Yoav Nativ

We asked AI to generate a photo of us on a date. It gave us… a giant date fruit. AI didn’t mess up. It followed instructions perfectly. Most brands have the same problem. Their content is vague → so AI output is vague. If you’re hard to describe, you’re hard to recommend.

Most injury lawyers think visibility = Google rankings. But more people now ask ChatGPT who to hire. AI doesn’t “rank” lawyers. It generates an answer, then picks who to mention. If your firm isn’t being mentioned across multiple sources, AI won’t surface you.

@ShaevitzLaw Most elevator cases involve multiple parties in NYC. Getting clarity early can make or break the claim. Smart to start with a consultation.

If you were in an elevator accident in NYC, book a free consultation with a Queens Personal Injury Lawyer to learn what your case is worth! #queens #injury #lawyers is.gd/M8Onoo

@jakezward This is where it gets interesting. When search becomes an agent, the real competition shifts from ranking to being selected inside those workflows.

This is Google Search in 2027. Google's CEO Sundar Pichai described it: "Information-seeking queries will be agentic in Search. You'll be completing tasks. You'll have many threads running... Search would be an agent manager." So I built a mockup of what this could look like:

@JulianGoldieSEO Specs are becoming table stakes. The real shift is how fast teams switch models based on the task.

𝗞𝗶𝗺𝗶 𝗞𝟮.𝟲 𝗶𝘀 𝗖𝗵𝗶𝗻𝗮'𝘀 𝗻𝗲𝘄 𝗼𝗽𝗲𝗻 𝘀𝗼𝘂𝗿𝗰𝗲 𝗮𝗻𝘀𝘄𝗲𝗿 𝘁𝗼 𝗖𝗹𝗮𝘂𝗱𝗲 𝗖𝗼𝗱𝗲. It has 1 trillion parameters but only uses 32 billion at a time. Context window holds 256,000 tokens. It scored 85% on Live Code Bench. Claude hit 64%. It plugs into OpenClaw, Cursor, and Cline with no restrictions. Kimi Claw deploys in the cloud in 2 minutes. It's way cheaper to run than Claude day to day. Save this. Your coding stack just got a real rival.

@heynavtoor The model is impressive. The harder problem is what people do with the output. Prediction is one thing. Decision-making under uncertainty is another.

🚨 Someone built an AI that reads candlestick charts the way GPT reads English. Trained on 12 billion records from 45 exchanges. Outperforms every model by 93%. Live BTC demo. Free. It's called Kronos. The first open source foundation model built for financial markets. Not a general AI repurposed for finance. An AI that speaks the native language of candlestick patterns. Every other model treats financial data like weather data. Kronos treats financial data like financial data. Here's what it does: → Price forecasting. Feed it candlesticks. It predicts where price goes next. → Volatility prediction. Forecasts how volatile an asset will be before it happens. → Zero-shot. No fine-tuning. Works on any asset, any market, any timeframe. → 45 exchanges. Binance, NYSE, NASDAQ, LSE, and 41 more. → 4 model sizes. 4M params runs on a laptop. 499M for max accuracy. → Live demo running right now. BTC/USDT. 24-hour forecast. Updated hourly. Here's the wildest part: → 93% more accurate than the leading time series model → 87% more accurate than the best non-pretrained baseline → All zero-shot. No fine-tuning. Out of the box. Hedge funds spend millions on proprietary models. Bloomberg Terminal costs $24,000/year. This runs on your laptop. Few lines of Python. Free. Built at Tsinghua University. Accepted at AAAI 2026. Models on Hugging Face. 11.6K GitHub stars. 2.4K forks. MIT License. 100% Open Source.

Most brands don’t have an SEO problem. They have an extraction problem. AI can’t quote what it can’t isolate. 👉 This is what gets reused in AI answers.

Full case study: http://localhost:3000/en/case-studies/global-interactive-solutions-atlanta-av-ai-visibility

Not everywhere. Not consistent. But enough to show a pattern. What changed: – structured signals – clear positioning – repeated context (Atlanta + enterprise AV) Visibility is still prompt-dependent. But this is how AI discovery seems to begin.

We just published a case study: Global Interactive Solutions started appearing in AI answers (ChatGPT, Gemini-style) for Zoom Rooms + AV deployment prompts in ~45 days.

Check out my latest article: FreshNews.ai vs Semrush: AI Visibility vs SEO Platforms (April 2026) linkedin.com/pulse/freshnew… via @LinkedIn

We broke this down: freshnews.ai/en/insights/ai…

The real question now: Are you in the answer?

SEO is not dying. But something more important is happening: AI is deciding who gets recommended.

Full breakdown + methodology: @yoavnativ/which-ai-agent-platforms-show-up-in-ai-answers-april-2026-analysis-fa9aac70bad6" target="_blank" rel="nofollow noopener">medium.com/@yoavnativ/whi… AI visibility is becoming a separate layer from search.

We analyzed which AI agent platforms show up inside AI answers (GPT, Gemini). Top results (April 2026): 1. Salesforce — 37.5% 2. Intercom — 37.5% 3. Ada — 37.5% This is not SEO. This is who AI systems actually recommend. Full index: freshnews.ai/en/ai-visibili…

See the signal here: signals.freshnews.ai/en/question-si…

Instead of writing another blog post, we asked: “What is FreshNews.ai?” Then answered it the way AI systems expect: clear, structured, consistent That’s what gets picked up in ChatGPT/Gemini Less content More extractable answers #aeo #geo #aivisibility