Lead Web 3 Engineer | Devrel | Podcaster | @web3wikixyz, @coverantxyz | @Moca_Network / @animocabrands | Advisor | Army Veteran | Man on many missions

Dubai, United Arab Emirates
Joined October 2021
Replying to @github
@github are you alive bud? You need some help ?
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16 hours ago @om_patel5 already reported on X that @AnthropicAI has a major privacy management problem. The goal of this post is to push public awareness. When you use Claude’s Share feature, it generates a public link. What surprised me is that some of those links ended up being indexed by search engines. In other words, “share with anyone who has the link” effectively became “anyone can find it through search.” It’s a good reminder that “unlisted” isn’t always the same as “private.” If a public URL can be crawled or referenced, there’s always a possibility it will become discoverable. go to settings > privacy > your data > shared chats > manage Delete anything you dont want the whole internet to see, especially anything personal or financial
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The main bottleneck for AI development is no longer a shortage of chips, but of ordinary power transformers. Future data centers are quite literally running out of power Transformer manufacturing is a highly custom, heavy-duty process that is incredibly difficult to automate. Order backlogs now stretch out for years, prices have doubled, and about 40% of new data centers in the US are already missing their launch deadlines. This infrastructure bottleneck is expected to last until 2030. The super-technologies of the future are heavily dependent on analog hardware 💡
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Summing up Global Tech Weekend Tbilisi. The “Speculation vs. Real-World Adoption” conversation focused on where crypto is actually heading beyond the buzzwords. We talked about community, tokenized indexes and stock markets, and identity — but one point stood out the most: The biggest challenge is still the learning curve. We keep seeing the same pattern — governments introducing regulations without fully understanding how to monitor crypto, and users struggling to protect their own funds. The gap in knowledge continues to slow real adoption.
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zcash:native crashed over 50% after a critical privacy bug went public 🚨 Market dumped Zcash after researchers revealed a flaw inside the Orchard shielded pool – the privacy layer that has been live since 2022. The scary part: the bug could have allowed counterfeit ZEC to be created in a test environment. It was found with help from Claude Opus 4.8 and patched through an emergency upgrade. But the patch is not the real problem. The real problem is trust. - With Bitcoin, anyone can audit the supply on-chain. - With Zcash, the same privacy that hides balances also makes it much harder to prove whether fake coins were ever minted before the fix. The team says there is no evidence of fake ZEC being minted. But the trust is already gone
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Is the AI Rally a Bubble or a Boom The chart captures the core distinction between what ends badly and what usually does not. In a bubble, price runs far ahead of earnings until the gap closes. In a boom, earnings grow fast enough to carry the price. Lately, there has been growing talk that the stock market is overheated, that the growth driven by AI has run its course, and that tech companies are significantly overvalued. Let’s take a critical look at the situation. Back in 2000 $CSCO peaked near 200x earnings, and Pets. com went public with none at all. The entire case for internet stocks rested on revenue from a technology that was years from generating the cash flows the market had already priced in. When that gap closed, the Nasdaq fell 78% and took 15 years to recover. Today's core companies look different. Nvidia's revenue went from $27B in fiscal 2023 to $130.5B in fiscal 2025, up 114% in a single year, with net income reaching $74B. The stock has run roughly 2,000% since its 2022 lows, but earnings grew fast enough to keep the forward P/E near 30x. The @Nasdaq -100 forward P/E sits near 26x today versus roughly 50-60x at the 2000 peak. Companies are spending hundreds of billions on GPU and data center capacity before enterprise use cases have proven their economics at scale. The earnings are real, but they depend on that spending continuing, and that spending needs to be justified by what the AI actually produces for businesses paying for it.
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Replying to @maisha_anj63027
My github contribution looks like this
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One of my recent interviews where we discussion was floating from my life path, career, achievements, teaching some digital security tweaks and again discussing the future of blockchain #fintech youtu.be/L4MHg6w5qpQ?si=kFec…
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Replying to @0xNairolf
we are not bullish enough on alts
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