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Trump Vodka Becomes Available for Pre-Orders

https://www.forbes.com/sites/kirkogunrinde/2025/12/01/trump-vodka-becomes-available-for-pre-order...
1•stopbulying•36s ago•0 comments

Velocity of Money

https://en.wikipedia.org/wiki/Velocity_of_money
1•gurjeet•3m ago•0 comments

Stop building automations. Start running your business

https://www.fluxtopus.com/automate-your-business
1•valboa•7m ago•1 comments

You can't QA your way to the frontier

https://www.scorecard.io/blog/you-cant-qa-your-way-to-the-frontier
1•gk1•8m ago•0 comments

Show HN: PalettePoint – AI color palette generator from text or images

https://palettepoint.com
1•latentio•9m ago•0 comments

Robust and Interactable World Models in Computer Vision [video]

https://www.youtube.com/watch?v=9B4kkaGOozA
1•Anon84•13m ago•0 comments

Nestlé couldn't crack Japan's coffee market.Then they hired a child psychologist

https://twitter.com/BigBrainMkting/status/2019792335509541220
1•rmason•14m ago•0 comments

Notes for February 2-7

https://taoofmac.com/space/notes/2026/02/07/2000
2•rcarmo•15m ago•0 comments

Study confirms experience beats youthful enthusiasm

https://www.theregister.com/2026/02/07/boomers_vs_zoomers_workplace/
2•Willingham•22m ago•0 comments

The Big Hunger by Walter J Miller, Jr. (1952)

https://lauriepenny.substack.com/p/the-big-hunger
2•shervinafshar•24m ago•0 comments

The Genus Amanita

https://www.mushroomexpert.com/amanita.html
1•rolph•28m ago•0 comments

We have broken SHA-1 in practice

https://shattered.io/
9•mooreds•29m ago•2 comments

Ask HN: Was my first management job bad, or is this what management is like?

1•Buttons840•30m ago•0 comments

Ask HN: How to Reduce Time Spent Crimping?

2•pinkmuffinere•32m ago•0 comments

KV Cache Transform Coding for Compact Storage in LLM Inference

https://arxiv.org/abs/2511.01815
1•walterbell•36m ago•0 comments

A quantitative, multimodal wearable bioelectronic device for stress assessment

https://www.nature.com/articles/s41467-025-67747-9
1•PaulHoule•38m ago•0 comments

Why Big Tech Is Throwing Cash into India in Quest for AI Supremacy

https://www.wsj.com/world/india/why-big-tech-is-throwing-cash-into-india-in-quest-for-ai-supremac...
1•saikatsg•38m ago•0 comments

How to shoot yourself in the foot – 2026 edition

https://github.com/aweussom/HowToShootYourselfInTheFoot
1•aweussom•38m ago•0 comments

Eight More Months of Agents

https://crawshaw.io/blog/eight-more-months-of-agents
4•archb•40m ago•0 comments

From Human Thought to Machine Coordination

https://www.psychologytoday.com/us/blog/the-digital-self/202602/from-human-thought-to-machine-coo...
1•walterbell•41m ago•0 comments

The new X API pricing must be a joke

https://developer.x.com/
1•danver0•42m ago•0 comments

Show HN: RMA Dashboard fast SAST results for monorepos (SARIF and triage)

https://rma-dashboard.bukhari-kibuka7.workers.dev/
1•bumahkib7•42m ago•0 comments

Show HN: Source code graphRAG for Java/Kotlin development based on jQAssistant

https://github.com/2015xli/jqassistant-graph-rag
1•artigent•47m ago•0 comments

Python Only Has One Real Competitor

https://mccue.dev/pages/2-6-26-python-competitor
4•dragandj•49m ago•0 comments

Tmux to Zellij (and Back)

https://www.mauriciopoppe.com/notes/tmux-to-zellij/
1•maurizzzio•49m ago•1 comments

Ask HN: How are you using specialized agents to accelerate your work?

1•otterley•51m ago•0 comments

Passing user_id through 6 services? OTel Baggage fixes this

https://signoz.io/blog/otel-baggage/
1•pranay01•51m ago•0 comments

DavMail Pop/IMAP/SMTP/Caldav/Carddav/LDAP Exchange Gateway

https://davmail.sourceforge.net/
1•todsacerdoti•52m ago•0 comments

Visual data modelling in the browser (open source)

https://github.com/sqlmodel/sqlmodel
1•Sean766•54m ago•0 comments

Show HN: Tharos – CLI to find and autofix security bugs using local LLMs

https://github.com/chinonsochikelue/tharos
1•fluantix•55m ago•0 comments
Open in hackernews

Casmos: Optimizing for LLM Citations Instead of Rankings

https://yyyokel.com/claude-ai-search-monetization-operating-system-2026-playbook/
1•wompapumpum•2w ago

Comments

wompapumpum•2w ago
Been down a rabbit hole on how Perplexity, ChatGPT, and AI Overviews actually decide what to cite. Turns out it's nothing like traditional SEO anymore.

The short version: LLMs don't care about your domain authority or backlink profile. They care about whether they can extract a clean answer from your content. Structured stuff (Q&A format, comparison tables, FAQ markup) gets cited way more than 3000-word walls of text. And different models cite completely different sources for the same query—like 35-40% disjoint.

I put together a prompt system for Claude that walks through the whole thing: researching how LLMs behave in your niche, figuring out what's exploitable, building content that's easy for AI to parse and cite, seeding it across platforms these models actually crawl, then deciding what's working and what to kill.

It's five prompts that I run in sequence. Pretty tacticalless "best practices" and more "here's how these systems actually work right now." based on my findings.

Would love to hear if anyone else is seeing meaningful traffic from AI search yet, or if it's still mostly noise...

storystarling•2w ago
From a backend perspective, this matches what I've seen building RAG pipelines. The issue is usually that standard chunking algorithms often sever semantic context in long-form text, even with overlap. Structured data or explicit Q&A formats survive retrieval much better because the embedding actually captures a complete thought rather than a fragment.