OpenYield’s Post

“We’re redoing computing all over again — and this time, in English.” It's hard to find so much alpha in a YT video, I just found one - YC talk from Andrej Karpathy is an absolute gem on the direction of where products are moving. Top 3 insights that I picked from the talk : 1. The autonomy slider. - Users must control how much autonomy the system gets (from tiny suggestions to full agentic actions). Good products expose this slider and let users choose risk vs. speed. 2. Agents will consume software differently, build for them - Karpathy predicts a new consumer: agent-as-user. Products must expose machine-friendly interfaces (protocols, structured docs, action endpoints). 3. Application specific GUIs for auditing. - Visual diffs, red/green changes, side by side previews, citations . GUIs speed human verification and make fallible LLM outputs auditable. Here is the link to the video - https://lnkd.in/gYCJ4ZV4

🚀 Backward Compatibility: Where Tech Meets Trust Imagine shipping a new software version, only to have old features break or integrations fail. Nightmare, right? That’s where backward compatibility comes in—a technical superhero in disguise. 🔹 Technics Behind It: API Versioning: Maintain older endpoints so apps depending on them don’t break. Data Format Support: Support old file formats or database schemas alongside new ones. Feature Flags & Deprecation Policies: Gradually phase out outdated features without shocking users. Testing Legacy Systems: Automated regression tests ensure new releases don’t break old functionality. Hardware Drivers & Firmware: Old peripherals should still work seamlessly after updates. 🔹 Why Engineers Care: Reduces customer frustration and support tickets. Ensures smooth migration to new systems. Safeguards years of software investment. 💡 Key Takeaway: Backward compatibility isn’t just a checkbox—it’s a careful dance of innovation and respect for what came before. Technical mastery + foresight = future-proof products. #TechLeadership #SoftwareEngineering #BackwardCompatibility #APIDesign

This open-source agent is sick! Klaus Kode is an open-source, console-based workflow for building data integrations using the Claude Code SDK. Find the link to the repo in the comment below. I've been building software for 30 years, and building connectors to other systems to move data in and out is as painful as it gets. It's challenging to get it right, particularly when building applications that scale and maintain high throughput. That's precisely what this project solves: 1. It will guide you step by step to understand your requirements 2. It will write the integration code 3. It will automatically test the integration 4. It will help you deploy everything This will get you to a working connector 10x faster than you would by asking a chatbot to write everything for you.

Event Sourcing: More Than Just an Audit Trail Most systems store only the current state: balance: 100. But this approach has limits. - How did the balance reach 100? - What if we need to replay transactions? - What if business rules change? That’s where Event Sourcing shines. Instead of storing just the latest state, we store every change as an immutable event: Deposit 50 Withdraw 20 Deposit 70 The state (100) is always derived by replaying history. Why it matters in real projects: 🔎 Traceability → Every change is auditable, no “mystery updates.” 🐞 Debugging → If a bug occurs, you can replay events with new logic to see different outcomes. 📊 Multiple Views → One set of events can power different projections: balances, reports, notifications. 🚀 Future-proof → Business rules change? Replay the past with new logic. Of course, in production you’d need snapshots, versioning, and projections to keep things efficient. But the core idea is simple: ➡️ Stop storing just “what is.” ➡️ Start storing “what happened.” That shift in mindset opens the door to richer, more resilient systems. #EventSourcing #SoftwareArchitecture #NodeJS #EventDriven

A backend that works fine today can still fail tomorrow,and without proper logging and monitoring, you’ll never know why. Good logging tells the story of what your system is doing: which requests succeed, which fail, and where performance degrades. Monitoring adds another layer, alerting you in real time before users even notice something’s wrong. I’ve learned that logs aren’t just for debugging,they’re for prevention. The clearer your logs and the smarter your monitoring, the faster you can resolve issues and the less downtime you face. If this is your first time seeing my post, I’m Isaac, a backend developer sharing thoughts on building reliable systems. #BackendDevelopment #Logging #Monitoring #SoftwareEngineering #SystemDesign

💡 APIs are nothing more than “indirect conversations” between software. Think about it — at the application layer, your program rarely talks to another system directly. Instead: - You call an API endpoint. - That endpoint translates your request into actions inside another system. - You get back a structured response (JSON, XML, etc.). This indirection is what makes APIs powerful: - Systems remain decoupled (they don’t need to know each other’s internals). - They enforce contracts (clear inputs/outputs). - They provide scalability (swap out internals without breaking users). The next time you hit a REST or GraphQL endpoint, remember: 👉 You’re not just sending a request. 👉 You’re engaging in a carefully designed conversation protocol that makes the modern internet work. #SoftwareEngineering #SystemDesign #SoftwareArchitecture #TechExplained #DeveloperThoughts #EngineeringMindset #BuildInPublic #API A BEAUTIFUL CONNECTION IS WAiTING HERE 👇 Follow me on LinkedIn: https://lnkd.in/d973i-rP

Vibe Coding: Letting LLMs Take the Wheel ⚙️ Andrej Karpathy popularized the term vibe coding — a loose, experimental way of building software using LLMs: * You provide high-level goals in natural language. * The model writes the code; you iterate, test, and refine through feedback loops. * The human shifts from coding line-by-line to guiding, verifying, and problem-solving. Karpathy suggests that LLMs should be seen like operating systems: * They manage context, processing, and interface interactions. * Developers now build on top of an LLM’s “mind,” similar to how applications are built on operating systems resources: https://lnkd.in/eRD8kdtc https://lnkd.in/eNxPeMnX bonus: https://lnkd.in/eZeviJXW

Bit-rot quietly kills software systems — on average it takes a system down within six years. I just published a deep-dive on what I learned about bit-rot so far. I list the technical and organizational causes, and practical strategies to extend system life: detection techniques, maintenance patterns, testing approaches, and architecture choices that matter. You can read it here: https://lnkd.in/e3RJ9Gdh If you manage or build software, which practice do you use to fight bit-rot?

For those interested in software architecture, there are two important things to know about Prompt Injectionator: 1) I use as many proper software patterns as possible -- including Adapter, Chain of Responsibility, etc. This is not just so the software is well crafted, but so that future SWEs can understand the architecture by seeing familiar patterns. 2) While the app runs some things locally -- in browser, CLI -- there is a backend that does things on behalf of the user. For example, if you choose to use the "Dual LLM" shield/attack, then that runs remotely. If you want access to the live library of prompt injections, that is remote. I'm working on a diagram that explains this, but I think the use case examples will be the best explainers.

Quick .NET Tip ❓ Which one is faster between FirstOrDefault() and SingleOrDefault()? ✅ Answer: FirstOrDefault() performs faster because it stops iterating as soon as it finds the first match. SingleOrDefault() checks the entire collection to ensure there’s only one matching element, which makes it slower in comparison. 🔑 Takeaway: Use FirstOrDefault() when you just need the first match. Use SingleOrDefault() when you want to ensure there’s only one match in the collection.