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Show HN: Sales Agent Benchmark – SWE-Bench for sales AI agents (open source)

The idea came from noticing that every sales AI tool demos well on clean summaries but falls apart on real deal data — and there was no rigorous way to measure that gap.How it worksYou register an API endpoint. We send your agent deal context (anonymized real B2B deals), it returns structured recommendations (risks, next steps, stakeholder analysis). A multi-judge panel (Claude, GPT, Gemini via OpenRouter) scores against ground truth — what actually happened in the deal.Two evaluation modes:Summ

Show HN: I killed my Calendly link after people booking randomly

Suggests times that make sense for THIS specific meeting's priority levelExample: A prospect who's been emailing about a deal gets offered your best slots.Someone wanting to "pick your brain" gets next Tuesday at 3pm and nothing else.It's still early—I'm using it myself and with ~10 beta users. The context analysis is basic (email volume, reply speed, keywords) but it's already prevented 3 calendar disasters this week.Built with [tech stack]. Would love feedbac

Show HN: The Frontier, Tracking the LLM Pareto Frontier

- A daily sync to keep the chart up-to-date with new releasesI also just added Latency and Throughput metrics because sometimes latency or throughput is just as important as intelligence.I’d love to hear what you think, especially if you spot any weird model matches (Unfortunately they still happen) or have ideas of what to add next ! I have a few ideas, like combining latency and throughput into one, or even intelligence, latency and throughput, I'll call it Wisdom :)URL: https:/&#x2F

Why Every Business Must Engage with AI – and How to Do It Right

Many failures happen here not because AI doesn’t work, but because teams skip the earlier foundations.The biggest risk isn’t “doing AI wrong.” It’s not building AI fluency at all while the rest of the market moves forward.Once AI systems are in production, new problems appear: cost control, reliability, hallucinations, latency, silent regressions At that point, AI stops being a demo and becomes infrastructure.For teams already dealing with production AI systems, we’ve been thinking a lot about o

Show HN: I turn scattered feedback into a prioritized roadmap in 5 min

Hey HN! I'm Fran, a full-stack dev working on this as a side project. The problem: I've been building SaaS products and the feedback loop is broken. Feature requests come in through Slack DMs, support tickets, emails, Twitter — everywhere except somewhere useful. By the time you look at them, half are duplicates and the rest have no signal on priority. So I built Plaudera — a public feedback board with voting, an embeddable widget, and AI-powered duplicate detection. The AI part is practical, not flashy: when someone submits "add night theme option" and you already have "dark mode support" with 24 votes, it catches that and suggests a merge. Keeps the board clean without manual triage. Stack: Next.js, TypeScript, PostgreSQL. The widget is a lightweight embed — single script tag, no framework dependency. Currently offering lifetime deals at $49 while I'm in early growth mode. Happy to answer any questions about the tech, the AI dedup approach, or the indie SaaS journey. Also genuinely looking for feedback — I eat my own dog food, so Plaudera's own feedback board is at feedback.plaudera.com.

Ask HN: How do you manage flaky E2E tests at scale?

I’m curious how folks + teams here deal with flaky end-to-end tests once a product and test suite gets "big" (> thousands test cases).I’ve seen a few patterns over the years: retries everywhere, quarantining tests, rewriting flows, adding more waits than anyone feels good about, or just slowly losing trust in CI signal. None of them feel great once you have hundreds or thousands of tests running across multiple environments.I’m especially interested in how QA and engineering teams s

Show HN: Personal AI Talent Agency for Content Creators

Sharing something exciting we've been working really hard on for the past month.tldr: 80% of Content creators in the 10k-1M range don't have professional agency representation and spend ~60% of their time on admin around brand deals (brand discovery, outreach, follow-ups, pricing), which is their main source of revenue, by the way. I have led content and growth at a YCw20 and have done ML at LinkedIn and found a burning intersection I can really help with. YC's RFS was pleasant ti

Show HN: Update UK Butchers Meat Price Tracker

Hey all!Following up on a previous post (had a bit of a hug of death) - <a href="https://news.ycombinator.com/item?id=46255827">https://news.ycombinator.com/item?id=46255827</a>Have made a lot of improvements to make it actually useful and move to a stable domain (desktop still best, but it at least works now on mobile):Butcher list - Lots more butchers added to the scraper.Browse by Cut - This is the big one. Instead of scrolling through 1000+ individual products, you can now browse by standardised cut (Ribeye, Brisket, Lamb Leg, etc). I've mapped products from a selection of popular butchers to ~154 canonical cuts. Click a cut and see every matching product across all sites, sorted by price/kg. Looking to improve taxonomy over time with ongoing missed matches/remaps where the automation was wrong.90-day price ratings - I've been collecting price data for a while now, so the site can tell you if a product is at its lowest price in 90 days () or within 5% of that low (). Handy for spotting whether a "sale" is actually a good deal.Fresh vs Frozen indicators - Shows up on both the cut list and product detail pages. Filter by storage type if you only want one or the other.Table layout - Ditched the card grid for a proper table. Much easier to scan prices when everything's lined up in columns. Sortable by name, protein, type, price, number of options, or number of sites stocking it.Full row click - Click anywhere on the row, not just the tiny product name link. Small thing but it was annoying me.Looking for as much feedback as I can get, please share!

Show HN: An API for on-chain swap

Hi HN,I was tired of having to manage gas fees across multiple blockchains and constantly figuring out which chain offered the best rates, so I built an API to solve that.I truly believe that the next billions of dollars flowing on-chain won’t need to know which blockchain they’re on, which protocol they’re using, or have to deal with gas fees at all. Everything will be fully abstracted.So this API allows you to perform swaps on the same chain or cross-chain even when they require multiple txs&#

Ask HN: What is the best bang for buck budget AI coding?

Poor developer here.I'm trying to learn AI coding (already have multiple years experience with "normal" programming in various languages.) I want to know how to make my budget (about $30/month) go furthest.At the moment, I am using:Z.ai $6/month plan:Ok model (GLM 4.7) It seems to rate limit/throttle aggressively if I use it a lot.andGithub copilot $10/month plan:Seems to reduce model context to 100k tokens, and only offers unlimited access to smaller model (GP

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20 Savings Hacks to Use on Your Next Flight

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