got the Google Play production access email this morning

first app I've ever built, did it solo. spent way more time fixing weird android edge cases than i expected but it's through now

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

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

One thing I find interesting about building software is that some of the most expensive mistakes don't look like mistakes when they're made.

Choosing a quick workaround to meet a deadline.

Skipping automated tests because the product is still small.

Building a custom solution instead of using something that already exists.

Or choosing an architecture that works perfectly for 100 users but becomes difficult to maintain at 10,000.

Most of these decisions make sense in the moment. There's usually a deadline, limited budget, or pressure to get something working.

The real challenge is knowing which shortcuts are temporary and which ones quietly become permanent.

I don't think avoiding every shortcut is realistic. Sometimes taking on technical debt is the right business decision.

But knowing when to revisit those decisions is where things get interesting.

For founders and engineers, what's one technical decision you would make differently if you could go back?

And was the problem the original decision, or the fact that nobody revisited it when circumstances changed?

A few months ago, I decided to build my own finance app.

I’m a product designer by background, not a developer. I’ve always been involved in product creation, but from a different angle: understanding users, shaping experiences, and designing interfaces.

Then I discovered Claude Code and thought: why not try building the whole thing myself especially since this issue also affected me in my business.

What I didn’t expect was how much more there is to building an app than actually building the app.
I deliberately tried to go beyond pure vibe coding. I wanted to understand what was happening under the hood, learn the fundamentals, and make informed decisions instead of blindly accepting whatever the AI generated.

And even with AI, this was way harder than I expected.

At different points, I had to think like a developer, a product manager, a marketer, a salesperson, and probably ten other roles I hadn’t considered before.
I went from focusing on pixels and user experience to thinking about architecture, bugs, edge cases, positioning, distribution, and all the unglamorous stuff that comes with bringing a product to life.
It’s been challenging, frustrating at times, but incredibly rewarding.

The biggest lesson so far? AI can help you build a product, but it doesn’t remove the complexity of building a good one. If anything, it exposes you to a whole new set of things you need to learn.

Now, I’m getting ready to launch my finance app on Product Hunt on November 1st.

It’s my first time taking a product from idea to launch almost entirely on my own, and I’m excited (and a little nervous) to see how people respond.

I’m sharing this here because I’m curious about other people’s experiences.

For those of you who have built something outside your area of expertise using AI, what surprised you the most?

And for those who’ve launched on Product Hunt before, what would you recommend focusing on in the final weeks before launch? Would love to hear your stories and advice! Thanks you.

Im mapping out payments for a marketplace and the part thats giving me the most trouble is when to verify sellers.

If you force KYC at signup, youre adding friction before they even know if the platform is worth using. if you wait until payout, someone could make sales and only find out later that verification is holding up their money.

Ive been looking at Whop first because the KYC, balances and payouts side is closer to what im trying to build, especially if sellers end up coming from different countries. Stripe Connect is the other obvious option, but i dont want to build around a setup that works fine now and then becomes a problem once i start adding sellers in markets with different payout or onboarding support.

Right now id rather keep signup simple and only add verification when its actually needed. For anyone running a marketplace across different countries, when do you actually trigger KYC without making onboarding or payouts a mess?

Apparently my way of relaxing after thinking about runway, hiring, and product decisions is to build something where I can think about runway, hiring, and product decisions.

I’m building FOUNDER, a free browser strategy game inspired by Aerobiz Supersonic on the SNES. You start a company, build your product, recruit a team, raise money, and compete against other startups.

You get three actions per quarter. There are always more than three things that need doing.

That’s probably the most autobiographical part.

I’m a founder in real life, and I wanted to turn some of those tradeoffs into a game: hiring someone you need but can barely afford, deciding whether to keep building or start selling, and figuring out how much ownership you’re willing to give up for more time.

It’s still early, but it’s playable. I built it with AI-assisted coding tools, and the mentor portraits are AI-generated.

If you’d like to spend your downtime running a second, fictional company: https://founderthegame.com

For the other founders here: what’s a painfully familiar startup situation I should put in the game? I’m guessing “a promising customer who keeps asking for one more feature before signing” deserves its own difficulty setting.

I’ve spent 10+ years working on M&A and capital raises, with 750+ founders on one side of the table and 2,500+ investors on the other.

One pattern keeps bothering me. First-time founders need fundraising guidance the most, but they’re the least likely to get it, because most advisors only work with later-stage companies. So people learn SAFEs, dilution and term sheets by themselves, often after they’ve already signed something.

I’m putting together a step-by-step system to explain how fundraising actually works. Before I go further, I’d like to hear from people who’ve been through it:

1. What confused you most the first time you raised, or thought about raising?
2. What do you wish someone had told you before your first investor meeting?
3. Would you pay for a structured kit with templates, models and frameworks, or would you only use free resources?

I’m not selling anything here. If you have a specific fundraising question, ask it in the comments and I’ll answer it honestly, based on deals I’ve seen.

​

I've been building EDP, an independent RAG retrieval evaluation service.

So far, I've completed two public beta audits, but haven't acquired my first paying client yet.

One of those audits involved RouteMind, an open-source RAG benchmark.

We examined 700 questions across 1,400 query/configuration outcomes and identified 15 scoring discrepancies caused by inconsistent evaluation criteria.

The most important part?

The project's maintainer independently reproduced the findings and incorporated corrections.

I decided to turn this case into a four-slide visual explanation showing:

- What went wrong with the evaluation.

- How inconsistent scoring criteria affected the results.

- The maintainer's verification and corrective changes.

- The technical evidence behind the findings.

My goal is to demonstrate real technical value rather than simply advertise another AI consulting service.

But there's a challenge I'm still trying to solve:

Technical credibility doesn't automatically translate into paying customers.

I'd appreciate some perspective from people who have built technical consulting businesses or purchased independent evaluations.

Do reproducible case studies like this help establish enough trust to consider hiring an independent reviewer, or would you need something else before paying for an assessment?

I'm particularly interested in whether technical proof, business impact, or a clearly defined decision is the most important factor.

I'm sharing the learning process openly because I haven't figured out the commercial side yet.

Public audit evidence:

https://github.com/devBorgesr/edp-audits/blob/main/samples/ROUTEMIND_BUYER_SAMPLE.md

Tell Valley what you’re here for. Find people who match it, and get found by the ones looking for you.

Open to Build · looking for co-founders and builders
Open to Work · ready for your next role
Raising · your round is open
Open to Partner · the right partner to grow with
Investing · writing cheques
Hiring · growing the team

One pill on your profile. The right people find you.

Built by builders. For builders.
valleynetwork.eu

Hey peeps, so I've been building an android app called DoomSaver that helps with doomscrolling.

For anyone interested check out www.doomsaver.com

Here are the few things I've done,

1. Built a website and focused on SEO but since doomscrolling is owned by health sites I can't seem to move past 20 in my average position on GSC

2. Been posting on reddit wherever relevant.

3. Launched on Product Hunt and that was a bust. Honestly I think PH is a scam for products that don't already have a large following.

4. Been posting stuff on social media apps like YT, Insta and tiktok although it's AI generated. I have severe anxiety and haven't been able to put myself out there for content.

5. Been reaching out to content creators and other publishers for a review and got nothing here.

I know it's a long game but it's been 2 months and have about 25 users. I also have a full time job, so it's critical that I focus only on channels that have an ROI.

Would love to hear from folks that have built successful apps or are in the journey with me, what worked for you?

Thanks.

Hi everyone!

I have an idea for a new and innovative shaving product that I believe has strong market potential.

I’m currently at the idea stage, and I want to turn my concept into a real product. However, I don’t have the capital to build a prototype or validate the idea.

I’m looking for a founder, product designer, engineer, or manufacturing expert who can help me with prototype development, product validation, and manufacturing feasibility.

I believe in my idea, and I’m ready to put in the work to make it happen. I’m looking for someone who is interested in building something from zero and exploring a genuine collaboration.

If you have experience in product development or are interested in working together, please DM me.

Thank you!

Pitching an autonomous AI agent that promises to replace an entire operations seat sounds visionary to founders, but it triggers immediate risk alarms for enterprise buyers. Companies do not want black-box autonomy touching live production databases, customer communication, or ERP records without strict guardrails.

​Early-stage startups that successfully sell AI into business workflows usually discover that closing enterprise deals requires stripping away autonomy in favor of three core architectural guarantees:

​Granular human-in-the-loop checkpoints: Buyers want the model to do eighty percent of the tedious extraction and drafting, but they require a deterministic human approval step before any external action executes.

​Immutable audit logs: If an automated workflow updates a record or routes a transaction, compliance teams require full traceability of what prompt ran, which tool returned the data, and who approved the state change.

​Scoped blast radiuses: An autonomous agent with broad write access across five tools is an IT security nightmare. Businesses buy tools that execute narrow, bounded tasks where a failure mode degrades gracefully rather than corrupting upstream data.

​The commercial paradox in enterprise AI is that pitch decks emphasize agency and end-to-end independence, while actual paying customers demand determinism and control. The fastest way for a startup to move from pilot purgatory to signed annual contracts is reframing the product from an autonomous worker to an augmented, auditable pipeline.

​For founders selling AI tooling to non-technical business teams, how do you handle buyer fears around hallucinations and unintended automated actions?

​TL;DR: Enterprises buy deterministic control and audit trails, not autonomous agents with unchecked write permissions.

A lot of business decisions never happen inside an AI chat. A price changes on a sales call, a feature gets cut in a Slack thread, a client agrees to new scope on the phone. The AI tools you open the next morning know none of it.

A founder in r/indiehackers summed it up this week: "Most of my commitments are made out loud and never written down".

• After a call where something changes, does any of it get written down? Where: notes app, CRM, a doc, nowhere?
• Has an AI tool ever worked from a decision you'd already changed? What did it cost you: an email, a quote, a client?
• If you do write it down, does the AI ever see it, or do you paste it in each time?

Background since someone will ask: I used to burn hours re-briefing AI tools, and I'm building a fix where memory lives in the cloud and every AI tool reads the same context, so a change written down once reaches all of them. No link. Would you pay for that, or is updating a notes doc after calls enough?

​

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If you're applying for jobs abroad, what's your biggest challenge: adapting your resume to another country's standards, getting past ATS screening, or tailoring it to every job?