... product. I would love your honest feedback on a few technical and UX fronts: 1. Does the real-time map interface feel responsive and intuitive when you first land on it? 2. For a global P2P network, what alternative web-mapping APIs or voice formatting tools would you look into to keep server architecture lean

... dramatically smarter this year. Your product didn't get more trustworthy and in 2026, those turned out to be two completely different problems. Here's the line that reframed it for me. Stanford's AI Index this year leans on a phrase from Ethan Mollick the "jagged frontier" to describe how these systems excel and then fall off a cliff with no warning. Their example is almost too good: an AI model can win a gold medal at the International ... ... fires when the user already caught it, so I'd be measuring my catch rate and calling it my error rate. The run-it-twice-and-check-for-disagreement trick is the part I've underused. At Murror we lean

... that survive the meeting. Action items carry an owner and a due date and roll into the next retrospective instead of dying in meeting notes. An MCP server. QRetro speaks Model Context Protocol, so Claude, Claude Code, Cursor and VS Code can read boards, summaries, health trends and open action items and write back. One address, sign-in in the browser, nothing to install: https://qretro.com/docs/mcp 50+ templates. Mad Sad Glad, Sailboat, 4Ls, Starfish, Lean

... nothing, the reviewer's normal experience becomes an empty screen, and empty screens train people to expect empty. Whether the one that is not empty gets read properly on day forty is an open question. It still beats the alternative, because a difference against a background of silence is about as salient as anything gets. And yes to the small pile. Most of what gets called judgement is work nobody has bothered to make mechanical yet. Comment from Aadil Ghani ... ... finished land in the same bucket, and the bucket is named after the success case. There is a comment in that file explaining the choice and it reads as obviously correct. One thing I would check on yours before leaning

... tracks Claude alongside ChatGPT, Gemini, Perplexity, Copilot and Grok, so that's six engines, every tracked query, fetched every 24 hours. Why this matters: every engine we've added so far has had its own sourcing personality (Gemini leans creator content, Grok will build an answer from a single post, GPT leans

... post daily across five platforms, but if you don't actually know who your ideal customer is or what pain point you're solving, you re just putting a lot of effort into something destined to fail. Personally, I lean toward strategy being the real differentiator. Great execution on a flawed strategy just gets you to failure faster. But if you have clear positioning and know  where you re going, you will eventually find a way. At least, that ... ... gaspard_dupuich): I usually notice confusion starts when the customer problem is not clearly defined. Could every task be linked to one business goal? That simple check makes execution much easier. Comment from Yanex(@yanex): I think the strategy-versus

... Been thinking about this after a few good conversations here lately: there's a real tension between building something that flags "this looks off" for you automatically, versus just surfacing the raw signal and trusting the human to interpret it. Too much automation and you risk false confidence, the tool says everything's fine, so nobody looks closer. Too little, and you're back to relying entirely on someone's attention, which doesn't scale past a certain team size ... ... number of ventures. With Trackly, I've mostly leaned

... first, so you don't need to know the file structure or the manifest.  - Permissions are scoped to what the feature actually needs, and it flags permissions that are declared but never used, so you go to review lean.  - It handles the whole last mile too: store listing, permission justifications, privacy disclosures, and publishing directly to the Chrome Web Store.  - The code is yours, with a live preview, full version history, and a real side-by-side ... ... actually required. On review: it runs a Web-Store pre-flight before you submit, generates the permission justifications and privacy disclosures Google asks for, and catches the common gotchas that get extensions bounced. So you go into review lean

... pause before an answer was genuine uncertainty or just thinking time. To see whether the person's expression changed when they described a feature they claimed to like. To catch the moment when engagement visibly dropped when they stopped leaning forward, when their eyes moved away from the screen even while their words stayed polite and positive. That gap between the transcript and the recording is where a significant amount of research insight lives. And it's also where ... ... that transcripts just drop. Comment from Johnson Gill(@johnsongill): For me it's emphasis, and a transcript almost hides it by design. On the page, every sentence carries equal weight, but in the room, you can hear what someone leaned

... that made the use case exist. like don t say my tool solves this , say i wasted 40 min doing this stupid thing last week and let the tool show up at the end almost as an afterthought. people lean in on the frustration, not the feature. also honestly the biasedness never fully goes away, you just stop trying to hide it. saying yeah im obviously biased but here s how i actually use it reads way more honest than ... ... just keep telling the story of the annoyance and the plugin quietly becomes the obvious answer. kinda poetic too, the platform restricting you is literally handing you the marketing angle for the thing that fixes it lol. i d lean

... different features (see our launch history ). Each time I worry it reads as "this again?" Our current strategy: launch features like they're products. Give the feature its own name, own story, own audience, and don't lean on the company's history to sell it. Take our last launch, Basedash Actions . It's just one feature within our larger BI platform, but we positioned it as the quintessential new way for companies to manage their data and interface ... ... definitely a version of this that goes wrong, where every minor update gets the full launch treatment and people tune you out entirely. Curious how others draw the line. What's your bar for something deserving a launch versus

... Google recently announced and pushed two new models into the Gemini API. For informational purposes, I am breaking down what's confirmed vs. 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 ... ... reports are mixed. A few people testing the image model are seeing real speed gains, roughly half the generation time on basic tasks, but anything detail-heavy (blurry text, fine classification) still needs the full model. Omni Flash reactions lean

... each bad hire costs over 200k. must have problem for HR. three. the 92 percent of work that linkedin never covered. plumbers, nurses, electricians have never had a portable record. that is the most must have segment because the alternative is no record at all. when receipts replace resumes, all three solve at once. that is the wedge. @anna_ludwinowski   Comment from Mustafa Arian(@thenameisarian): problem first every time. demo without the problem reads as a personality trait. demo ... ... your conversations. One identity. One social graph. Launched on PH today. The problem is deeply personal I was the user I built it for. Comment from Indigo Carpiniello(@indigo_carpiniello): Could not agree more, Anna. This is the Painkiller vs

... also use the waitlist as a validation tool. Rather than simply collecting emails, I'd ask subscribers about their biggest LinkedIn growth challenges. That insight could help shape both the product roadmap and future messaging. For discovery, I'd lean heavily into founder-led content showing real examples of activity levels, warning signs and how users can stay within safe limits. The idea definitely addresses a real problem. The key question is whether the pain is strong enough for users ... ... site yet, your extension itself becomes the funnel very simple: unlock pro insights join waitlist 4. distribution > features right now your biggest lever is: LinkedIn posts showing real before/after activity patterns short demos ( this is what looks risky vs

... retail investors - most of them don't have 3 hours to parse an earnings call and just want to know if the number matters. Natural language on top of financial data is exactly where AI actually adds value vs. just looking useful. Real-time accuracy on constantly changing financial data is genuinely one of the hardest infra problems in this space, so props for taking it on. Comment from Sam(@sammyaxe): Building MerchPush , a platform that makes distributing branded merchandise ... ... verified AI disclosure. others will not. over time the receipts with agent transparency outperform on credibility because the alternative

... Product Hunt I'm Ritesh Sharma, founder of NeerSoft Technology - a lean product studio from Pune, India. Over the last few years, I've been building SaaS products without a traditional dev team using AI-assisted development to ship real products. Our current portfolio includes CVDeck (career tech), MyListed (real estate), and iMRIVE (NGO impact platform). This month we launched something I've wanted to build for a while: CRM by NeerSoft - a lightweight CRM built specifically ... ... clients over WhatsApp, tracking deals in spreadsheets, and losing follow-ups because no tool was built for how they actually work. Zoho and Salesforce exist - but they're built for teams of 50, not 5. So we built something lean

... output and lean into it. For devs it's Cursor right now. For marketing folks I see Notion/Linear hit that 3x for designers Figma. Curious what tool has been YOUR unexpected 3x? Comment from SARWAR ALAM(@sarwar10): @busmark_w_nika  yes, last week. Comment from SARWAR ALAM(@sarwar10): My go-to tools Keynada A project I recently built to add calming, meditative typing sounds to my workflow, making coding sessions more enjoyable than standard keyboard clicks. VS

... just global ones. I d want to see things like: Median votes/comments by category, not only top launches How competitive each category is over time Comment-to-vote ratio by category Early traction curves: first 1h, 3h, 6h vs final position Best launch days/times by category Hunters with consistent activity in specific niches Similar past launches and how they performed The biggest value would be helping makers answer: What does a strong launch look like for a product like mine ... ... unanswered question does. If you weight them equally, a maker who replies to every easy congratulations and ignores every genuine question will score well on your metric while doing exactly the wrong thing. Even a crude intent flag, question versus

... galdayan): our setup ended up being a Slack webhook per agent session, posted to a channel only that agent writes to. sounds basic but the key part was making the notification say WHY it's waiting (needs approval vs finished vs

... machine I was creating. Then the AI era arrived. In 2025, I started heavily exploring AI coding assistants and vibe coding. At first, it felt magical. Faster output. Cleaner UI. Less friction. It genuinely impressed me. So I leaned into it. But after about 6 months, I started noticing something uncomfortable. The application became harder to reason about. Logic became overly abstract. Simple flows turned into dramatic labyrinths. Code looked intelligent, but felt emotionally disconnected from the product itself. Slowly ... ... keep the ownership/control on your code. Comment from Lawrence Porter(@lawrence_porter): I don't think the future is anti AI development at all . It s probably developers becoming much more selective about where AI accelerates versus

... prefer to review the output of agents, rather than individual actions, and run one or more sessions in parallel. What type of developer are you when working with AI coding agents? For context, when @Kilo Code launched their new @VS Code extension last week , with parallel agents, inline diff reviewer, and multi-model comparisons, some users actually wanted more control back. While the team is working on multiple improvements , like better diffs before you approve and permission flow fixes ... ... curious about your point of view. How do you like to work with AI coding agents? Comment from fmerian(@fmerian): @fberrez1  interesting! fun fact: when @Kilo Code launched their new @VS

... start of the journey, but product quality is what matters above all. Comment from Gangadhar Desai(@gdenterprises005): I think it depends on the type of product you're building, but if I had to choose, I'd lean towards building both at the same time. A personal brand definitely helps build trust, especially in the early days when people are deciding whether to give your product a chance. That said, a strong brand can't make up for a product ... ... eigenst ndige Pr senz wirken kann, ist https://der-arkadenhof.at/ . Comment from YekSoon Lok(@ys_askodin): Having operated on both sides of the table as an allocator and a founder, I view this through a different lens. The binary of "personal brand vs

... them, photo profiles were special in a similar way. When I double checked the profiles, the links were not working. And I hate finding myself interacting with bots. What is the limit that bothers you in interacting with AI vs what feels fine? A/ Interacting with a bot B/ Interacting with content being 100% generated C/ The person giving the idea, and asking AI to write an answer. D/ Asking AI to rewrite E/ Correcting with AI It was funny ... ... safe and always AI-compatible. The thing that can get you fired if you apply it to the wrong deal that's the signal. On images and video: agree with Saad that effort is the better frame than AI vs

... late at night, before deals closed was drown in contracts. 40-page Word documents. Clauses copy-pasted into ChatGPT one by one. Weeks lost to negotiation because there was no legal team, no budget for one, and no good alternative. It looked like a design problem to me. Turns out, that's exactly what it was. So I built Fusial to help him; it's an AI-powered contract redlining for founders and lean

... from the dropdown and you'll see an exploration context that tells the agent to focus on cross-category shopping behavior, brand dynamics, and price range diversity things that only matter for large multi-category retailers. The Gaming pack leans on this heavily: the Idle game context explains prestige cycles and offline earnings, while the Casual game context focuses on ad tolerance and onboarding funnels. Same domain, very different analysis. Analysis Areas Analysis areas define what the agent should look ... ... intervals Each area includes its own detailed analysis prompt. For example, the Conversion Funnel prompt tells the agent to check cart abandonment by price range, compare category-level conversion, and estimate revenue at risk and it defines what "critical" vs