Andrea Volpini

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Andrea Volpini

Andrea Volpini

@cyberandy

One of the better-known cyberandy. Passionate about Semantic SEO and AI I am co-founder and CEO of WordLift and insideout10.

Rome, Italy Katılım Kasım 2006
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Andrea Volpini
Andrea Volpini@cyberandy·
We don’t need wrappers. We need systems. AI Search isn’t about chunking or embeddings. It’s about building a memory layer that Gemini, ChatGPT, and the rest can trust and interact with. 1️⃣ wordlift-cli npmjs.com/package/wordli… 2️⃣ KG-building SKILL geminicli.com/extensions/?na…
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Thariq
Thariq@trq212·
We just released Claude Code channels, which allows you to control your Claude Code session through select MCPs, starting with Telegram and Discord. Use this to message Claude Code directly from your phone.
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Andrea Volpini
Andrea Volpini@cyberandy·
@gfiorelli1 It might sound elitist, but niche adoption often helps maintain an edge in innovation. Claude gained traction in the enterprise segment partly because it didn’t try to appeal to consumers. If that balance shifts, it risks losing some of that edge.
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Andrea Volpini
Andrea Volpini@cyberandy·
@dawnieando Yes and no. I’ve noticed some degradation in response quality as the focus seems to have shifted toward scaling the customer base. Two months ago, comparing Codex to Claude Code would have been a clear win for Anthropic. Today, the gap feels much narrower.
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Andrea Volpini
Andrea Volpini@cyberandy·
MCP now documents what tool names can and cannot contain. Not mandatory, but helpful. It is a good reminder that retrieval tools and apps need to be designed for clarity, interoperability, and reliable invocation by models. modelcontextprotocol.io/specification/…
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Andrea Volpini retweetledi
Jono Alderson
Jono Alderson@jonoalderson·
Clicks don’t count. They never did. SEO spent 20 years pretending the search interface was the market. Now people are doing it again with prompt tracking. Measure competitiveness, not clicks (or prompts). jonoalderson.com/conjecture/cli…
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Lily Ray 😏
Lily Ray 😏@lilyraynyc·
First ever keynote in Spanish! Mission accomplished and so much fun. 💃 And I loved DJing too! Thanks for having me @seocamp ❤️🙏🏽 Gracias por recibirme a mi primera charla completamente en español, fue un gran placer ❤️🙏🏽
Lily Ray 😏 tweet mediaLily Ray 😏 tweet mediaLily Ray 😏 tweet mediaLily Ray 😏 tweet media
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Andrea Volpini
Andrea Volpini@cyberandy·
Smarter models do not just “know more.” They increasingly spend more inference-time compute: more fan-out searches, more validation, more filtering, more retries. Accuracy improves not because they answer in one shot, but because they investigate more before committing.
Mic King@iPullRank

Great post from the @writesonic team on how ChatGPT 5.4 searches differently. writesonic.com/blog/chatgpt-c… TL;DR - it's looking for more brand sites than 3rd party sites now. It's running a lot of site: searches based on what this analysis says.

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Nishkarsh
Nishkarsh@contextkingceo·
We've raised $6.5M to kill vector databases. Every system today retrieves context the same way: vector search that stores everything as flat embeddings and returns whatever "feels" closest. Similar, sure. Relevant? Almost never. Embeddings can’t tell a Q3 renewal clause from a Q1 termination notice if the language is close enough. A friend of mine asked his AI about a contract last week, and it returned a detailed, perfectly crafted answer pulled from a completely different client’s file. Once you’re dealing with 10M+ documents, these mix-ups happen all the time. VectorDB accuracy goes to shit. We built @hydra_db for exactly this. HydraDB builds an ontology-first context graph over your data, maps relationships between entities, understands the 'why' behind documents, and tracks how information evolves over time. So when you ask about 'Apple,' it knows you mean the company you're serving as a customer. Not the fruit. Even when a vector DB's similarity score says 0.94. More below ⬇️
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Andrea Volpini
Andrea Volpini@cyberandy·
The true power of AI. Reducing cancer screening workloads.
Jeff Dean@JeffDean

Excited to see this joint collaboration between @GoogleResearch, @NHSuk and @imperialcollege showing AI’s potential to detect 25% of the interval cancers previously missed by conventional methods. Additionally, the research found AI can reduce screening workloads, and give results back to clinicians and patients faster. This first figure from the @NatureCancer article shows how the study was set up, and the second figure shows that the AI system dramatically increases sensitivity (detecting true positives) without significantly affecting specificity (false positives). Learn more ⬇️ Blog: blog.google/innovation-and… Nature Cancer paper: nature.com/articles/s4301…

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