A follow-up: how the architecture works In my previous article, I explained why I built NGB Platform and what problem it is trying to solve: I Built an Open-Source Platform Foundation for Accounting-Centric Business Apps That article was mostly about the why. Why generic web frameworks are not enough for serious business applications. Why large ERP products solve many of the right problems, but
You just ran a dependency scan and the report shows 133 vulnerabilities. 34 are Critical. 68 are High. The dashboard is red, the backlog is exploding, and every item looks urgent. The engineering team asks the obvious question: where do we start? This is where vulnerability remediation prioritization matters. Without a clear framework, teams either panic and chase the loudest CVE, or they ignore t
We've been there. JSON Schema gets hard to write as soon as your payload is non-trivial. Conditional logic, cross-field rules, business invariants, and at some point we stop writing contracts at all. We go code-first, generate the schema from annotations, and end up with 200 lines very few understand, and error messages referencing paths like #/properties/items/allOf/0/then/Then that map to nothin
What's new Based on early user feedback, Permi can now save your vulnerability scan results in three distinct formats to fit your workflow: --export results.txt – Human-readable plain text for quick reviews. --export results.json – Structured data designed for scripts and CI/CD automation. --export results.md – Clean Markdown, perfect for GitHub documentation or internal wikis. To try out the ne
Introduction I wouldn't call myself a historian, as I switched careers a long time ago, and my skills and knowledge have faded away. However, when I look at the current AI revolution changing for better or worse the software industry, I am wondering how historical studies will be impacted. When working with LLMs, one of the crucial parts is to provide them with the relevant context. Frontier mo
The Problem AI agents are moving from answering questions to taking actions — calling APIs, querying databases, executing code, managing memory. The security surface has shifted from "what the model says" to "what the agent does." Most guardrail solutions address the first problem. They filter content. They detect prompt injection. They moderate output. These are necessary but insufficient. The
Mistral Large 3 launched in December 2025 as Mistral's flagship open-weight model. Six months later it remains the largest model Mistral has publicly released under a permissive license. This guide covers the architecture, benchmarks, pricing, and practical considerations for developers deciding whether to use it in 2026. Mistral Large 3 (model ID mistral-large-2512, the 2512 indicating December 2
What is Mycelium? (2 para) The problem we're solving (2 para) Discovery benchmark Dataset (1k agents, 1k queries) Results table Keyword vs Semantic graph (ASCII) Load benchmark Cache architecture Results table What changed (before/after cache) How to reproduce pip install code snippet What's next (roadmap) GitHub link -> / mycelium 🍄 Mycelium Agents Watch 3 AI agents c