... About eighteen months into our product, we hit a wall that wasn't a feature problem. Every new thing we shipped took roughly three times longer than the last comparable one. Bug fixes kept reopening. Two engineers had built quiet, undocumented workarounds around the same broken assumption in our data model, and neither knew the other had done it. The obvious answer was a rewrite. We didn't do it not immediately. We spent a month arguing about it instead ... ... forced us to name the actual problem: it wasn't the codebase. It was one early decision about how we modeled user accounts that everything else had been built to work around. We ended up doing a partial rebuild. Roughly

... convert trials to paid 52% better than non-AI apps, 8.5% against 5.6% at the median. They monetise downloads about 20% better. Realised lifetime value per paying user runs $18.92 a month against $13.59, and $30.16 annually against $21.37 roughly 40% higher on both. The other half, same report: annual retention for AI apps is 21.1%. For non-AI apps it's 30.7%. Monthly retention is 6.1% against 9.5%. Refund rates run about 20% higher, 4.2% against ... ... with is 21% intact and you're wondering what changed. Nothing changed. You just finally got the second number. There's independent data pointing the same way with a sharper edge on it. Kyle Poyar, working with ChartMogul, classified roughly

... watched 68,879 real Google searches in March 2025. Not a survey about how search feels. Actual behaviour. When an AI summary appeared, people clicked a traditional search result on 8% of visits. When it didn't, 15%. Roughly half. They clicked a link inside the summary itself on 1% of visits. And they ended the browsing session entirely on 26% of pages with a summary, against 16% without. An AI summary showed up on 18% of searches ... ... find points the other way 973 ecommerce sites, $20 billion in revenue, 12 months of first-party analytics, more than 50,000 ChatGPT-driven transactions compared against 164 million from traditional channels. ChatGPT referrals were about 0.2% of sessions, roughly

... asking for. Five teams that already process real documents as part of their work. Invoices, delivery slips, receipts, statements, forms, anything where you extract fields and then do something with the result afterwards. One real workflow per team, roughly 20 to 100 documents through space ocr. Redacted is completely fine. I set the fields up with you, and we compare the output against your real values together. The number I actually want. When the extraction is wrong, does space ... ... checks anything afterwards. That is a good place to be, and you probably do not need this. Comment here or email me at oisidonut@gmail.com . It helps if you say what your team does, what kind of documents you process, roughly

... make small conflicting decisions about naming, style, and edge cases, nobody wrote the assumptions down, and the merge is where it dies. Cost reality check, since this is the part nobody quotes: Anthropic's engineering blog put agents at roughly 4x the tokens of a chat session, and multi-agent systems at roughly

... started testing Reddit ads for Causo Fundraising, mainly because Reddit has already been one of our strongest organic acquisition channels. After ~2 weeks: 226 spent 31,483 impressions 165 clicks 0.52% CTR 1.37 CPC ~10 conversions Those conversions have roughly covered the ad spend, so technically the campaign has paid for itself. Still, the results are quite a bit weaker than we expected. The biggest surprise has been the difference between creatives. One ad got 0.052% CTR . Another ... ... That is roughly

... start my own AI-native architect studio Relay Labs. Veritome is the result of my even boy-like fascination in working out logical solution for everyday pain : a production Next.js and Postgres application 105 data models, 350+ API routes, roughly 1,000 automated tests, ten releases in the last month, built and hosted entirely in the EU. I give checkable numbers deliberately. The point is not that I learned to code; it is that the regulatory logic in this product ... ... article-by-article classification, provider versus

... 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 ... ... major platforms LinkedIn, X, Substack, Medium, and Reddit among them. The result: more than 40% of LinkedIn's long-form posts were flagged as fully AI-generated, the highest share of any platform measured. LinkedIn alone accounted for roughly

... efficiency numbers aren't close, and not in the direction I expected. One widely cited test had Claude Code completing an identical multi-file feature task using around 33,000 tokens with zero errors , while Cursor Agent burned roughly 188,000 tokens on the same task and hit several errors along the way, a 5.5x gap for the same deliverable. Separately, other community head-to-heads put Claude Code at roughly

... thinkingmachines : Inkling (Jul 17), Inkling Small (Jul 30) Ant Group : Ling-3.0-flash (Jul 23) Kuaishou : KAT-Coder-Air V2.5 / Pro V2.5 (Jul 10) SenseTime : SenseNova U1.5 (Aug 3) That's 17 vendors, 25+ models, in roughly one month. A new model roughly

... paid conversion. 25%+ with PQL. Webinars (live): 22-33% CTA conversion. High-engagement webinars hit up to 69%. AI search (GEO/AEO): 4-5x higher conversion than traditional organic. One B2B study found AI-referred traffic converted at 7.12% vs 1.37% for organic. Another found 14.2% for AI traffic. Quora: 2-5% conversion. 35% of B2B decision-makers answer questions on Quora. Reddit: 0.3-1.5% post-to-customer conversion in fit subreddits. CPC of $0.50-$2.00 vs

... For a while now, whenever I ve been building different apps, I ve often found myself feeling frustrated and a ...

... before anything became a testable prototype. This release closes that gap. A designer can now sketch a quest, write the branching dialogue for the NPC who gives it, block out the level layout where it takes place, and rough in the UI that displays it to the player, all inside one connected canvas, without switching between four different tools that don't talk to each other. That matters because the biggest time sink in early game development usually ... ... single task, it's the friction of moving ideas between disconnected tools, re-explaining context every time you switch. With dialogue, level layout, and UI mockups now living next to your systems map, a rough

... Predicates work where you own the surface, because you can choose what to serve. Absence works where you do not, because dropping a field is the only move available on a response you receive. So the rule is roughly: predicate what you serve, redact what you receive. The awkward middle is a field you receive and then pass on, which is where most of these systems actually live. Comment from Zeeshan(@zeeshan12): Agent Safety & Blast Radius FFire App Really ... ... scale, we've been compiling some practical approaches to this nothing magic, just real-world patterns for managing agent behavior at the intersection of reach and responsibility. Comment from Dale Mooney(@dalemooney): @alex_amancio_candoa_   @aadilghani  Constant versus

... total. I did exactly that twice. 121 KP total. Forum Threads +58. Comments +48. Reviews +10. Maker +6. Eight forum threads produced that +58. Every comment I have ever written on this site produced +48. So a thread pays roughly 7 KP and a comment pays roughly

... Genuinely curious how bad this problem is for other people, or if it's just me. I track roughly how much time I lose every week just copying stuff out of emails into HubSpot names, companies, deal details, next steps. It's not hard, it's just constant, and half the time I forget to log something until it's too late to actually follow up on it. I ended up building a small AI tool for myself that reads ... ... sales emails and call notes and pulls that info out automatically, with the source sentence and a confidence score attached , with overall analytics so I'm not just trusting a black box. Still rough

... years of domain expertise from big tech, strategy consultancies, and unicorns, systematically cleaned, audited, and structured. The neural layer handles nuance and language. Neither layer works alone. What that means in practice: on rule-bound queries we run at roughly 10% hallucination versus

... 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 ... ... registration, up from 70.1 million in the prior six months. In the first half of 2025, it removed roughly

... thing instead of complaining about it. The idea was simple: make the charting part free, and put an AI on top that looks at the chart and tells you what it sees - patterns, where support and resistance are, roughly where an entry/stop/target would sit. Basically the second opinion I wished I had at 1am staring at a candle. The part I'm weirdly proud of: instead of the AI just sounding confident, I made it keep a public track record ...

... than any Friday report does, just nobody's usually looking for it that early. Genuine Monday question for this community: Do you pay more attention to how your team starts the week, or how they finish it? Has a rough Monday ever turned out to be an early sign of something bigger, before it showed up anywhere else? Comment from Stacy Wycoff(@stacywycof83995): @shahroz_siddique  Good question. It doesn't use one universal definition of "off," it learns ...

... instinct for this: some days I let it just run with a whole feature and barely glance at the diff, other days I'm rereading every line like it's a junior dev's first PR. Right now my rough rule is billing/auth code gets the paranoid review, UI and analytics panels get the "looks fine, ship it" treatment. But that's just a gut feeling, not a real system. Anyone here have an actual framework for this ... ... head right now which isn't great for consistency. Comment from King Joshua Marcos(@moddy): Honestly just trial and error early on. Let it fully own something low stakes, watched what broke, adjusted from there. The billing/auth vs

... 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 ... ... /sec of video output, same rate as Veo 3.1 Fast. Confirmed limitations: Capped at 10 sec of generations for now, no audio reference uploads or scene extension yet in the API, character consistency across scene changes still has rough

... send on fundraising emails? That is a much harder problem. For context, Causo helps early-stage founders find relevant investors and run cold fundraising outreach without manually building lists, writing everything from scratch, or duct-taping 5 tools together. Rough numbers so far from the fundraising product: 272 founders signed up in the fundraising flow 253 created a company profile 92 completed onboarding 90 got matched with investors 38,000+ founder/investor matches generated 117 outreach campaigns built 38 campaigns launched ... ... more than speed when fundraising is involved Launch spikes are real, but they fade quickly Pricing early is mostly a learning tool Content compounds, but only if it is actually useful Personal emails beat automated lifecycle slop People forgive rough

... source spam filter called SpamAssassin doing the filtering. That world is gone. On the consumer side, Gmail launched in 2004 and gradually took over. By 2015 it had overtaken Hotmail as the most popular US email provider, and today roughly three-quarters of US adults aged 18 64 use it. Source: https://www.statista.com/chart/3... The business market consolidated along the same lines, just a few years behind. Google launched G Suite (now Google Workspace) in 2006. Microsoft responded with Office ... ... Today those two products account for roughly

... 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 Elias(@elias ... ... demo just becomes the thing that confirms or kills the read you already formed from the description. A slick demo for a problem I don't recognize gets an "impressive, not for me" and a scroll past. A rough