The core finding that surprised me: we looked at cross-platform citation data and the overlap between engines is tiny. - Only 11% of domains get cited by both ChatGPT and Perplexity. - Less than 1% for specific queries. - Perplexity leans heavily on Reddit (47% of top citations). - ChatGPT favors direct authoritative sources with strong recency signals. - Google AI Overviews has 76% overlap with Google's top 10.

The practical implication for anyone building a B2B product: the AI engine your team uses for research is probably not the same one your enterprise buyer uses during procurement.

Wharton-GBK 2025 data shows ChatGPT at 67% enterprise adoption and Copilot at 58%, while Perplexity sits at roughly 18%.

The conversion data is also worth noting. Across 42 B2B sites studied, ChatGPT referral traffic converted at 15.9% vs 2.8% for traditional organic Google traffic. AI compresses the research phase, so visitors arrive further down the funnel.

Are you seeing similar patterns? And for those building developer tools or B2B products, which AI engines are you actually seeing referral traffic from?

Comments URL: https://news.ycombinator.com/item?id=47223235

Points: 1

# Comments: 2

I ran into this when building a kids' education app a few years ago. We explored a bunch of options, from asking for the last four digits of their parents' SSN (which felt icky, even though it's just a partial number) to knowledge-based authentication (like security questions, but for parents).

Ultimately, we went with a COPPA-compliant verification service, but it added friction to the signup process.

It's a trade-off between security and user experience, and there's no perfect solution, unfortunately.

The lack of dedicated registers meant a lot of memory access, which slowed things down considerably. This is probably why it never gained the same traction as the 6502-based systems like the Apple II or Atari.

I'm curious to see how this UNIX-like OS addresses those limitations. It's a pretty neat accomplishment if it can provide a usable environment on that hardware.

We are building the infrastructure for the post-SEO era. As B2B buyers shift from traditional search to AI assistants like Perplexity, ChatGPT, and Gemini, the old playbooks for visibility are breaking. GrackerAI provides the analytics and automation layer for Answer Engine Optimization (AEO) and Generative Engine Optimization (GEO).

We help brands track their real-time AI visibility scores and automate the creation of high-intent content that these engines actually cite. We’re looking for a Senior Backend Engineer to help scale our data ingestion pipelines and LLM-based evaluation systems. You’ll be working on the core engine that benchmarks brand mentions against competitors across various model architectures.

We are a small, results-driven team focused on high-intent lead generation for SaaS. If you're interested in the intersection of search behavior and automated content strategy, we’d love to hear from you. I am the founder and will be personally reviewing and responding to all applications.

Contact: careers@gracker.ai

Comments URL: https://news.ycombinator.com/item?id=46724926

Points: 1

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Comments URL: https://news.ycombinator.com/item?id=46495440

Points: 1

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Comments URL: https://news.ycombinator.com/item?id=46437464

Points: 1

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Comments URL: https://news.ycombinator.com/item?id=46437449

Points: 57

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Comments URL: https://news.ycombinator.com/item?id=46188614

Points: 2

# Comments: 1

Two trends stand out:

1. Identity systems are starting to use behavioral and contextual signals instead of just passwords or keys.

2. Our current trust models break when adaptive AI systems act independently.

As AI agents become more autonomous, is it time to design identity systems that verify intent, not just identity?

Comments URL: https://news.ycombinator.com/item?id=45737860

Points: 1

# Comments: 1

Two key observations: trust is built through peer networks and practitioner validation, not polished outreach; and most CISO buying decisions emerge from internal problem framing long before vendors contact them. Interestingly, data shows over 80% of deals start from an internal referral or known tech stack gap.

Question to the readers: ow have your enterprise sales or procurement experiences aligned—or conflicted—with this behavior pattern?

Comments URL: https://news.ycombinator.com/item?id=45659793

Points: 2

# Comments: 1

Three key areas stood out: decentralized identity standards, just-in-time credential issuance, and autonomous trust negotiation between agents.

I’m curious — how are others approaching machine identity lifecycle management when both issuance and trust decisions must happen autonomously in real time?