For people struggling with limited utility of OpenAI subscription, I recommend mastering the Dot. Connect everything to it. Pi-harness with 1017 from opencode-go, *ChatGPT-Web*, google drive, whatever. It's slow but it can get the job done… eventually, and this boosts limits.

I've been slowly adding to $ONDS again because after years of acquisitions across autonomous defense I think we're finally reaching the point where we get to see whether all those pieces can form a real platform. The company now has counter-drone systems, long-endurance surveillance through ULTRA and World View, Mistral's defense relationships, ground robotics and a growing software layer through $PLTR, Omnisys, DefenseOS and Regna that could connect everything together. The upside could be massive as modern warfare shifts toward coordinated autonomous systems across air and ground so Ondas has essentially bought all the pieces it needed to become a serious player but now they have to prove they built a company.

It's crazy how every company "uses AI" but nobody tells their team how to use it. So I wrote this memo for my team as a non-negotiable instruction: ------- > I couldn't fit everything in one image. > I shared the rest here: ------- Rule 1. Protect the data. Before you paste anything. ☑ Ask: "Would I be fine seeing this in the company-wide channel, with my name on it?" ☑ No? Swap names for roles. "Sarah at Acme" becomes "the client." ☑ Never click thumbs up/down on a work chat. ☑ Never click "Share" on a work chat. Never click the 'thumb" button; it sends that chat to train the model. Rule 2. Open every link. ☑ Every number, every name, every source. ☑ You shouldn't be the person responsible for presenting fake data to the team and to clients, just because you were lazy enough to double-check the source. Rule 3. Use your brain first. Then prompt: ☑ Write your own 3 options before opening any AI. ☑ Maybe after then: "What did I miss? Compare all of them for our situation." ☑ Never end a prompt with "right?" or "maybe?" Rule 4. Claude won't be accountable. You will be. ☑ If you send anything, you wrote it. ☑ Can't explain a sentence yourself? Not worth sharing. ☑ Raw AI idea? Better to label it: "Claude suggested this, worth exploring?" Unedited AI output turns your work into my work. I'm not your proofreader. DOn't make my life difficult. Rule 5. Go to brain gym. ☑ Once a day, write one first draft yourself. ☑ Do one calculation by hand. ☑ Make one decision before asking. It's not that hard. You used to do it before ChatGPT 3 years ago. Don't lose your intelligence to AI for short-term laziness and efficiency. Rule 6. Don't connect everything. ☑ A connector can read your whole inbox, your whole Drive, your whole Slack. Most of them you'll never use. ☑ Connect only what it worth, read-only when possible. ☑ Never plug a work account into a personal AI account. Review what's connected once a month. If you are still unsure? Ask me first. Rule 7. Treat Claude like someone who joined yesterday. ☑ It doesn't know our clients, our jargon, or what happened in Tuesday's meeting. Tell it. ☑ Send the screenshot instead of retyping the numbers. ☑ Tell it to look around first: "Before you start, open every email, doc, and tab that could be relevant." Claude feels dumb halfway through? Open a new chat. Every time. Rule 8. Shorter wins. ☑ You write once. The team reads 10 times. If a 2-line prompt made a 2-page doc, send the 2 lines instead. ☑ Do not use AI for everything. You are smart enough to do the micro tasks faster than AI. Nobody should receive these AI patterns: "Here's the thing," "It's not X, it's Y," "delve," "seamless," a pile of em dashes, a pep-talk ending. Rule 9. Ask once. Ask right. ☑ Give the goal, the context, and what "done" looks like. ☑ Delete "think step by step." It already thinks. ---- All of this, but I would still rather read the recent 5 articles at

Institutional DeFi is moving past the question of whether large capital wants onchain exposure and the appetite is increasingly obvious. The harder problem is everything institutions need around the trade. From custody, governance, reporting, compliance, risk controls to clear separation of responsibilities. That is why the next phase of institutional DeFi may be less about finding another 10% yield and more about building the financial infrastructure that allows serious capital to participate safely. With platforms like @Securitize now managing $4B+ in assets, that stack is starting to take shape. Here’s where the real bottleneck sits. — ● Institutional DeFi no longer has an access problem Early DeFi was built for individuals. A user connected a wallet, chose a protocol, managed custody, selected a strategy and absorbed most of the risk themselves. The flow looked something like: Wallet -> protocol -> strategy -> risk -> custody That works surprisingly well for crypto-native users. It does not map cleanly onto how institutions operate. Large allocators need: • Segregated custody • Policy-based approvals • Continuous risk monitoring • Transaction controls • Accounting and reporting • Compliance infrastructure So the problem is no longer simply can institutional capital access DeFi? It is now can DeFi fit inside an institutional operating model? — ● That requires the stack to break into specialised roles Traditional finance does not expect one entity to handle settlement, custody, asset management, risk and execution. Institutional DeFi is gradually moving in the same direction. The emerging stack looks more like: Settlement -> financial protocols -> asset managers / curators -> custodians -> institutional infrastructure At the settlement layer: • @ethereum, @solana, @base and @arbitrum provide the underlying rails. • Above that, protocols such as @aave, @Morpho, @maplefinance and @Uniswap provide lending, liquidity and market infrastructure. • Managers and curators such as @Re7Capital, @gauntlet_xyz and @SteakhouseFi determine how capital is allocated and risk is managed. • Tokenized-asset platforms such as @Ondo, @Securitize and @RWA_xyz bring traditional assets onchain. • And custodians such as @ZodiaCustody and @Anchorage handle institutional asset security. No single protocol needs to become the entire financial system. The stack becomes more useful as each layer gets more specialised. — ● RWAs are making that transition easier Tokenized assets give institutions something familiar to bring into an unfamiliar environment. @BlackRock’s $BUIDL, @Ondo and @Securitize are good examples. BUIDL crossed $1B in AUM in March 2025. By 2026, Securitize reported more than $4B in assets across its platform. But the important development is not only that traditional assets are being tokenized. It is that those assets are becoming increasingly usable inside DeFi. A tokenized Treasury can become: • Collateral • A vault asset • A liquidity source • A settlement instrument • Part of an onchain portfolio That creates a much more direct bridge: TradFi asset -> tokenized RWA -> DeFi application -> onchain liquidity For institutions, that is easier to understand than deploying directly into entirely crypto-native risk. — ● But more institutional capital also means a more complicated risk stack This is where infrastructure becomes critical. @Re7Capital breaks DeFi risk into four broad categories: 1. Financial risk Collateral volatility, liquidity, credit exposure, defaults and market risk. 2. Smart-contract risk Code vulnerabilities, upgrades and governance failures. 3. Structural risk Composability, leverage, dependency chains and liquidation cascades. 4. Stablecoin risk Reserve quality, redemption mechanisms and regulatory treatment. The important point is that these risks rarely exist independently. A lending position might depend on a protocol , an oracle , a bridge , a stablecoin , an underlying custodian A problem several layers away can still affect the original position. That is very different from simply asking whether one smart contract has been audited. — ● Institutional DeFi therefore needs risk to become a service As the stack gets more complex, institutions cannot realistically monitor every dependency themselves. Someone has to continuously answer questions like: • What collateral backs this position? • How liquid is it under stress? • Which oracle does the protocol depend on? • What happens if a stablecoin depegs? • Who can upgrade the contracts? • Where is the underlying RWA custodied? • What other protocols sit underneath the strategy? That turns risk management from a one-time due-diligence exercise into ongoing infrastructure. The same is true for compliance and reporting. Institutions do not just need access to onchain markets. They need onchain activity translated into systems their legal, risk, finance and operations teams can actually use. — And that may be the bigger shift happening in institutional DeFi. The first phase was about proving that blockchain could host financial markets. The second was about getting institutional-grade assets onchain. The next phase is about building the operating layer around those markets. • Custodians secure the assets. • Curators allocate capital. • Protocols provide the markets. • Risk systems monitor dependencies. • Reporting and compliance connect everything back to institutional workflows. That is how DeFi starts looking less like a collection of protocols and more like financial infrastructure. Institutional capital does not simply need better yields. It needs confidence that every layer between the asset and the strategy can be understood, monitored and controlled. And that is why the next institutional DeFi winners may not be the protocols offering the highest return. They may be the companies making onchain finance operationally boring enough for institutions to use at scale. Read the full report by @Re7Capital: