... accepted exactly zero. Usually, it was because: The other person was already putting me in an inferior position: You ll get 40%, I ll get 60% because I m developing the product, but we ll be working on it equally. The product idea wasn t something I was excited about. I was apparently supposed to be the figurehead who would help get VC funding, but probably having very little actual decision-making power. :D That said, I do think having ... ... founder, so this is just the marketing seat watching from outside. The split you mention upfront, the 60/40 "inferior position" framing, tends to be the tell rather than something that gets fixed later. If the ownership isn't equal

... nice-to-have. Product Design is the number one skill, and Figma outranks Python. The modern solo builder is expected to make it look good, not just make it work. Second, TypeScript is nearly caught up with JavaScript (49 vs 52) and growing faster in project tags. If you're picking one to invest in deeply, the trend line points clearly at TS. The full picture: JavaScript + TypeScript + React + Next.js + Figma + a Postgres backend. That's the default ... ... platform, and skills are self-reported. Treat it as a strong signal about where indie builders are heading, not gospel. But the direction is hard to miss. AI is up and to the right, design is on equal

... that limit becomes their entire first impression of the product. So the decision is less about who pays and more about which limit an invited person hits first. Comment from Brandon Dennis(@bdennis11907): we are debating a free trial vs money back guarantee - it is less about cost, but more about which one gets someone actually to try product and see the value especially for PH launch @adana any thoughts on it? Comment from Hisashi Space(@hisashispace): Not sure ... ... simple enough that it probably reads as something that only works on paper. But working alone means I can run at close to no cost, so I can actually hold both ends of it at once. The customer gets equal

... earlier this year. An end-to-end test timed out at 300 seconds, then at 420. The agent raised the limit to 480 and added a skip-on-timeout. Their summary: the test now has no failure mode, timeout equals skip, success equals

... shoutout to @galdayan , kindly asked us in the comments - what if I receive a message from across the world that sounds a bit off to me? Can I use your product to clarify possible misunderstandings? That felt like an equally important focus problem. Which function would you personally use more? Before sending, to check how your words may land After receiving, to check whether you might be misunderstanding the tone or meaning Also, for a received message, what context would ... ... there would need to be a dataset informing and supporting the judgment - a cultural ontology or data on cultural associations. Would you prefer WIT simply to flag the possible cultural association mismatch or also suggest a culturally safer alternative

... subconsciously I perceive it as "something less"). I have to say that some outputs that look really high quality and I have trouble distinguishing them from "handwork" are perceived as completely normal (at least for me). As equal human work. How do you view things generated by artificial intelligence? Maybe it's true that who is behind the output and prompting also influences the result (professional vs

... market: I speak Portuguese, Mariana is Portuguese and my wife is Brazilian. We ran a test in Portuguese. We recruited 100s of Brazilian users in three weeks, mainly thanks to Ting on WhatsApp. IYKYK . December Based on competitors communications, social activity and web traffic, Ting appeared to have become the most-used scheduling agent of its kind. But the category was filling up. Sequoia had backed a competitor

... need to retry with exponential backoff while logging to three different services? The assistant completely missed it and didn't even flag that it was skipping anything. It got me thinking about where these tools actually excel versus where they consistently fall short. They're genuinely exceptional at scaffolding, at spinning up the obvious structure of a feature. But the moment you need to handle what shouldn't happen race conditions, partial failures, the weird state your system ends ... ... they seem to lose the plot entirely. The frustrating part isn't that they can't solve these problems. It's that they sound equally

... creators have access to more data, dashboards and idea generators than ever, but many are still unsure what they should publish next. UploadPack is designed to help solve that gap. It reviews a creator s channel, previous uploads, selected competitors, audience search behaviour and saved channel context. It then identifies opportunities worth investigating, explains the evidence behind them and turns the chosen direction into a complete publishing workflow. Some of the areas I am focusing on include: Finding opportunities without ... ... requiring the creator to begin with a topic Identifying channel-specific audience, competitor

... been experimenting with AI-assisted development, and it's completely changed how quickly I can go from idea to MVP. But it's also made me question something. We've become incredibly good at generating code. Have we become equally good at deciding what to build? I keep coming back to this simple thought: def build_startup(idea): validate_market(idea) understand_customers() analyze_competitors

... agent didn't just act, it acted with someone's credentials, someone's access, someone's blast radius. and when it goes wrong, the audit trail usually can't tell you what the agent was actually authorised to do versus what it happened to have access to. those are different things and most systems conflate them. honestly that's a big part of why we're building MonoCloud the way we are. scoped identity for agents so the blast radius ... ... rather than hold the line forever. A stalled job that took the cautious path is recoverable. A stalled job that just sat there is a support ticket. Comment from Dale Mooney(@dalemooney): @alex_amancio_candoa_   @aadilghani  Constant versus

... already done. But I still wanna polish something, e.g. add pricing so I can see whether it converts. Comment from Nika(@busmark_w_nika): @abidhusain  When you describe it like this, it sounds complex. Does it have any competitors at all? Comment from Nika(@busmark_w_nika): @abidhusain  What is your tool about? What does it do? :) And does it have your first initial testers? Comment from Nika(@busmark_w_nika): @xshahneil  Do you have any data ... ... nika): @dinocorreia  I was the very first user of my tool (because the problem happened to me) :) Comment from Nika(@busmark_w_nika): @dinocorreia  To be honest, for now, I was able to find only one competitor

... median points needed to break the top 5 and top 10 on each day. Check the full report here: https://app.databox.com/shared/a... The short version: Saturday is the easiest day. Only 266 median points to crack top 5, vs 360 on Wednesday. That's a 35% harder climb on the worst day vs

... curious (no login, works on crypto/forex/stocks): traderai.cloud/chart Anyway, it's been mostly me, a lot of coffee, and staying up late carrying me through the parts I'm bad at. Launching it properly tomorrow and I'm equal parts excited and nauseous lol. Genuine question for this crowd: for those of you who've shipped solo - how did you deal with the "is this even good enough to show people" feeling right before launch? Trying not to talk myself ...

... slow Monday at a cafe and a slow Monday at a software company are not the same signal). The confidence grading is a nice touch too, gives you a way to triage instead of treating every flag as equally urgent. Would genuinely enjoy the call if you're open to it, curious how it handles the early days before there's enough history to know what "normal" even looks like for a business. Comment from Kartik Batchu(@kartikbatchu2003): Monday signals ...

... consulting, and training revenue simultaneously and still hope the business will scale. Even with AI efficiencies, stretching the team too thin kills momentum. 3. Not thinking deeply enough about the Moat and GTM. A great product does not automatically equal a great business. If you haven't thoroughly thought through your Go-To-Market strategy and why your business is defensible against competitors

... Launch a Prediction Market Platform Like Polymarket 1. Define Your Business Model- Identify your target audience, revenue strategy, supported markets, and platform objectives. A clear business model lays the foundation for long-term growth. 2. Conduct Market Research- Analyze competitors, user preferences, and industry trends to identify market opportunities and differentiate your platform. 3. Choose the Right Technology Stack- Select blockchain networks, smart contract frameworks, backend infrastructure, and frontend technologies that align with your scalability and performance requirements. 4. Develop ... ... prediction markets offer significant opportunities, but businesses must carefully address several key challenges to ensure long-term success. Regulatory compliance is a major consideration, as legal requirements can vary across different regions and jurisdictions. Maintaining sufficient market liquidity is equally

... user___1702026e6f946759d1d798a): This is also one of the first things investors look for. A polished demo can attract attention, but if someone cannot quickly understand who has the problem, how painful it is, and why the current alternatives are inadequate, the conversation hits a dead end. Based on my own experience and a friend who works at 1752vc, the strongest pitches often make the problem feel inevitable before they spend much time explaining the product. Comment from Martin Tanner ... ... that's a very important distinction. That could also explain why you're attracting more men, who are looking for a real solution vs

... LLMs. But here is the tension. 75% of global marketers express excitement about generative AI, but there is a growing philosophical debate about the enduring value of human connection The authenticity paradox The acceleration of AI has created an equal and opposite reaction: a craving for the real. As generative AI floods the internet with synthetic content, "perfection" is no longer a differentiator; it is a commodity. The new premium is flaws, vibe, and human connection . Ogilvy's 2026 Futures ... ... powered search systems are deprioritizing content that AI helped create. Instead, search systems surface work demonstrating originality, firsthand insight, and human judgment . The conclusion is uncomfortable but clear: Stop measuring success by output alone. Volume no longer equals

... like telegram more than the whatsapp for chatting :) VS Code : i do code . Comment from mono.(@shakutovbekzat): Here s my stack for building mobile apps today: Antigravity + Codex (AI Agent): Switched to this setup recently. Previously, VS

... Chief of Staff I built after running a software company, a care home, and a cafe at once. Identifying what's important now is easy to say but hard to do daily across separate businesses, curious how automated vs manual your prioritizing is right now. Open to a quick call if useful. Comment from Stacy Wycoff(@stacywycof83995): @mark_trowbridge  This is the exact problem I built FounderFlow to solve, after running a software company, a care home ... ... cafe at once, identifying what's important now was the hardest part because everything competed equally

... made them succeed or fail? For those who've sold into small/mid-sized businesses, what's usually the biggest blocker to adoption price, integration effort, or something else? Is there a feature here that seems like a "nice to have" versus something that would actually change behavior? Would appreciate any perspective, whether from experience building similar things or just as someone who's dealt with this as a customer or business owner. Comment from Alessandro Lusardi(@alelusardi): I am currently building ... ... scroll through it like a feed. Same muscle memory as scrolling Reels, except every card is helping you retain something real. Why it's more than "just flashcards with extra steps": The app quietly tracks what you actually know vs

... would help you make better launch decisions? Comment from M. M. Carvalho(@m_m_carvalho): @oshylabs  Did exactly what you said. Coverage is the headline now , reply speed moved to the side, and I added a simple question vs. non-question split with its own "questions answered" number. So the lazy pattern you described reply to every "congrats", skip the real questions now actually shows up, because that number drops even when the overall one looks fine. Right ... ... coverage first; timing adds nuance for high-coverage launches. On comment types: yes, worth distinguishing, and it changes the signal significantly. A congratulatory comment that goes unanswered does not indicate disengagement. An unanswered question does. If you weight them equally

... will create. I guess this is the closest to the honest trade-off great product and tech divisions have done for many years before the advent of coding agents. Focus on reliability and observability. Not all tech-debt is equal but we are keeping a close eye on the most critical paths with additional infra to monitor for that. What tradeoffs are you making, and what's working for you? Especially curious about teams that are heavily AI-assisted ... ... Fair point and yes, I believe continuous refactoring tilts the equation here. Same can be said about error resolution. As long as instrumentation is in place to catch issues quickly one could say the trade-off of moving fast vs

... shipped front-end with Claude, Cursor, or Copilot, you know the look. Purple gradient, three equal cards, Inter blown up huge, a "John Doe" testimonial, 300ms on everything. The tools don't choose it. They default into it, because the average of everything they trained on is generic. I'm a designer, and undoing the same five mistakes by hand stopped scaling. So I built ux-skill. It sits between you and your AI tool and swaps improvising for constraints ... ... makes the slop, so I took the model out of the decision and wrote the taste down as rules you can read and switch off. There's a real before/after in the repo: a skip-hire site, generic template versus