... output_tokens, OpenAI reports it separately. Pass it twice and you ve paid twice on paper. Idempotency, which I d never heard of: if a send fails and you retry, but the first one landed, that request now counts double. A stable key per event lets the server skip the repeat. Retry on timeouts and 5xx, never on a 4xx, since a bad payload stays bad. None of that fits in a line someone copies off a docs page ... ... holds it. track() never throws or blocks your request. The adapters (fromOpenAIUsage(), fromAnthropicUsage()) only rename fields, and a missing field comes back undefined, never 0, because a 0 looks like a real number. I still got one wrong. I double

... into the attachment name on the email that reaches the client of the seller, and into a path when a command writes the PDF to disk. In August a review tried it against real responses. A number containing a double quote closed the filename early, and everything after it was read as further header parameters. A number containing a newline made the header invalid, and the download answered 500 on an invoice that rendered fine everywhere else. A slash ... ... into the document. The check for your stack: search for Content-Disposition, attachment names and file paths, and for each one ask where the name comes from. If any part of it is text a user typed, try a double

... webhook fire sequence before going live. Testing is either skipped or scripted in isolation against mocked responses that don't reflect real API behavior. What does prod surface? The edge cases. Rate limits, flaky webhooks, card declines mid-flow, double-charges on retry. The stuff that only shows up when real money or real users are involved. What we're building toward: connect FetchSandbox MCP, prompt "make this app survive in prod," and the runtime reads your app config, infers ... ... relations, not assertions about what the right outcome is. The one you're looking at says: delivering the same event twice should leave the state the same as delivering it once. We don't say what happens on a double

... Fable 5.1 is here and it builds small worlds Anthropic s newest model just went live in the Happycapy model picker. The benchmark story is that it more than doubled its predecessor on frontier science. The better story is what it does with a free afternoon. Fable 5.1, Anthropic s newest model, went live on September 1, 2026, and it s in Happycapy today. It s the latest model in the Claude 5 family and part of the Mythos-class ... ... across a task far too long to hold in your head. The headline number is the one every launch post will lead with: on Terminal-Bench-Science , a benchmark for autonomous scientific computing, Fable 5.1 scores 52.6% more than double

... break top 5. Thursday needs 235. That's a 70-point gap just from picking a different day. Weekends aren't just easier, they're way less crowded Tuesday averages 30.4 launches a day. Saturday averages 10.7. Fewer competitors, lower bar, most of the effect comes from volume, not some algorithm quirk. If you can't launch on a weekend, Friday is your best bet 205 median points for top 5, the lowest of any weekday and noticeably easier than ... ... Thursday. Tuesday's hidden trap Tuesday has more total launches than Monday (1,064 vs

... also categorized as AI: Fathom 3.0 = Productivity + AI + Meetings Goldfish = Productivity + AI + Mac  PollyReach = Productivity + AI + Virtual Assistants OpenHuman = Productivity + AI + Open Source Upstream = Productivity + AI + Email Coming in third was the Developer Tools category, which more than doubled its growth from the previous year and saw several very large launches: Kilo Code v7 for VS

... expanded beyond a Gmail-only beta and removed the waitlist. I had resisted opening up because Ting still occasionally made mistakes. I worried users would be upset. I was wrong. Restricting access was restricting our signal. We quickly doubled from 100 users to 200. Every user had to connect both their calendar and email, so this was a high-trust product. We were happy with the growth. September Said 'largest PC manufacturer' went through a reorganisation. The opportunity disappeared. That ... ... market: I speak Portuguese, Mariana is Portuguese and my wife is Brazilian. We ran a test in Portuguese. We recruited 100s of Brazilian users in three weeks, mainly thanks to Ting on WhatsApp. IYKYK . December Based on competitors

... didn't either. I wrote the fixtures, so I never thought to send the same event twice. My assumptions were just checking my assumptions. What actually caught it Running the failure. Deliver the event, deliver it again, watch the double-credit, add the dedupe, run it again, watch it hold. Agents probably make this worse because they learned from the same quickstarts that only imagined one clean event. Curious what broke for you A bug that sailed through review ... ... think to do it, and most of this thread is about how you usually don't. for the ones that slip through, detection's tougher, and for the same reason: your logs and db agree with themselves. a double

... call to surface the AI's mark as a suggestion to review, not a final score, because presenting it as settled felt dishonest. Curious how others building agent/AI tools are drawing that line different UI for "AI generated this" vs "AI judged this," or same treatment either way? Comment from Ghost Kitty(@ghost-kitty-10042916): Comment Deleted Comment from Ghost Kitty(@ghost-kitty-9637647): Comment Deleted Comment from Farrukh Ahmed(@farrukh_ahmed8877): @new_user___090202674ab6e030a7a9c52  That s exactly what ... ... farrukh_ahmed8877): @luke_bell  True, and it's a little uncomfortable how much that one word is doing. Same confidence, same model, same output the label is the only thing that changed, and it still shifts whether someone double

... After the initial launch spike on Product Hunt, most early-stage founders face a critical fork in the road: whether to double down immediately on aggressive paid distribution or spend those first weeks refining onboarding based on launch feedback. From analyzing recent SaaS releases, a recurring pattern shows up: startups often see high top-of-funnel traffic during launch week, but bounce rates spike on cold channels (like LinkedIn or Meta Ads) because abstract AI features are hard to demonstrate ...

... only caught it because I kept trying to remember who I was supposed to be meeting. The interesting part is I still use it for the same task; I've just learned which of its confident moves to double-check. It feels a bit like working with a sharp new hire who's still finding their footing. When did you first notice your AI agent needed a second look, and did you stop using it or just build a workaround ... ... needs attention" with total confidence, and I trusted it right up until it was wrong about something that mattered. What actually fixed it wasn't a smarter model, it was forcing it to rate its own confidence honestly, Verified vs

... when users came back after a gap, the app acknowledged the gap without judgment. "It's been a few days. No need to catch up. Start wherever you are." No prediction. No nudge. Just patience. Retention over 30 days doubled. Not because we were bringing people back more aggressively, but because the people who came back felt safe doing so. They weren't returning out of guilt from a notification. They were returning because the space was still there, unchanged ...

... touch a thing. 3. Budget pacing and overspend forecasting. Projects end-of-month delivery. Flags blown budgets early. 4. Creative performance breakdowns. Ranks every ad by ROAS, CTR, CPA across both platforms. 5. Cross-channel attribution checks. Flags double-counted conversions between Google and Meta. 6. Audience overlap and wasted spend detection. Finds the ad sets cannibalizing each other. 7. Search term mining and negative keyword lists. Finds the negatives I should have added last month. 8. Landing page ... ... tracking QA. Checks every URL and pixel fire in the account. 9. Competitor

... Overviews and AI Mode. This is the baseline for any AI visibility strategy. Identify which pages perform best in AI answers. The reports show you which URLs are surfaced most often. You can see what content actually works and double down on it. Monitor your AI performance across different countries. The reports include geographic data. You can see if your content is more visible in one region and less visible in another. Understand device-specific performance. The reports include device ... ... data is now available. There is no excuse for guessing. The report is rolling out now to a subset of sites before full availability . Start checking your account. The bar has been set. If you have data and your competitors

... 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 ... ... Gemini, since more buying decisions now start there instead of traditional search. If you want to see how an AI agent currently reads your own site, we put out a free tool that shows what an AI fetches vs

... Helps me a lot with competitor research and content writing. - Lovable - I don't have a lot of resources at hand, so if I want a new landing page design or I want to add a feature to our existing product, Lovable makes the execution easy. - SemRUSH / Ahrefs - I am a big content and SEO nerd. What are competitors

... have actually diverged in outcome in the ledger so far and if it's inferred, what's your cold-start before a single divergence has been observed? Comment from Alexander Bering(@alexanderbering): @aadilghani  The reason "edit vs. tell-it-to-revise vs

... start from where i'm sitting: i talk to founders, hiring managers, and recruiters every week, and the same conversation keeps coming up. nobody trusts their pipeline anymor Application volumes have doubled since 2021. Cheating on technical assessments doubled

... brand didn't need to be constructed. It needed to be uncovered. Build your product first. The brand is already happening whether you notice or not. Comment from Ali Berk Canli(@abcanli): I think personal branding is a double-edged sword. If people like you too much, they stop being honest about your product's bugs. I m building a local AI tool right now and I d rather show my technical struggles than a fake CEO image ... ... think "build the brand" advice sometimes becomes an excuse to not build the hard thing. Comment from Piyush Gajrani(@piyush_teq): @busmark_w_nika Most founders don t fail at brand vs

... most important and challenging experiences you ll have as a founder is fundraising. I pitched VCs across London and San Francisco. Some spent 15 seconds on my deck. Some took the call just to diligence a competitor. One told me to ask for more money. Oh, and I found out your pitch is probably being recorded and run through AI. This is the high-impact version of all of those lessons to save you time, energy, and emotional damage. Please ... ... just politely wait for your turn to talk. Ask questions. Do they invest in your market? Do they lead or follow? Etc. You can learn very quickly whether the meeting is worth your energy, or where to double

... Last month, I did something that felt slightly insane. I took our product description, fed it into ChatGPT, and asked it to build a competitor. Not a parody. A real competitor

... standard ranked order . Hidden Points To keep the focus on the products rather than the "score," all points will be hidden from public view to encourage the community to vote based on merit, not current rank. The "Double" Boost Here is the kicker: Every vote cast during a randomized period counts for double

... Maybe more. Here's the painful truth: Your site is translated. Your AI visibility isn't. When a German user asks ChatGPT in German about your category, you're invisible. When a French prospect searches Perplexity in French, your competitor shows up. Translation AI visibility. And it's costing you. The Data We tracked 200 SaaS companies with multilingual sites at Rankfender. Market % Visible in Local AI Answers US (English) 64% UK (English) 58% Germany (German) 22% France (French ... ... Founder: B2B SaaS, 8M ARR "We spent 40k translating our site into German and French. Beautiful work. Native speakers. Perfect messaging. Six months later, we checked German AI answers about our category. We weren't there. Not once. Our competitor

... found errors. Average cost: 28k." 120k impressions, 400+ new signups. Free resource: Post as a human. Share what you're learning in real time. People don't follow companies. They follow people. 5. Multi-Language: The Hidden Channel Most competitors track AI in English only. We built for 120+ languages from day one. Why: A German user asks in German. AI answers in German. If you're not in German content, you don't exist. One example: A US SaaS ... ... with perfect German translation had zero German AI mentions. A local competitor

... form opinions based on how inclusively you conduct public conversations . Finding #4: Page Structure Drove Citations Product Hunt's own AEO case study showed clear patterns. Change Impact Adding FAQ section 10x ChatGPT citation rate Google AI Overview citations Doubled after FAQ addition Category page impressions +200% after Q&A content Terminology matters. Product Hunt changed a page title from "The best AI dictation apps" to "The best AI dictation and speech-to-text software." Result: citations tripled overnight ... ... language people actually ask , not just what they type . Finding #5: One URL Can Carry You For Superwhisper, one single Product Hunt URL drove 1.6% of their ChatGPT visibility and 5.5% of Google AI Overview visibility. Compare that to competitors