... spent a day trying to fix something and could not. Nothing worked. I tried everything I could think of. Then I remembered I had deleted a block of code months ago because I thought it was useless. It was not useless

... spent a day trying to fix something and could not. Nothing worked. I tried everything I could think of. Then I remembered I had deleted a block of code months ago because I thought it was useless. It was not useless

... check my competitor's product every morning. Not productively, not with a plan. Just a quick scroll to see what they are doing. It is the worst ten minutes of my day and I keep doing it. I never feel better afterward. I feel either behind or briefly superior, and both are useless

... check my competitor's product every morning. Not productively, not with a plan. Just a quick scroll to see what they are doing. It is the worst ten minutes of my day and I keep doing it. The thing is, I never feel better afterward. I feel either behind or briefly superior, and both are useless

... Spent a lot of time analyzing competitors before launch, but once building started, all those notes became outdated pretty quick. Tracking everything daily creates useless

... also left me with a problem: now I know about a real issue, and fixing it will take a month, and the person who told me is already gone. So the feedback is useful for the future and useless for the person who gave it. Do you ask churned customers why they left? And does the answer ever actually change what you build, or does it just sit in a doc? Comment from Hisashi Space(@hisashispace): Yes, I always ... ... point of cancelling. So in your shoes, I might offer that person a year at half price as a thank you for the honest feedback. They might just come back. Comment from George Basov(@gbasovv): On the "useless

... decided to spend an entire Sunday finding free or cheaper alternatives to my current app subscriptions, mostly by digging through Product Hunt and old bookmarks. I made a list, set aside the day, and went through my tools one by one. The task manager was the easiest swap. I found a free one in about ten minutes that does everything I need, plus a few extra features I did not expect. The password manager was much harder. I tried ... ... felt too clunky to stick with, so I kept my paid plan. The cloud storage swap was an absolute disaster. I spent two hours migrating files before realizing the free tier had a file size limit that made it useless

... through them again, turn some off, allow a few back in, change Focus settings then somehow I m back to getting random alerts all day. The weird thing is I don t actually want fewer notifications. I want fewer useless ones. If someone messages me, fine. If an app wants to tell me about something that happened 9 hours ago, I really don t need that on my lock screen. Is there anything that handles this more intelligently ...

... Apple's own support pages. Apple In-App Purchase: 26%, or 15% if you're in the Small Business Program, the Mini Apps or Video Partner Programs, or on an auto-renewable subscription after the subscriber's first year. Alternative payment processing inside your app: 20%, or 10% for those same groups. Out-of-app offers with an actionable link: a 15% store services commission, or 10% for those groups, on anything bought within 7 days of the tap. Apps ... ... distributed outside the App Store entirely - an alternative

... That s the serious version of the story, and it s true. Here s the one we d rather tell. One afternoon, we stopped handing Fable 5.1 science problems and started asking it to make things beautiful, faintly useless, entirely delightful things. It built three. Watch first; we ll walk through them underneath. The whole pitch, in one line Anthropic built it to solve frontier science. We asked it to shake a snow globe. Turns out that s the same ... ... scientific computing) 52.6% Fable 5: 24.7% Opus 5: 29.0% Context window 1,000,000 tokens hold a whole codebase at once Max output 128,000 tokens a full build in one pass Prompt-cache reads up to 75% cheaper vs

... 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 can make an agent feel useless. If I have to approve every tiny step, I m basically doing the work myself again. But too little confirmation creates the opposite problem: the agent may save clicks while adding anxiety. So the UX question I keep coming back ... ... hard-to-reverse consequence. I m curious how other people building agentic products think about this. Do you use a similar risk / reversibility framework, or have you found a better rule for deciding when an agent should act vs

... ones were five star. 93% had the "verified purchase" label, so even that badge doesn't mean what people think it means anymore. The part that got me: real reviews mention weird, specific, slightly annoying details. "The manual was useless but I figured it out." AI written ones glide right past that. They praise smoothly and specifically avoid describing anything a person would actually notice. Once you know to look for it, you start seeing it everywhere. Feels like ... ... opposite, really: a five-star review that still admits something mildly annoying is often more trustworthy than a five-star review with zero friction in it at all. Comment from Sabber Ahamed(@sabber_ahamed): the "manual was useless

... breaks in real use. Here's why It answers what you asked, not what you mean. "Why did the signups drop last week?" turns into a query that spits out a few numbers. The numbers are often right and useless. It doesn't tell you if the drop is real or just noise. It ignores sample size. LLM will cheerfully tell you A beats B based on 30 data points vs

... assistant specifically designed for early-stage founders. Here's what it actually does: Structured decision analysis You describe your decision, and it walks you through a framework (not just a "do this" answer, but a real evaluation: risks, assumptions, alternatives) Pattern recognition It learns your decision-making patterns over time and flags when you're repeating mistakes Blind spot detection It asks the questions you're not asking yourself It's not a replacement for intuition or community ... ... good?" it's "when do you actually use it?" I'd love your feedback on: What decisions are you currently struggling with as a founder? And if you've used AI decision tools before what made them useful or useless

... across your network. Perfect for a printer, a NAS, a phone. Wrong for the Mac you're sitting at A dev server on 127.0.0.1:3000 genuinely refuses connections from anywhere else so the check says "closed". Accurate, and completely useless. The most interesting services on the machine you care most about are exactly the ones a network probe can never see. Local Services a new tab on This Mac that doesn't probe anything. It asks the system directly, then ... ... that way: The Ports tab on a network device, grouped by category Also fixed: a closed port now says closed. A port that actively refuses a connection was being reported as filtered and those mean different things. Nothing listening, versus

... release the supply-chain scan could only talk in the present tense: here is what auto-executes right now, here is a commit tip that looks forged. Useful if you happen to scan while the implant is sitting there. Useless for the two questions you actually have when a worm is circulating did something change, and what could whoever got in reach? Now: every scan records a fingerprint of what auto-executes in the repo, and the next one tells ... ... scan? Comment from Rabnoor Singh(@rabnoor_s): @gfazioli  On how far back to keep it: I would stop treating retention and scoring as the same knob, because they have very different costs. Scoring past 30 days is genuinely useless

... inside your app if they can only feel understood while they're talking to your model you haven't solved loneliness. You've made it more comfortable to stay lonely. You've built a very sophisticated waiting room. The alternative is to design for the exit. Concretely, that means three things. Point users back at real people, not deeper into the app. The most valuable thing an emotional AI can do isn't be a better listener than your friends ... ... been avoiding. Rehearse the hard talk. Untangle what you actually feel before you say it out loud. Then get out of the way. Refuse the agreeable-mirror trap. An AI that always validates you is engaging and useless

... first six items decide whether a launch deserves to do well. The seventh decides whether it does. I was reading them as one list. Where I think the standard advice falls short: "build an audience first" is true and useless, because it does not say what an audience is made of. From today, I think it is two specific things, and neither of them is upvotes. One, people who have had an actual back-and-forth with you. Not people ... ... threads have pulled more follows between them than every reply I've left combined. Drop your link Sunday and I'll read it properly, and I'd like to know your follower count the night before versus

... suppose. That's the gate I was describing, and you just found the tell it doesn't catch. Taking the note on the dashes. Comment from Aria(@ariajinling): I agree: degradation has to be an explicit, author-authored alternative, not a timeout-time improvisation. If an action has no degraded form, it needs a stronger escalation path or a shorter approval window. For partial work, I would preserve a compact execution ledger: completed steps, external effects, and the invariants ... ... there's no shared webhooks folder they both sit under. so the glob fix doesn't even apply to the three i have today, they were never colocated in the first place. which proves your enumeration vs

... what the actual job entails. Developers have noticed. Only 12% of developers use LinkedIn as their main source of technical information, according to a Stack Overflow survey. Most are on the platform purely because they feel they have no alternative, not because they find it genuinely useful. The Fake Everything Problem LinkedIn has a trust problem that is getting dramatically worse, not better. In the second half of 2024, LinkedIn identified and removed 80.6 million fake accounts at the point ... ... fake professionalism intolerable. The content culture on LinkedIn actively rewards performance over substance. Emotional posts that make people feel something outscore technical posts that actually teach people something. This is fine for the platform's engagement metrics. It is useless

... this community thinks: - Do you actually trust r sum s, or are they just a habit at this point? - If not r sum s, what would you rather see before deciding to interview someone? - For those who hire: what's the single most useless part of your current process? Would love honest takes, especially from people who hire regularly. Comment from Rahul Reddy (@rahulreddy01): @sebastian_patterson  If I had to remove one step, it would be using resumes as the primary screening filter ... ... video of just one question: "Tell me about yourself." Most of the time, the intro call really shows a lot about communication, storytelling skills, and so on. Scanning through hundreds of resumes and portfolios is the most useless

... problem I keep hitting: Telegram communities are full of buying signals people asking for tool recommendations, complaining about a workflow, looking to switch vendors but reading every thread manually doesn't scale, and scraping members is spammy and mostly useless. What's actually working for you? - How do you decide which communities are worth monitoring? - What signals tell you someone is genuinely in-market vs

... without now. Comment from Stacy Wycoff(@stacywycof83995): @nolan_vu  Thanks Nolan, really appreciate you reading it closely. The confidence grading came straight from beta feedback, people have been burned by tools that state guesses as fact, so "Verified" vs "Monitor Only" ended up mattering more than any feature. I'll take a genuine look at AI Hive. Comment from Waqas Baloch(@waqas_baloch4): Building Glint , a neutral trust and control layer for AI coding agents. Glint plugs into ... ... planning, from idea to celebration. Plan your occasion, discover vendors, manage your budget, coordinate tasks, and bring everything together in one place. www.tendr.co.in Comment from Richie Varghese(@ric_v36): What you're building: Building NexQL, a PostgreSQL extension for VS

... 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

... tired of the noise in technical analysis. Some people swear by RSI, others rely on EMAs. But when you try to average them, you realise a static average doesn't work because different indicators dominate different market regimes (trending vs cycling). To solve this, I spent the months building an engine (TickerSignals) that scores 39 indicators across 6 layers daily for 2,500+ stocks. To calibrate the weights, I backtested roughly 2L+ historical signals. Here are my two biggest takeaways ... ... from the data: Standard averages lie: Averaging indicators is useless