... names, pedigrees, and geography 1,602 founders  profiled. Name-matching surfaced major-founder profiles adjacent to launches Srinivas (Perplexity), Kothari (Notion), Perkins (Canva), Mensch (Mistral), Pei (Nothing)   flagged as likely match artifacts  (could be namesakes) unless confirmed.  18.5% are ex-Big Tech , with  2.9 larger  audiences. Top prior employers (descending):  Google 62, Microsoft 47, Meta 41, Amazon 37, Apple 36 . Geography:  US 522, India 160  (India nearly matches US reception). Schools ... ... Stanford, Oxford, Cornell, Tel Aviv. Part 3. What actually works at launch Teams win:  solo 123 2 3 = 188 4+ = 288; blended multi-maker avg ~227 vs

... test a workflow that spans four services? Been hitting the same wall for a while and curious how others handle it. What's the failure shape? Someone books a flight to London. Four things have to happen: confirm the booking, send a Slack message, fire a confirmation

... from Jan 1 to Sep 1, 2026, 4,962 launches across 244 days, and looked at how many points it actually took to hit #1, top 3, and top 5 on each day of the week. Some of it confirmed the myth. Some of it didn't. The gap is bigger than I expected Saturday needs a median of 165 points to break top 5. Thursday needs 235. That's a 70-point gap just from picking a different ... ... Weekends aren't just easier, they're way less crowded Tuesday averages 30.4 launches a day. Saturday averages 10.7. Fewer competitors

... reply on my last thread got me thinking about something I hadn t really considered before: Maybe the answer to agent trust isn t more confirmation. Maybe it s better recovery. Right now, the safest UX for an agent often looks like this: Do you want me to do this? Yes. Are you sure? Yes. Just checking At some point, we ve basically built a very cautious coworker who needs emotional reassurance before creating a reminder. The obvious problem ... ... that confirmations

... comment on my last thread made me rethink how confirmation should work in AI agents. Someone asked: If I ve approved the same action 20 times, why should the agent keep asking? That feels obvious at first. If I repeatedly approve the same low-risk action, asking me again and again eventually stops feeling like safety. It starts feeling like friction. But I also don t think the answer is simply: The more you approve, the more freedom the agent ... ... need to be earned but scoped. Right now, the model in my head looks something like this: 1. Repetition builds trust If a user repeatedly approves the same kind of low-risk action, the agent should probably reduce unnecessary confirmations

... been thinking about a product-design problem that seems simple at first, but gets complicated very quickly: When should an AI agent just do the thing and when should it stop and ask for confirmation? The more actions an agent can take, the more useful it becomes. But the more autonomy you give it, the more important trust becomes. I ve started thinking about this less as an AI capability question and more as a combination of risk, reversibility ... ... make the result easy to review or undo. Higher-risk + external Send a message. Delete something. Submit a form. Make a purchase. These feel much more like ask first territory. What I find interesting is that too much confirmation

... post approximately (at least) twice a week. But I think that in general, if you want to be visible within the forums, twice a week is bearable. ----- The other side of the equation is whether your discussions are getting confirmed. To make them as effective as possible and increase the chances of confirmation

... updating some backend code straightforward find-and-replace, target text, swap it in, print success. Ran it. Got "PATCHED." Checked the file to confirm the change landed. Nothing had changed. Ran it again with slightly different phrasing. "PATCHED" again. Still nothing changed. Turned out the target text in the file used a real em-dash ( ), and my search pattern used a plain double-hyphen (--). Visually close enough that I didn't catch it reading the code. The script's "success ... ... message was printing regardless of whether the replace actually matched anything it was reporting that the script ran , not that the edit happened . Nothing broke because I'd built in a habit of grepping the file afterward to confirm

... manually search for every ingredient and enter every serving size, FitBin allows them to take a picture of a meal. The application identifies the visible food items, estimates portion sizes, calculates nutritional values, and presents the results for confirmation before adding them to the user s dashboard. The goal is not merely to tell someone how many calories are in a meal. FitBin is designed to answer a more useful question: How does this meal fit into this particular person ... ... users can review and correct the result before saving it. They can change the food name, portion, preparation method, quantity, or ingredients. When confidence is low, FitBin can request another picture, ask a short clarification question, or provide likely alternatives

... Confirmation bias is the thing that keeps 90% of startups living in the illusion that "it's almost working" for months on end. 2. The mechanics are simple: You show the idea to friends they praise it out of politeness. You collect email signups on a landing page you read it as demand (even though leaving an email costs nothing). Someone says "it'd be cool if..." you hear it as a willingness to buy. 3. The brain searches ... ... confirmation

... lapsed. Our resolution stack, in order: explicit format cues elsewhere on the invoice, GST filing conventions of the retailer, delivery or payment timestamps when the receipt came from email, and finally a confidence flag that asks the user to confirm instead of guessing silently. The general principle: when a wrong answer is costly, an honest "please confirm

... Product Hunt We just launched Concierge Compass today. We're a couple who plan all our own trips from scratch, and for years the best tool we had was the Notes app, plus digging through email for booking confirmations every time we needed them. It really hit home on a trip to Singapore, our first time in Asia. We needed our bookings with no internet, and on top of that, one of us held all the trip info while ... ... other had zero visibility, so every day became "what's next?" Concierge Compass brings everything into one place, flights, hotels, bookings, and your full itinerary, all accessible offline. Forward a confirmation

... card" email. But the reason it failed is usually very different an expired or lost card, insufficient funds, or a bank 3-D Secure/SCA verification challenge. Telling someone to "update your card" when their bank just needs them to confirm the charge is not only useless, it makes the whole thing read as impersonal and a bit spammy. Industry-wide, a meaningful chunk of subscription churn is just failed payments that never get recovered, and a lot of that ... ... these avoidable mismatches. So I built Revova ( https://revova.io ). It detects failed charges across Stripe (native), plus Paddle, Braintree, Chargebee, and Recurly, and writes a different AI-personalized email depending on the actual decline reason including a "confirm

... services. Learning about these workflows helped me see that every interface is connected to a much larger ecosystem. Technology Shapes User Experience Travel products depend heavily on real-time data. Flight availability, hotel inventory, pricing, payment status, and booking confirmations all rely on APIs communicating with external systems. As designers, we may not build these systems, but understanding how they work allows us to design better loading states, clearer feedback, and more resilient experiences. Simplicity Requires Thoughtful Design Modern travel ... ... load and improves decision-making. This principle has changed the way I think about designing complex interfaces. Trust Is Built Through Small Details Booking travel often involves significant financial decisions. Clear pricing, secure payment indicators, transparent cancellation policies, booking confirmations

... Google recently announced and pushed two new models into the Gemini API. For informational purposes, I am breaking down what's confirmedvs. what's just early testing chatter so far. Nano Banana 2 Lite (gemini-3.1-flash-lite-image): Text-to-image in around 4 seconds. $0.034 per 1K-resolution image. Positioned as the direct replacement for the original Nano Banana. (gemini-2.5-flash-image) Rolling out across AI Studio, the Gemini API, Gemini Enterprise, and consumer surfaces. (Search ... ... Conversational editing: now you can refine a generated video with plain language instead of re-prompting from scratch. Multimodal input (text/image/video combined) to keep a scene consistent. $0.10/sec of video output, same rate as Veo 3.1 Fast.

... launched a SaaS recently and noticed a cluster of accounts created within minutes of each other that never confirmed email or returned after signup. We want to keep our user table healthy without accidentally deleting real users. Curious what other founders do in practice, more specifically: Do you auto-delete accounts after X days without email confirmation

... more than any UI polish did. So yeah, I d say naming the problem is the actual unlock. The demo just has to not get in the way of it. Comment from Viraj Parab(@viraj_parab): StartupHQ to organize competitor research, validate ideas, and keep my roadmap focused. It removed a lot of the "what should I do next?" moments. Now the challenge is exactly what you mentioned: getting distribution right. Comment from Mincheol kim(@mincheol_kim): @anna_ludwinowski ... ... Kozlo(@wvitalik): I look for the problem/need first. However, note that some products are solving the problem of a bad existing UX and user interface (think about the goal "to manage virtual private servers" and solutions via the terminal VS

... live on PH Aug 22, so this thread's been good practice at saying it in one paragraph.) Comment from Demetrio Koro(@aktivist): siOsi upload one selfie and it reads your 12-season color type, undertone, gold vs silver, and which hair colors suit you, then grades the actual makeup in the photo (flash cast, oxidation, coverage), which most tools skip. Free, no signup. Built it because every beauty sub has a queue of "what season am I" posts waiting ... ... easy not merging two different root causes into one bucket, or splitting one real problem into five duplicates, isn't. Similarity search alone kept silently corrupting the ranking, so we added an LLM-judge pass that has to confirm

... exciting until the assistant closes the wrong tabs. We built a hard stop for irreversible actions. Insight for other users:  When Oasis plans something  destructive  (for example closing many tabs or deleting data), a  confirmation modal  blocks the browser until you  approve or cancel . Nothing runs until you make an explicit choice. What usually does not trigger this:  Non-destructive reads like listing tabs, summarizing a page, or searching your history. Those ... ... proceed without the same gate. How to stay safe: Read the summary in the modal carefully.  Cancel  is always safe. Hit  Confirm

... recoverable native-memory spikes. With the heap ceiling at 60% of the limit, V8 still hard-stops growth well below the watchdog, so the new threshold gives transient spikes more room to resolve before we preemptively cycle the pod. Confirming the fix against real kubelet The change was small, but justifying the rollout took more work. The risk cut the other way too: a too-tolerant liveness probe could mask a genuinely stuck pod and delay a restart that would ... ... world. They aren t safe for Node.js out of the box. Treat liveness and readiness as fundamentally different. Readiness should be strict and liveness should be tolerant, because failing readiness just drains traffic while failing liveness destroys process state. Confirm

... doorbell. It rings the same whether it's a package or a fire. That's basically the gap Pushary fills, same hook idea you've already wired, but the event carries a real handoff (done vs blocked vs

... issue without leaving the terminal. What's new: Action menu press space on any row of Repos / PRs / Issues to open a centered modal: Actions for octoscope o Open in GitHub d View details c Copy URL enter confirms, single letters are direct shortcuts (lazygit-style), esc closes, q quits at any depth. Repo drill-in (d from the menu) replaces the Repos tab body with a rich detail view: Header with visibility / license / language chips Description, quick stats, latest ... ... cursor preserved; r refetches. Copy URL (c) drops the row's URL into your system clipboard via the right helper for the platform: pbcopy on macOS, clip on Windows, wl-copy / xclip / xsel on Linux. A URL copied toast confirms

... gave both models the same workflow orchestration spec and reviewed the code. Here's what review turned up. Key takeaways Claude Opus 4.7 ran 31 tests, all green. 1 real bug. Kimi K2.6 ran 20 tests, all green. 6 confirmed issues. Opus 4.7 scored 91/100 at $3.56 Kimi K2.6 reached 75% of this score (68/100) at 19% of the cost ($0.67) Full write-up here As pointed out in another thread comparing @MiniMax M2.7 with Opus ... ... narrowed significantly over the past year. For prototyping or exploring a design, the $0.67 run is a good deal. For work requiring correctness and accuracy, Opus 4.7 remains ahead. Any experiences coding with open-weight models? [1]: MiniMax M2.7 vs

... constantly. The parents are lonelier than they admit. And a daily phone call is never really enough. What Saathi does: Greets your parent every morning in Hindi/English (just like Alexa) on their existing phone; Reminds them about medicines and confirms they took them; Checks and confirms

... nothing . At the security level: 70% had authentication vulnerabilities that would give any security engineer a heart attack . At the quality level: 91% had no automated tests. Every deployment was a gamble. No one could "click a button and confirm that nothing else is broken" . The True Cost (Not Just Engineering Hours) For a 4-person engineering team, the math is brutal. 42% of engineering time is spent dealing with bad code. Over three years, that ... ... first line of code: spend two weeks on architecture. Scale mindset: Ask "what will break at 10,000 users?" not "can it run with 100 users." Automated testing from day one: If you cannot "click a button to confirm