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Curated links from external sources — not 360Softy original articles.

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Claude Fable 5 Is Here. Here's What Actually Matters for Developers 👨🏾‍💻

Anthropic dropped two models today. Fable 5 — the public-facing Mythos-class model. Available on Pro, Max, Team, and Enterprise right now. Stronger than anything Anthropic has released publicly. Better at long-context, agentic coding, vision, and knowledge work. The longer and more complex the task, the bigger the gap between Fable and previous models. Mythos 5 — same architecture, fewer restrictions. Going out through Project Glasswing to a small group of security providers and government inst

aiclaudellm
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Common Nmap Parameters

The following table lists frequently used Nmap parameters along with their descriptions in an academic context. Parameter Description -sT TCP connect() scan. This method records a large number of connection requests and error messages in the target host’s logs. -sS Half-open scan. Few systems log this activity; however, root privileges are required. -sF, -sN Stealth FIN packet scan, Xmas Tree scan, and Null scan modes. -sP Ping scan. Nmap employs a ping scan by default when scanni

nmapcybersecurityparameters
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ExternalSoftware Engineering
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I wrote a read-only scanner for MCP / agent-gateway production-readiness

I build and maintain an MCP server that works in Claude Code, Cursor, and Gemini CLI. Doing that for a while taught me something uncomfortable: the distance between a registered MCP server and full access to everything it exposes is roughly zero. The convenience is the exposure. So when teams move an agent from "works in the demo" to "touches real systems," the same gaps show up every time. Tool access gets granted per-server instead of per-operation. Fail-open becomes the default nobody chose o

mcpaidevops
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docfx-remote-include: inline remote markdown into DocFX, and govern the assembled page

docfx-remote-include is a Markdig extension and a dotnet CLI tool for DocFX. It does two things: it inlines markdown fetched from an HTTP service at build time, and it can send each fully-assembled page to a transform service for centralized governance. It is not a fork of DocFX. It plugs into DocFX's public BuildOptions.ConfigureMarkdig seam, so it tracks upstream DocFX releases as a regular .NET 8, 9, and 10. If you read my earlier post on this project, it had a per-include AI rewrite feature

aidocfxdotnet
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Craig Walls’ Spring AI in Action is out: 5-book giveaway + Spring AI discussion

Spring AI is the Spring project's response to the gap in solutions for integrating enterprise Java with generative artificial intelligence models like GPT, Claude, Gemini, and others. As I decide to invest time in learning and contributing to the project, I missed something that helped me grow in the past as a Java developer: an online community where people could ask questions, participate in discussions, and promote their content. To fill that gap, I created a dedicated subreddit for the Sprin

springaispringbootspring
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🚀 Looking for a Co-Founder / Technical Partner

🚀 Looking for a Co-Founder / Technical Partner Hello builders, For the past months, I have been developing ONYX, a next-generation programming language and runtime ecosystem designed to combine developer productivity with high performance. ONYX is not just another programming language. The vision is to create a sovereign, production-grade ecosystem with: • A modern virtual machine (VM) The project is currently around 70% complete, and the core architecture is already taking shape. I am now look

aiproductivitypython
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Biome v1, Go 1.26, and the Quiet Modernization of Developer Tooling

This week's releases aren't chasing AI headlines — they're fixing the friction that slows down every serious codebase. Biome landed formatter options that kill entire categories of config debates, Go 1.26 automated the idiom modernization work nobody wants to do manually, and Astral shipped a type checker that makes Pyright feel like it's running on a dial-up connection. Here's what actually matters. Biome 1.0 adds JSX quote style control, arrow function parentheses configuration, and a dedicate

aidevtoolsprogramming
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I built an autonomous SRE that lets an LLM diagnose incidents — but never touch a shell unsupervised

I built an autonomous SRE system where a local LLM diagnoses production incidents, proposes a fix, and a deterministic engine decides whether that fix is ever allowed to run. The whole thing works inside your own network — zero data egress. It's called Sentinel. It's a prototype and a learning project: I started from scratch on a Mac and used it to go deep on distributed systems, gRPC, local LLM inference, and safe automation. This post walks through why it's built the way it is — the design dec

godevopsdistributedsystems
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