... leadership." Copy, paste, post. Zero lived experience, zero original thought. It's just AI slop in a blazer. AI-written emails to people who matter. Your client can tell. Not because the grammar's off because the warmth is. VS GOOD AI JUDGEMENT Using AI to actually look at what a candidate did. Not keyword-matching a CV pulling apart their portfolio, cross-referencing their claims. You still decide. You just decide better. Using AI to draft, then making ... ... scores across different domains, "critical thinking" which is one of the key markers of how AI fluency is measured, is lowest in students. Approach the findings with a grain of salt of course, as this is a self selected sample

... 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

... years by people who cared about how it feels to use. Dark, considered interfaces. Whitespace that isn't accidental. Content that is the product, not decoration bolted onto a spreadsheet. The short answer to "what's the best LinkedIn alternative in 2026" is this: builders aren't looking for another feed. They're looking for a professional network that was actually designed, not just maintained. That's the gap forg.to is built to close. Here's why the gap exists ... ... highest share of any platform measured. LinkedIn alone accounted for roughly two-thirds of all AI-generated content Pangram detected across every platform in the study, even though its posts made up only about a third of the total sample

... something different. We're still arguing about the mix internally. So, for anyone whose product needs an input before it does anything, a spreadsheet, a repo, a calendar, a dataset: did you solve the cold start with sample content, and did people ever graduate from the samples

... bound to fall behind. I call this the "entry phase." Like you, I successfully navigated this stage. However, the next challenge awaits: conversion. Anyone with experience in e-commerce knows that the 4P strategy is used to boost conversions. Alternatively, one can keep the conversion rate constant (mine, for instance, is a very average 5%)and focus on maximizing impressions. External advertising and social media activities are examples of ways to maximize impressions. I have recently begun testing in this ... ... channels where content is accessible to everyone. That is why I created a "YouTube Lab." I will not mention or discuss my specific YouTube account here, as doing so would compromise my authenticity. I use a selfie and a sample

... annoying part is that creating this data manually can take a surprising amount of time. Basic fake data is easy to generate, but realistic data that actually looks useful for testing and demos takes more effort. I built AI Sample Data to help with this problem. I am curious how other developers handle sample

... really interested in how you evaluate your agents in production. The standard approach is sample, LLM as judge and possibly a golden dataset. That seems to be the standard setup. But the challenges include: model drift, who is reviewing the llm and it's not live... I'm looking for who is doing world class evaluation on agents, would love to hear how the community is doing it. Matt Comment from Matt Doughty(@matt_doughty): @alieksia ... ... first class functionality is tokenless evaluation - quality and risk. My broader focus is to create examples where tokenless evaluation can be layered so that you only bring in an LLM when there is a problem, rather than just sampling

... best with. Comment from Arnold Oshenye(@oshylabs): @pamela_arienti  Yes, and the number is small enough that your objection is fair. Single figures per product, informally, mostly people already in a conversation with me rather than a recruited sample. The reason I still trust it is that comprehension and demand need very different sample

... people getting comfortable, which you already said yourself. Does Pushary let the customer define that ladder, or is the destination something you configure for them? 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 ... ... nothing, not I could not look. An empty inbox and an unreachable inbox both return zero items, and a precheck is exactly where that ambiguity gets rebuilt one level down. Comment from Dale Mooney(@dalemooney): @aadilghani   The gate versus

... more people struggle :D it gave me courage. :D Comment from Sabber Ahamed(@sabber_ahamed): @busmark_w_nika   @abdullah_javaid3  the random-id-on-activation trick is the right call. weekly active hides exactly the churn-vs-loyal split you're describing, twenty once-and-done and twenty daily users report the same number. Comment from Jin Ci(@youliqn): Love this question it's something I wrestled with while building my party game (Salad Bowl Game). Here ... ... only one using your own product daily, that's actually not nothing! It means YOU have the problem you're solving. The question is whether others share that same problem. What's been your experience with early user feedback vs

... pieces cited across four client brands on day one of tracking. And it has a clear favourite surface so far: almost every one of those citations is a Medium post (one Paragraph piece snuck in). This is a small sample ofc, and we'll share a proper breakdown once we have enough fetches to trust the pattern. If you ran an audit during launch week, your tracked queries now include Claude citations automatically. Worth a re-look to see where ... ... Claude is responding more to the platform, the structure, or just crawlability. Comment from Omri Ben-Shoham(@omri_ben_shoham1): the Medium bias for Claude citations is a really useful early signal, especially if that holds up as the sample

... goal: if you want raw eyeballs go Tue-Thu, but for a badge/ranking with a modest following a weekend can punch above its weight. Comment from Sabber Ahamed(@sabber_ahamed): @busmark_w_nika   @abdullah_javaid3  the invitation vs favor framing is the most useful line in this whole thread. i caught myself drafting DMs that were basically upvote asks in a nicer outfit. what actually worked was showing up in threads like this one for weeks with nothing ... ... only to personal story (my coding skills are limited since I am trying to learn coding) :D Comment from Nika(@busmark_w_nika): @dinocorreia  To be honest, for now, I was able to find only one competitor

... recently compared Toolyzo, GPTZero, ZeroGPT, QuillBot, and Copyleaks using the exact same writing samples. One thing surprised me: The same paragraph received completely different AI scores depending on the detector. One human-written sample

... there, what are you missing? Let us know! -- Additionally, I've compiled here the list of top currently available resources on Tyto and ai-coustics SDK to help you get started. Tyto documentation Launch blog with samples Post-call analysis tutorial Live demo app Comment from Ghost Kitty(@ghost-kitty-9958581): Comment Deleted Comment from Zajin Dacos(@zajindacos123_coder): i'd love to see more before and after audio examples. hearing the difference would probably answer most of my questions ... ... issue with machine-first enhancement is that the outcome is not pristine, like you'd expect with perceptual (human-to-human) enhancement - on purpose. That's why we usually include quantitative performance as well, like WER improvement. What samples

... transcribe, then cut video like editing a Google Doc. Delete a sentence, the timeline cuts itself. Smart Cut one-click filler word + silence removal, running locally via FFmpeg Voice cloning & TTS clone any voice from a 6-second sample; 22 Indian languages via Sarvam AI AI Video Generation Hub 9 models across 5 providers (Runway, Pika, Kling, MiniMax, Luma ) AI Co-Pilot Agent type "make this a 60-sec reel with captions and music" it plans the steps ... ... mean it structurally "data never leaves your infrastructure" is the one privacy claim a regulator can't argue with. Respect. One spicy thing even self-hosting can't get you out of though: voice cloning from a 6-sec sample

... that problem showed up on their own. which leaves me with a weird conclusion i dont fully trust yet: the loud, scalable stuff performed worst and the slow, unscalable stuff performed best. maybe thats just my niche, or my sample size of one. so im curious about your data points. whats a distribution move that worked way better than it had any right to? and whats the standard advice that did nothing for you? Comment from Anastasiia(@alieksia): Hi Artem ... ... thanks for writing it up :) It seems to me as less about effort or volume and more about what you're actually doing: touching a real problem vs

... Apple Music on Mac can show Lossless but what is your Mac actually outputting? Audex Trace shows: the actual playback format bit depth and sample rate your Mac output sample

... real audio, not just testing one prompt in a browser tab. What changed: 100+ studio-quality voices Local generation on your desktop Scripts stay on your machine No per-character meter on paid plans Voice cloning from a consented sample on paid plans Voice Design and Omni in Pro for broader voice creation and 600+ languages Script workflow, retakes, mastering, and export in one app I built this because cloud TTS pricing punishes iteration. Retakes, pacing fixes, pronunciation edits ... ... alternate

... based. We wanted an editor that stays on your hardware. Here's what you get: AI that runs locally: - Edit video by editing the transcript delete a sentence, the timeline cuts itself - Clone any voice from a 6-second sample - Remove filler words and silences in one click - Generate AI video from text using 9 models across 5 providers (Runway, Pika, Kling, Luma, Seedance, or run CogVideoX locally for free) - AI co-pilot: describe your goal in plain English ... ... clips - Audio effects chain (EQ, compressor, reverb, de-esser, limiter) - LUFS loudness normalization for YouTube/Spotify/podcasts - Beat detection with snap-to-beat - Batch export with 8 platform presets 30+ languages including 22 Indian languages via Sarvam AI unmatched by any competitor

... 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 non-question, lifts the metric considerably. The classification does not need to be perfect; the cost of ignoring the distinction is higher than the cost of occasional misclassification. Presence window as the third dimension looks right. The three together give ... ... congratulations fastest, which is the behaviour you are trying to catch. Median time to first reply on questions only is the honest version. Same denominator caveat applies, with few questions it gets noisy, so show it but mark low sample

... 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 Tommy Kang(@sjtkang): What I'm building ... ... worth ad dollars at a tiny budget, and which are a money pit? I'm doing daily build-in-public content on TikTok, YouTube Shorts, and X, but I honestly can't tell yet what's driving downloads versus

... checking out Audex Trace. Trace is a small macOS app for Apple Music that shows what s actually playing not just the badge. It can show: The actual playback format: AAC / ALAC / Lossless / Hi-Res / Dolby The Mac output sample rate Whether playback and output are matched Playing Next quality estimates Skip warnings before a queued track may fail or skip A few people pointed out that concrete examples make the value much clearer, so I m improving the page ... ... around cases like: Lossless badge, but output sample

... 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

... turned my free Alibaba quote sanity check into a small paid review service for ecommerce sellers who already have a supplier quote, sample order, or freight quote in front of them. The problem I keep seeing: sellers get a quote with unit cost, MOQ, sample

... 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