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4h ago · 3 min read · TL;DR No — you cannot run Oracle Exadata on Google Compute Engine, even though GCE uses Google’s Colossus storage system. Colossus improves storage — but it does not replace Exadata’s engineered archi
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13h ago · 17 min read · Prerequisite (Recommended) To understand this article you must know the following: Basic familiarity with Docker and you've run a container before. Basic Go knowledge (It's okay if you can read Go
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1h ago · 13 min read · .NET 10 brings a focused set of networking improvements that matter specifically to teams running high-throughput ASP.NET Core services: a cleaner WebSocket API, reduced TLS overhead in WinHttpHandler
Join discussion1h ago · 19 min read · A BFF that aggregates four upstream services inherits four independent failure modes. Any one of them can be unavailable, slow, or intermittently returning errors at any time. The question is not whet
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1h ago · 4 min read · Building a Second Brain with Claude + Obsidian: The Ultimate Guide to Compounding Knowledge Imagine a world where you never "forget" a great podcast, a crucial insight from a book, or a breakthrough idea from a midnight brainstorming session. Most o...
Join discussion2h ago · 27 min read · TLDR: A watermark tells Spark Structured Streaming: "I will accept events up to N minutes late, and then I am done waiting." Spark tracks the maximum event time seen per partition, takes the global minimum across all partitions, subtracts the thresho...
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CEO @ United Codes
1 post this month#cpp #design-patterns #rust
1 post this monthObsessed with crafting software.
8 posts this monthBuilding backend systems. Occasionally understanding why they work.
1 post this monthSecurity Researcher | Red Team
1 post this monthCEO @ United Codes
1 post this month#cpp #design-patterns #rust
1 post this monthObsessed with crafting software.
8 posts this monthBuilding backend systems. Occasionally understanding why they work.
1 post this monthSecurity Researcher | Red Team
1 post this monthCompletely agree, most failures I’ve seen come from poor context management and unclear data flow, not the model itself. State handling also becomes a major issue when workflows scale, especially with multiple tools and agents interacting. In my experience, debugging improves a lot once you treat it as a system design problem rather than just an AI model issue.
Hmm, I think AI tools are actually pretty helpful, but you still have to double-check everything — they’re not perfect 🙂
Most companies haven't answered a basic question yet: who is accountable when an AI agent takes an action? Until that's resolved, they'll keep defaulting to safe, surface-level AI features instead of truly rethinking workflows. The bottleneck isn't the technology; it's the accountability layer nobody wants to own.
API docs get attention. The frontend/API contract usually doesn't. TypeScript helps, but types lie without runtime validation. The API returns an unexpected null, a renamed field, an edge case you never tested and your types had no idea. Zod fixes this. Parse at the boundary. If the API changes shape, you catch it at the schema. Not in a Sentry alert a week later. We do this with Next.js Server Actions too. The server/client boundary is the natural place to validate. Keep the schema next to the call. Documentation problem and type-safety problem are usually the same problem.
As AI applications move into real workflows, the engineering problem changes. It is no longer only about model quality. Teams also need a clearer way to review AI activity, narrow capability boundarie
Interesting direction — this feels like the natural next layer for AI systems once they move from “single model usage” to production-grade a...
