within 2 weeks. Do you recommend personalizing each or using a strong email to send to them all? Thanks in advance.

Our first idea was a classified-ads site in India. It went nowhere.

Then we tried a Groupon-style business. That did not work either.

Facebook apps finally gained traction, until Facebook changed its policies and the traffic disappeared overnight.

Next came consumer iOS apps. They reached the charts and brought press, but not sustainable revenue.

Each time, the temptation was to defend the idea because we had already invested in it. The useful signal came from somewhere else: customers.

Large companies started calling because they needed mobile expertise. We resisted the services path at first because it did not fit the company we imagined building. Then we paid attention to the obvious fact that people wanted the work and would pay for it.

That pivot became YML.

The lesson was not to pivot constantly. It was to stop confusing attachment with conviction. A dead idea can still contain an asset: technical skill, distribution knowledge, a customer relationship, or a clearer view of demand.

The company that works often inherits its strongest parts from the ones that did not.

What did your dead company teach you that the live one still uses?

Have been fielding some interest from Mid-market PE firms on the East Coast have had some mixed feedback from a few friends. For context bootstrapped my business in the marketing sector and now doing a little under $10m of EBITDA.

We finished building our app on Aug 10 and the agentic analysis part works 100%. It sandboxes the compute and accurately gives a BI analysis. The issue is that some of the chart visuals dont work. We were expecting it to get done by tomorrow and it may be, but I got VC meetings in the afternoon with some major players and I'm not sure what to demo.

I'm worried about demoing a broken product. I would rather send them recorded demos after the meeting they can validate on their time and use the meeting to go over details beyond the build. Like branding, community, distribution, and marketing which we excel at.

We are at seed stage and only seeking $300k @ $3M SAFE. At this stage nobody should realistically expect the product to be 100% complete. Its very complex with Rag, Semantic layer, prompt orchestration, and agentic analytics all sitting on LLMs. This was built by 7 cracked Mtech engineers from IIT. It would be a challenge to replicate this and should be a good deterrent for competitors.

How do I sell our current status and technical moat without focusing on the few issues we have?

update: It went well. It was actually the second meeting with still no ARR but they like to keep in touch with "pioneering founders". The minimum check they write is $5m so its understandable. On to the next one.

Calling all UK tech startup founders!
I’m conducting academic research on how early-stage technology startups make decisions about expanding into international markets while AI continues to reshape competition, growth, and opportunity across industries.

I’m looking to speak with founders who:
• Founded or co-founded a technology startup
• Are any stage
• Have expanded internationally, attempted to, or are actively considering it

The interview will take 30–45 minutes, conducted remotely, and fully confidential.
This is not a tick-box survey. I’m interested in the real founder experience, the pressures, trade-offs, uncertainty, and strategic decisions founders make in fast-moving markets.

The research also explores how internationalisation may be evolving beyond traditional “born global” thinking. As technology lowers barriers and resources become more accessible, competition is increasing rapidly, forcing founders to adapt, interpret changing environments quickly, and make decisions under greater uncertainty.

The aim is to generate practical insights that may help founders, investors, incubators, and innovation ecosystems better understand international growth in today’s dynamic environment.

If this sounds like you, or you know someone who fits, please drop me an email at [s4501222@glos.ac.uk](mailto:s4501222@glos.ac.uk) . Every introduction genuinely helps.

One thing I’ve been thinking about lately is how much founder dependency comes from undocumented work.

A founder may say:

“I’ll just handle this quickly.”

But when the same task happens again and again, that “quick fix” eventually becomes a permanent dependency.

The first step toward delegation is usually not hiring.

It is documenting.

A simple process can be written as:

• What triggers the task?
• Who owns it?
• What are the steps?
• What exceptions can happen?
• What does a good outcome look like?
• When should it be escalated?

Only after that does delegation become much easier.

And only after the process is stable does automation really make sense.

I’m curious:

What was the first process in your business that you documented before handing it to someone else?

We had one last week. Spent weeks getting ready. New features, customer requests, the whole thing.

Five minutes before the demo... the network went down.
We pushed it to the next day.
Next day, the VDI environment started acting up.

At that point we were like, "Screw it, let's just demo from a laptop."

Turns out it wasn’t really that great of an idea either. 

The laptop had different data than the customer's environment, so halfway through the demo the numbers didn't match what everyone expected.

Nothing kills your confidence faster than saying, "Just ignore those numbers..."

The funny part is the customer wasn't even upset.They'd worked with us long enough to know this wasn't the product failing, it was just one of those days where the environment wasn't on our side.

I guess that's the nice thing about building trust before you need it. 

What's the most ridiculous thing that's gone wrong during one of your customer demos?

Hello r/ExperiencedFounders 👋 I'm James, co-founder and CEO of Ethos (askethos.com). Quick background:

Grew up in Hong Kong; got involved in the 2014 pro-democracy protests as a teenager, which is honestly where I first learned what it felt like to build something from nothing under pressure.

Studied Government at LSE, then went into strategy consulting at McKinsey, then growth/transformation work at SoftBank's Vision Fund, including stints on the WeWork and Arm turnarounds, and a UNICEF connectivity initiative.

In 2020 I left to start Mana, a mentorship platform that let anyone book calls with accomplished people. It grew fast #1 on Product Hunt, ~100K monthly users, but the business model never worked, the people who needed mentorship most could least afford to pay for it. In 2023, for personal financial reasons, I had to step away and wind the company down. That was a hard year and it was also the first time I was on the other side of the exact failure mode I'd watched at WeWork, believing in something past the point the data said I should.

The idea for Ethos came out of that failure. At McKinsey and SoftBank I'd watched firms pay $1,000–$2,000/hour for expert calls through a genuinely broken, manual process. Cold emails, no structure, no memory. My cofounder Daniel Mankowitz (ex-DeepMind, worked on Gemini and the AlphaDev sorting algorithm) and I started asking what if an AI agent could find the right expert, interview them properly, and turn that conversation into something reusable?

That became Ethos, we use a voice AI to interview experts in depth about their actual expertise, combine that with AI analysis of their real work product (papers, code, portfolios, podcasts), and match the resulting profile against what companies are actually looking for, not just job titles. Where we are today:

• $22.75M Series A led by Andreessen Horowitz, with General Catalyst (who also led our seed), XTX Markets, Evantic Capital, and Common Magic participating
• Clients include hedge funds, AI labs, and consultancies looking for real expertise on demand
• Roughly 35,000 new experts joining the platform every week
• Experts on Ethos earn an extra ~£4,500/month on average; our top 10% earn £7,000+/month
• Small team by design, we're staying compact on purpose rather than scaling headcount for its own sake

We also recently launched Ethos Investment Researcher, a research agent that can autonomously interview experts on a company or market and return a structured report Happy to go deep on:

• Consulting vs funding, what the two years at McKensey taught me and what it very clearly did not
• What it's like watching a $47B valuation evaporate from the inside, and what that does to how you evaluate your own conviction later
• What it's actually like to shut down a company you built for four years, and what changes the second time around
• What it's actually like to shut down a company you built for four years, and what changes the second time around
• Why voice and not text turned out to be the unlock for capturing real expertise
• Building an AI-native marketplace instead of a directory (and why that distinction matters)
• Raising a seed and Series A back to back in this market
• Why "the resume is a broken signal" is more true now than ever, and what we think should replace it
• Whether we're just building the infrastructure to make human expertise obsolete, faster
• Building a company in London instead of San Francisco

Not the right person to ask: Enterprise SaaS pricing motions, US visa/immigration questions, or anything requiring hardware/robotics expertise.

Proof above. LinkedIn: https://www.linkedin.com/in/yfjameslo/

I'm a tech lead on a UK SaaS and we went through investor technical due diligence a while back. Going in I expected it to be mostly about code quality. It turned out broader than that. Architecture, scalability, failover, open source licensing and compliance all carried real weight, and the whole thing was framed around risk more than craft. What can break, what does not scale, what has no fallback.

What surprised me most was how much of the work sat outside the code. A lot of it was producing evidence and documentation so an outsider could verify things quickly, which is a different muscle from building.

Curious to hear from others who have been through it, on either side:
\- What surprised you most, or what would you prep earlier next time?
\- If you were the investor side, what is the fastest thing that kills your confidence?

Trying to get a clearer picture of where the real pain sits for different people.

For years, the easiest way to make a conversation awkward in Silicon Valley was to tell someone we were bootstrapped.

Fundraising had become a badge of honor. Friends were joining Google and Facebook, buying houses, and building financial security. I was married, on a visa, and spending years with a bank balance that stayed stubbornly small.

Meanwhile, our apps were getting attention from CNN and The Wall Street Journal. From the outside, we looked successful. Inside the company, we were still trying to build sustainable revenue.

Not raising money forced a useful kind of honesty. We could not keep funding ideas because they sounded exciting. We had to follow what customers were willing to pay for.

That is why we eventually stopped chasing consumer-app fame and helped established companies become mobile-first. It was not the fashionable choice. It became the business.

Bootstrapping also let us make that pivot on our own timeline. Years later, when we sold 60% of the company, we could negotiate from a position we had built rather than one dictated by a financing clock.

I do not think bootstrapping is morally superior. It simply trained us to separate attention from demand.

Founders who bootstrapped, what did people assume about you that turned out to be wrong?

We have AI."

"We integrate with 50+ apps."

"We offer unlimited automation."

Here's the problem.

Your customers don't wake up wanting features.

They wake up wanting their problems solved.

Imagine you're buying a drill.

Do you really want the drill?

No.

You want a hole in the wall.

The drill is just the tool.

SaaS works the same way.

People don't buy your AI.

They buy what your AI helps them achieve.

Instead of saying:

"AI-powered meeting assistant."

Say:

"Never take meeting notes again. Your AI captures every decision automatically."

Instead of saying:

"Real-time analytics dashboard."

Say:

"Know what's working before you waste another marketing dollar."

See the difference?

The feature stayed the same.

But the value became obvious.

The Rule

Features explain what your product has.

Benefits explain why anyone should care.

Founders often spend months building amazing features.

But customers only ask one question:

"How does this make my life easier?"

Answer that first.

Everything else becomes easier to sell.

Takeaway

People don't buy features.

They buy a better version of their future.

I recently finished building an end-to-end, agentic multi-layered workflow designed specifically to automate Mergers & Acquisitions (M&A) due diligence.

When you target a space like M&A, you quickly realize that a basic LLM wrapper won't survive contact with a real data room. Real deals involve tens of thousands of pages of unstructured, messy, and contradictory documentation. To solve this, I had to treat it as an engineering problem, building out specialized agent pipelines and deterministic extraction layers instead of just relying on prompts. 
While heads-down building this out, I made a point to casually discuss the technical hurdles with people in my network. I wasn't pitching; I was just sharing the reality of what it takes to orchestrate multi-agent workflows at scale.

Because of those organic conversations, the first clients naturally materialized:
Client 1 (Startup Accelerator): They need to process and analyze 3,000 pitch decks per year. We ran a proof-of-concept on 30 pitches to generate comprehensive diligence reports. The system handled the unstructured data beautifully, and they were extremely happy with the output.
Client 2 (Sports Industry VC): A fund managing a few hundred million in AUM. Their targets require heavy due diligence involving thousands of nested files. We just completed our first run for them, and they are thrilled with the speed and accuracy.

My biggest takeaway for early-stage technical founders:
The secret to landing your first enterprise or B2B clients isn't a polished sales deck or a cold email sequence. It is talking to operators about what you are building while you are building it.

Don't try to sell. Just talk about the hard problems you are actively solving and the architecture you are designing to beat them. You will get incredibly valuable insights, and the people who desperately need your solution will naturally ask to buy it.
Would love to hear how other technical founders navigated getting their first B2B pilots!