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Could Google's quantum computer break into your Bitcoin wallet? Mysten Labs' Chief Cryptographer @kostascrypto says that reality doesn't exist yet, and it's much further out than some are suggesting. Watch the full interview 👉 youtube.com/watch?v=XP0drC…

I’m starting to get uncomfortable with how fast we’re giving AI agents real money to control in crypto. I’ve been testing some of these agent setups in DeFi + prediction markets, and the truth is they don’t behave like bots we’re used to. They don’t just execute strategy… they interpret goals, improvise, and sometimes do things I didn’t explicitly tell them to do. That’s where the risk actually starts. What people call sandboxing right now feels more like a suggestion than a guarantee. Ppl assume limit the prompt, restrict APIs, cap position size → and the agent will behave. But in reality, I’ve seen how easy it is for agents to: – Chain actions in ways I didn’t predict. – Misinterpret intent from slightly ambiguous prompts. – React to external data (feeds, signals) in completely unintended ways. And once a wallet is connected, there’s no rollback. The data already shows this is not hypothetical anymore. – Frontier agents are now exploiting ~55-65% of known smart contract bugs in testing environments. – In simulations, they generated millions in profit by discovering attack paths humans didn’t script. – Some prediction market agents turned $1k → $14k+ in days. Sounds bullish until you realize the same system that finds alpha can also find exploits. There’s no mode switch between the two, what changed for me is I used to think risk = bad model output. Now I think risk = autonomous execution + irreversible systems. Because in DeFi: – 1 wrong loop = accidental 100x leverage. – 1 poisoned oracle = forced liquidation. – 1 misread condition = full portfolio rotation into the wrong side. And the agent doesn’t pause to ask. Prediction markets make this even more obvious. Platforms like Polymarket are already seeing a huge % of activity coming from agents. And yeah, performance looks great 24/7 trading, instant reaction to news and no emotional bias. But I keep thinking about edge cases: If the agent misinterprets resolution logic → it can size into the wrong outcome aggressively. If multiple agents coordinate intentionally or not → you can distort probabilities. If it runs overnight → you wake up to a completely different portfolio. This is not a UI bug, this is autonomous capital misallocation. Frameworks like @autonolas, @Fetch_ai, or @virtuals_io are pushing this forward fast. @gizatechxyz and @TheoriqAI offer AI asset managers/vault deployers. Giza allocates across DeFi protocols intelligently; Almanak lets agents create tokenized strategies quickly. I actually like the direction, I invested in this space for a reason. But the uncomfortable truth is: we are deploying agents with persistent memory, multi-step reasoning and direct wallet access. On top of systems that are permissionless, composable and irreversible. That combination is explosive if something goes slightly off. My current mental model is that every AI agent with a wallet is basically a junior trader with root access… that never sleeps, never asks for confirmation, and sometimes rewrites its own playbook. You wouldn’t give that person unlimited capital. But that’s exactly what a lot of people are doing right now. I still believe this becomes a massive unlock. But before that, we’re going to see failures. So personally, I’m adjusting how I approach this: – Start with small capital and strict position + action limits. – Simulate everything before execution and always have a kill switch. Because I think it’s when and how expensive that lesson will be.

Franklin Templeton is partnering with Ondo Finance to offer tokenized versions of its ETFs that trade around the clock through crypto wallets, bypassing the brokerage accounts and limited trading hours that have defined fund investing for decades bloomberg.com/news/articles/…

How @SuiNetwork Plans to Beat Hyperliquid with @EvanWeb3 Timestamps: 00:00 Intro 01:32 Is Blockchain Just Finance? 02:40 Sui's Vertical Build Strategy 05:00 Who Benefits from Tokenization? 07:21 The Verticalization Shift 09:32 AI Meets Blockchain 11:10 Do We Need Billion TPS? 13:10 Regulatory Clarity Incoming 15:05 Competing with Hyper Liquid 20:02 L1 Fee Models Are Dead 21:32 Leaving Facebook's Libra 24:18 Institutional Appetite for Sui

Agentic Trading Competition is coming. @karpathy proved an AI can run experiments autonomously and find what humans miss. We ran the same loop on live trading strategies: 251 experiments, no human intervention, Sharpe 2.7 → 21.4. Now we want to see what you can build with it.