Nowadays blockchains treat privacy like it's just an extra. Just an additional feature. Everything is visible and public. This architecture works for systems where public transparency is the end goal. But what happens when you begin to handle big data, medical records or sensitive information? It collapses. Full transparency and accountability is not a feature in these contexts, it's a problem. Ho
LLM Foundry finally stops being a toy and starts acting like a system I wanted to see whether a weak local model could be made genuinely more useful without pretending the base model was magic. So I wrapped a small Hugging Face model in LLM Foundry, gave it memory, semantic retrieval, a reflection loop, and a benchmark harness — then made it explain why semantic retrieval matters, while the term
As Large Language Model (LLM) agents increasingly integrate numerous external systems, they suffer from Tool Space Interference (TSI), a phenomenon causing context bloat, attention dilution, and degraded reasoning accuracy. In this paper, we introduce the Agent-as-a-Tool paradigm—an evolutionary, practical implementation of the recently proposed Self-Optimizing Tool Caching Network (SOTCN) and Fed
If you're building an AI feature in .NET in 2026, the first framework you hear about is Microsoft Semantic Kernel. It's well-funded, actively maintained, and integrates deeply with Azure. For most projects, that's a fine starting point. But "fine for most" is not "right for all." Over the last few months we've talked to teams who started with Semantic Kernel and ended up looking for something else
Every AI app I've shipped recently rewrote the same plumbing. The OAuth dance for Slack. Encrypted storage for an API key. Refresh-token logic that finally fails on the 3rd call after an hour. Wiring up an MCP client to a server behind a bearer token someone pasted into a Notion page.
This is my Day 2 of learning AI fundamentals where I will be covering the following concepts: Vector Embeddings How Tokenisation and Vector Embeddings relate to each other Vector embeddings is the process of turning each token id(generated during tokenisation) into high dimensional vector where semantic similarity results into geometric closeness. Think of it like this: dog is closer to puppy, al
Stop Guessing Whether Debian Package Files Changed: Practical debsums for Integrity Checks A package can be fully installed and still not be in the state you think it is. Maybe a file was edited by hand. Maybe a cleanup script went too far. Maybe you are checking a host after a rough shutdown, disk issue, or suspicious change and you want one simple answer: Did files shipped by Debian packages c
The agent harness performance optimization system. Skills, instincts, memory, security, and research-first development for Claude Code, Codex, Opencode, Cursor and beyond.