JIQQYJONES

Digital security in Web3 gets plenty of attention.

Hardware wallets. Air-gapped devices. Multisig. You know the stack.

But what about physical, bodily security? Some of the biggest threats come through front doors rather than code.

Home invasions. Kidnappings. Torture. And worse.

Founders targeted because of what they built. Because of the value they’ve created.

And yet, physical threat modeling is almost absent from the Web3 conversation.

For the founders & visionaries among us—how do you protect yourself while still showing up? Still building your personal brand? Still pushing your project forward?

Some safety principles I’m thinking about:

→ Build in public but don’t live in public

→ Keep asset custody and personal identity separate

→ Speak about your values, not your balance sheet

→ Audit your personal digital exposure like you'd audit a smart contract

→ Train your team to think about operational security beyond just Discord moderation

The vibe isn’t fear—it’s clarity. Resilience starts with seeing the whole picture ahead of anyone else regardless of their intentions.

Scroll #polymarket instead of Twitter.

Just kidding. Kind of.

Betting isn’t required—just read the questions.

Why? Because Polymarket participation is scaled and its betting incentives are clean—so the questions themselves become a powerful source of signal.

~ Will there be a banking crisis by July?

~ Will the S&P 500 drop 20% before October?

~ Will there be a major stablecoin depeg this year?

~ Will Ethereum move to enshrined rollups by 2026?

All signal.

Wisdom of the crowd may emerge only at scale. Small networks echo while large networks can clarify with statistical significance.

That’s why Polymarket works. Why Google Trends reveals. And why viral memes matter.

The crowd isn’t always right—but it’s rarely irrelevant.

Market Trends 🔥
*Not investment advice*

Wall Street selling while retail buying continues in US stocks

Major market downturn: Dow dropped ~900 points due to Israel-Iran conflict

Strongest bullish market sentiment since 2020

Gold near all-time high at $3450/oz, up 30% YTD

Oil prices at $77/barrel raising inflation concerns

US News 🇺🇸

University of Michigan's Consumer Sentiment Index shows improvement

CFTC maintaining strict crypto oversight

Walmart and Amazon considering stablecoin implementation

Stablecoin Bill (Genius Act) gaining bipartisan support

Crypto Updates ⚡

Gemini and Coinbase expected to receive EU licenses under MiCA

Cardano proposing ADA to Bitcoin/stablecoin conversion

Polkadot community divided over DOT to BTC conversion

Bitcoin miners having their best quarter per JPMorgan

Net inflows reported for both Ethereum and Bitcoin spot ETFs

a16z funded Yupp, an AI model evaluation platform

Ethereum Foundation donated to Roman Storm's legal defense

Lookonchain 📊

Major whale (likely ConsenSys) bought 166,199 ETH at $2,618 average

SharpLink purchased 176,271 ETH ($462.95M) at $2,626 average

Significant ETH whale bought 48,825 ETH for $127M

Bitcoin ETFs: +940 BTC net inflow, Ethereum ETFs: +52,626 ETH net inflow

Trending coins 💰

Binance listed ROAM with user incentives

BSC Foundation invested in $CAKE, $LISTA, $MOOLAH ($225K total)

$VIXBT saw 62% market cap increase after BSC Foundation's $25K purchase

Wild day in the markets! While Wall Street's playing it safe, retail investors are going full YOLO. We've got some massive whale action in ETH, gold hitting the moon, and even Walmart and Amazon eyeing the crypto game. Meanwhile, Iran-Israel tensions are keeping everyone on their toes, and the crypto world's busy with some serious institutional moves. Traditional finance giants are finally warming up to crypto, making this one spicy market cocktail! 🍸🍹

Imagine this: An AI agent scans your site, finds a hidden input field, injects malicious code, and exfiltrates data—no human coder involved.

That just happened.

Researchers at the University of Illinois gave a GPT-4 agent an objective: hack a live website. Using only natural language, the agent found a vulnerability, bypassed basic protections, and accessed restricted data.

Fully autonomously. With no special tuning. And no coding help.

We’re entering the era of agentic hacking. Not “attacks on AI agents” (although those will persist) but attacks by AI agents themselves.

The best tech always attracts the best builders—and the worst actors, who are automating adversarial reasoning to build agents that are self-directed, context aware, and frightfully adaptive.

The pitch decks say “AI assistants.” While AI threat models predict the next actions of agentic attackers.

Web3 won’t stop agent-powered attacks. But it might help to contain them, through auditable compute, on-chain rate limits, access controls controlled by smart contracts, and transparent agent registries.

Agentic attacks are not sci-fi. They’re operational.
@Quantstamp @carbonb1ack

You’re a Web2 technical founder. You built the app. It’s working beautifully.

But you need to verify a credential—without storing it, seeing it, or trusting a third party.

Web3 offers some powerful primitives—yet integrating them probably feels like a full-stack commitment.

What if it wasn’t? What if you could drop in a secure proof to access your required guarantees—without touching the stack?

Zero-knowledge proofs with the right UX make that possible. On-chain trust becomes a black box primitive.

Forget navigating wallet connects.

Skip learning Solidity.

Just get confirmations that tell you “yes, this proof is valid.”

Some of the most innovative teams are using ZK to bring Web3 to Web2 devs. So you can keep building in Web2 but inherit Web3’s guarantees.

Zero-knowledge isn’t just privacy tech—it’s a versatile interface. And how Web3 may onboard the next million talented builders.

Web2 leaves users in the dark.

Walled gardens in tech create massive data shadows—opaque expanses of user-generated value that are monetized only by the giants.

Consider Apple's recent actions in the Fortnite case, in which a court ordered Apple to allow developers to direct users to alternative payment methods. @Apple introduced a 27% fee on those external transactions and implemented discouraging “scare screens”—moves the court deemed willful violations of the injunction.

ICYMI all of your clicks, your purchases, your preferences—all of it is data that you’re being forced to give away.

And what’s worse? You don’t really know what’s being recorded or how it’s being used.

You can’t access your Web2 data. You can’t verify it. And you don’t benefit from it.

That’s the shadow. It follows you but is never quite yours.

Web3 turns on the light.

Web3 protocols create data mirrors—transparent, verifiable, composable reflections of your user behavior and intent.

Interact on-chain and you’re creating a data trail that you can access, remix, or reclaim at any time. No gatekeepers, no NDAs, no adtech middlemen.

💡 Your data trail becomes your reputation.

💡 Your reputation becomes a credential.

💡 That credential becomes capital, usable in creative ways across Web3 protocols.

Web3 turns data exhaust into pure signal. Not just for protocols, but for protocol users, too.

Shadow to mirror is a paradigm shift—from purely extractive to mutually empowering. Mirrored data unlocks whole new economies built around trust, coordination, and digital identity.

And that’s why the decentralization of your data actually matters.

@AnimcocaVentures is backing the protocols that build the mirrors.

Every founder wants to define a magic number.

How many users? How much TVL? How many integrations or devs building on platform? How much more until impact is truly achieved?

The uncomfortable truth is that there’s no universally magic number. Yours is specific and defined by your market, your model, your thesis.

A DePIN protocol chasing location density has a different magic number than a social app building cult energy.

A DeFi primitive with long-tail LPs doesn’t measure success like an L2 chasing enterprise devs.

It’s the context that yields the meaning. KPIs lacking context are just vibes with a dashboard.

The better questions to ask—What are you trying to prove? And to whom? Get clear on that and the path sharpens.

If you're sitting on rich, well-structured data—about usage, behavior, on-chain intent—then you can track directional momentum in context-specific ways.

Sure, your backers matter, too. Because the right capital doesn’t just fund progress—it interprets it correctly.

What’s your magic number—and what makes it magic for you?

What happens when protocols have memory?

Web3 protocols are amnesiacs.

They execute, settle, and forget.

No history. No context. No learning.

But what happens when protocols have memory?

Enter AI agents. With the ability to read and reason across decentralized data sets—remembering what worked, what failed, and what matters—intelligent agents transform Web3 protocols into fully adaptive systems.

Programmable intelligence, not just programmable money.

Why is this big?

😲 Protocols that remember can optimize complex strategies (such as for crypto trading) without human intervention.

- Protocol memory can personalize recommendations based on your past preferences.

- That same memory can adjust liquidity incentives in real time based on historical performance—across chains, markets, and users.

- Memory unlocks agency.

Tech behemoths outside of Web3 are already releasing memory-enabled systems. ChatGPT now remembers your preferences and history across sessions. And NVIDIA’s Blackwell GPUs are powering persistent, private LLMs—AI agents that think and evolve in ways customized to you.

@Superior_Agents in Web3 is doing it big already, building blockchain-native, self-learning agents. Superior Agents evolve with every transaction, every decision, every market cycle.

But @HumanLevelJen and the Superior Agents / KIP team aren’t just building AI on blockchain. They’re creating memory. And in a space obsessed with composability, memory is the ultimate unlock.

Protocols that learn will massively outperform those that can’t help but forget.

What happens when protocols have memory?

Web3 protocols are amnesiacs.

They execute, settle, and forget.

No history. No context. No learning.

But what happens when protocols have memory?

Enter AI agents. With the ability to read and reason across decentralized data sets—remembering what worked, what failed, and what matters—intelligent agents transform Web3 protocols into fully adaptive systems.

Programmable intelligence, not just programmable money.

Why is this big?

😲 Protocols that remember can optimize complex strategies (such as for crypto trading) without human intervention.

- Protocol memory can personalize recommendations based on your past preferences.

- That same memory can adjust liquidity incentives in real time based on historical performance—across chains, markets, and users.

- Memory unlocks agency.

Tech behemoths outside of Web3 are already releasing memory-enabled systems. ChatGPT now remembers your preferences and history across sessions. And NVIDIA’s Blackwell GPUs are powering persistent, private LLMs—AI agents that think and evolve in ways customized to you.

@SuperiorAgents in Web3 is doing it big already, building blockchain-native, self-learning agents. Superior Agents evolve with every transaction, every decision, every market cycle.

But @HumanLevelJen and the Superior Agents / KIP team aren’t just building AI on blockchain. They’re creating memory. And in a space obsessed with composability, memory is the ultimate unlock.

Protocols that learn will massively outperform those that can’t help but forget.

#HaedalProtocol Analysis 🔥🔥🔥

Don’t just watch liquid staking derivatives (LSDs) on ETH and SOL.

Because what if the real signal is in Sui?

Haedal Protocol just conducted its TGE—and has already captured 37.4% of Sui’s LSD market with $130 million of TVL, 3.19% APY (vs. Sui’s 2.5% average), and approximately 794,000 holders.

Sui’s LSD penetration? Just under 2% of staked tokens.

Ethereum is topping 20%.

Solana’s LSD is 10%.

Haedal Protocol on Sui is closing the gap.

Under the hood, Haedal isn’t just staking—it’s stacked infrastructure:

✅ The Haedal Market Maker (HMM) is a real-time DEX liquidity optimizer that uses oracle pricing

✅ HaeVault is the ultra-narrow LP rebalancer for SUI-USDC, grossing up to 1117% APY and netting 938% after fees

✅ HaeDAO is for governance with veToken incentives, using treasury-compounding logic

Haedal’s network logic is baked into the core protocol. The tech monitors all verification nodes on Sui and dynamically allocates capital—staking to those with the highest APYs and withdrawing from the lowest—ensuring optimal yield performance at all times.

On-chain momentum gives the same energy. Daily volume surged from $6 millio to $32 million in just two months, fee revenue from HMM grew 4x, and haSUI’s annualized return rate climbed from 2.58% to 3.21%.

Haedal isn’t another LSD protocol—it’s the optimizer stack behind Sui’s DeFi layer.

One to watch, if you’re paying attention.

Study the charts 👉

Adtech is the most neglected layer in Web3.

Every project needs users, but far too few are building the infrastructure to actually reach them.

The current state of affairs is that Web3 has no systemized way to drive growth, no rails for ad or marketing campaigns, and no feedback loops. Just vibes, influencers, and hopes to go viral.

Contrast that to Web2, which built a $1 trillion ad machine. Love or hate ad spend, it works—and enables growth teams to measure, target, and iterate.

Web3 wallets are programmable. On-chain behavior is trackable. Users join by opting in. The ingredients for a radically new kind of adtech system are already here, and yet the Web3 ecosystem is still using YouTube influencer tactics from 2014.

Picture this instead—
👉 Web3-native open systems enable user acquisition
👉 User targeting is based on real wallet actions
👉 Marketing campaigns trigger directly from programmable contracts
👉 Campaign measurement is trustless and shared
👉 Incentives align rather than exploit
What you don’t get from Web3 adtech is middlemen, surveillance, or algorithm opacity. Just clean, composable growth loops for on-chain ecosystems.
The team that builds Web3 adtech doesn’t just unlock a new market for ad spend.

Web3 adtech builders create the feedback loop that Web3 lacks.
Web3 adtech builders create the missing growth engine.
Check out: #dat.network

Every major LLM is drinking from the same data trough—Reddit, Wikipedia, Stack Exchange, but the platform owners have begun to catch onto the value of their data, and are making scraping harder and harder.

The result is a shrinking public internet, and a greater proportion of AI slop in what remains. We will not be able to train AGI on the 2025 web. Not only is it too small, the vast amounts of synthetic data skew the distribution of the training set. This will lead to more beige, average answers, and finally to model collapse.

This is the future? A beige slurry of average? Nah.

The real unlock is decentralized data. Not just for privacy, not just for provenance—but also for signal.

To source high-quality, high-entrop data for future training it will be necessary to fine-tune AI models on sovereign, user-owned data vaults.

Models get trained on the weird, the wild, the real. Subcultures. Local languages. Outlier behavior.

These edge cases don’t break the model—they make the model.

What a model knows matters more than how it's built, especially as LLMs commoditize. Data is the new differentiator, and the most valuable data won’t come from the public web—it’ll come from the edges.

Where data is owned, permissioned, and alive.

And here's the kicker—centralized AI models are allergic to messiness. They’re optimized for compliance, not curiosity.

But messiness is where meaning lives. A model trained on DAO governance forums, fringe science subreddits, or voice notes from rural WhatsApp groups understands the world differently. It doesn’t just autocomplete—it contextualizes to produce deeper perspective.

If you're building AI without thinking about where the data comes from, or who controls it, you’re not building intelligence. You’re merely scaling consensus.