baraklaniado · HN

I audited my AI leaderboard scale – every score dropped 6-15 points

@bengincet · X

@yuangwya · X

@aliamdev · X

TruboRankAI helps brands grow in AI search with an intelligent system built to analyze, track, and improve how AI platforms discover and recommend them.

@hsn6789 · X

is an SEO assistant that combines AI and real human consulting in one simple chat interface.

@st0yanov · X

u/Rabus · Reddit

I got TestingModels too overcomplicated over the month it is running: looking for some feedback how to make it more useful and simpler I run a benchmark like arena.ai , but with pre-generated prompts. So far, nearly 6k people came in and like 30k comparisons has been made - which means the thing is genuinely useful for people to compare the models. The problem is the more features i started adding the more overblown and complicated UI became - like old internet explorer tab bars Old: ht

ATsimbalistov · HN

Show HN: Tracking GenAI cost and endpoint fragility so app teams don't have to

@adamyongseo · X

- AI site builder for local businesses. It can build any design you describe; the sphere is 388 ready-made ones for people who'd rather pick than prompt. Free to spin:

u/TasteMysterious5285 · Reddit

I built AI Census, a live field bulletin for how people are actually talking about AI models I’ve been building AI Census, a public “field bulletin” for how people are talking about current AI models. I kept running into the same problem: benchmark tables tell me how a model performs on a test, but not whether people are actually finding it useful, frustrating, reliable, etc. So I built a rolling view from public technical conversations across Reddit, Hacker News, Bluesky, GitHub, and Huggi

@emmaguetta · X

Claude code for GTM, connected to database signals and LinkedIn

@SamiirHalady · X

Building ReviewMitra: Living Customer‑Centricity If you listen closely enough, your customers will write your product roadmap for you. When I built the goal was simple : help businesses get Google reviews without typing them out. That idea became reality. My first vibe‑coded app took time, but it worked. Then a friend asked, “Can we respond to reviews too?” That one question sparked the next feature : replying directly from the merchant login. Soon, I added sentiment analysis, a word cloud, and WhatsApp integration. Then came support for multi‑outlet brands, and now, a white‑label option for agencies. And here’s the part I’m most proud of - ReviewMitra now generates reviews in 39 languages, including 22 Indian languages and several European and Asian ones. Because trust shouldn’t be limited by language! Every new feature wasn’t planned, it was inspired. By feedback, by curiosity, by conversations. For years, I’ve told clients that the best approach is customer‑