ØxPerri

There’s a difference between using a product and realizing you can build something entirely new on top of it. Two people can look at the same platform and see completely different things. One sees buttons, charts and features to interact with. The other sees data, systems and opportunities to build something beyond the original experience. The difference isn’t necessarily what the product offers. It’s how deeply you understand what sits beneath it. The interface shows you how to use a product. Understanding its infrastructure reveals what else you can create with it. This is a side of @seeryx_com worth exploring. Beyond its prediction markets, Seeryx provides developer tools that let software interact with markets programmatically. You can build on existing infrastructure instead of starting from scratch. First, the data. Seeryx’s public API provides access to current and historical rounds, order books, recent trades, trading volume, fees and event markets. Developers can access this public data without connecting a wallet. That means you could build a custom dashboard, analyse historical activity or monitor liquidity without being restricted to how information appears on Seeryx’s website. Then, real-time updates. Seeryx supports WebSocket connections that stream updates to order books, trades and volume. Your application can react as new information arrives instead of repeatedly requesting updates. This opens the door to live dashboards, market alerts and monitoring tools that respond to changing conditions. But what if you want your software to do more than observe? That’s where trading APIs and SDKs come in. Seeryx provides official SDKs for Python and Rust, alongside a trading API supporting market orders, limit orders, post-only orders, batch placements and cancellations. With the required authentication and signing, developers can build custom trading interfaces or software that manages orders according to predefined rules. These aren’t just technical features. They’re building blocks for new applications. Seeryx even provides a market-making bot guide. Market making involves placing buy and sell orders to provide liquidity and potentially earn the spread between them. Imagine a bot buying at $0.47 and selling at $0.51 for the same outcome. That’s a potential gross spread of $0.04 per share if both orders fill at those prices. But it isn’t guaranteed profit. One order might fill while the market moves against the position. Fees, liquidity and execution also affect the outcome. A bot must monitor the order book, adjust quotes, track fills and manage its inventory. The infrastructure can automate parts of this process, but it cannot eliminate trading risk. There are boundaries, too. Public market-data access doesn’t mean every operation is permissionless. Trading and account operations require appropriate authentication and signing, while trading requires the necessary funds, including USDC. So, what’s the bigger opportunity? You could build analytics tools without placing a trade, create your own interface for exploring markets, or experiment with automated strategies using existing infrastructure. You don’t have to rebuild an entire platform. You can focus on solving one specific problem with the tools already available. That’s what makes Seeryx’s developer infrastructure interesting. It gives builders ways to move beyond using the product and start exploring what they can create with it. Explore the documentation: seeryx.com/developers

What if you could prove what someone needs to know without showing them everything else? Imagine applying for a loan. The lender needs to know whether you have enough money to repay it. But does that mean they need access to your entire bank history, every transaction you’ve made, and everyone you’ve sent money to? Not necessarily. They need specific information to make a decision, not unrestricted access to your financial life. This is the idea behind selective disclosure, and it’s an important part of thinking about privacy in blockchain applications. Now, let’s look at how @sodabubblelabs approaches this problem. On a public blockchain, protecting sensitive information isn’t just about encrypting it. You also need to control who can access that information, how it can be used, and under what conditions it can be revealed. Otherwise, information that’s supposed to remain private could become accessible in places where it was never intended to be used. This is where Soda Labs’ approach to access control becomes interesting. Its privacy infrastructure is designed around the principle that access to protected data should follow the rules established by the application and the users who supplied that data. In its technical documentation, Soda Labs describes mechanisms for controlling how protected information is stored, accessed, and used during computation. Its approach also allows applications to process private data while revealing only the result intended by the application, subject to user consent. Let’s make that easier to understand. Imagine a business uses a blockchain application to manage confidential financial information. The application needs to calculate whether the business meets a particular requirement. The calculation may need access to certain private inputs, but that doesn’t automatically mean every other application or person should be able to read those inputs. A privacy system must do more than protect the information itself. It must also enforce the boundaries around how that information can be accessed and used. That’s the important distinction. Having access to a result shouldn’t automatically mean having access to all the data behind it. @sodabubblelabs addresses this challenge through its confidential-computing infrastructure, including mechanisms designed to restrict how protected data moves between applications and how it can be used during execution. Why does this matter? Because businesses may want to use blockchain applications without exposing their entire financial operations to the public or giving unrelated parties access to sensitive information. And selective disclosure offers a way to think about that balance: reveal what is necessary to an authorized party, while keeping unrelated information protected. Of course, selective disclosure doesn’t mean every system can prove every fact without revealing anything. What can be disclosed, to whom, and under which conditions depends on the application’s design and access-control rules. But the principle is worth understanding. Privacy isn’t always about hiding everything. Sometimes, it’s about having control over what gets revealed, who gets to see it, and why. That’s one of the problems Soda Labs is working to solve as it builds privacy infrastructure for on-chain applications. Because the future of digital finance shouldn’t require you to expose everything just to prove one thing.

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