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@maydali28 started using tool Kubernetes , 1 week, 6 days ago.

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@maydali28 started using tool Java , 1 week, 6 days ago.

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@maydali28 started using tool Azure Kubernetes Service (AKS) , 1 week, 6 days ago.

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@maydali28 started using tool AWS EKS , 1 week, 6 days ago.

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@sancharini shared a post, 1 week, 6 days ago

Why Understanding Software Testing Basics Is Essential for Every Developer?

Understand why software testing basics is essential for every developer. Learn key testing types, levels, techniques, and best practices to write reliable, maintainable, and high-quality code.

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@eon01 published a course, 1 week, 6 days ago

Founder, FAUN.dev

Practical MCP with FastMCP & LangChain

#LangCha... #Model C... #FastMCP #AI agen...

Engineering the Agentic Experience

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@kala added a new tool FastMCP , 1 week, 6 days ago.

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@kala shared an update, 1 week, 6 days ago

FAUN.dev()

FastMCP 3.0 Released: Community-Driven Enhancements Unveiled

#FastMCP #FastMCP... #Prefect... #AI #MCP

FastMCP 3.0 is now generally available. It keeps the @mcp.tool() API but rebuilds the internals around components + providers + transforms, adds a CLI, and ships production features like component versioning, per-component auth + OAuth additions, OpenTelemetry tracing, background tasks, pagination, tool timeouts, and hot reload. The project moved from jlowin/fastmcp to PrefectHQ/fastmcp on GitHub, and upgrading is supported via dedicated guides for FastMCP 2 and MCP SDK users.

FastMCP 3.0 Released: Community-Driven Enhancements Unveiled

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@laura_garcia shared a post, 1 week, 6 days ago

Software Developer, RELIANOID

🚀 Ready to level up your #AppSec skills?

Join us at London OWASP Training Days 2026 – February 25–28 in London! Hands-on, instructor-led sessions covering: 🔹 API Security 🔹 Secure Development & Testing 🔹 Threat Modeling & Risk Analysis 🔹 AI & Security 🔹 Mobile & IoT Security 🔹 Offensive Security & Pentesting Learn from the global OWASP com..

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@dwisiswant0 started using tool GNU/Linux , 2 weeks ago.

INTELLECT-3 is a frontier-class 100B+ Mixture-of-Experts language model developed by Prime Intellect and trained end-to-end using their large-scale asynchronous RL framework, PRIME-RL. Built on the GLM-4.5-Air base model, INTELLECT-3 combines supervised fine-tuning with long-horizon reinforcement learning across hundreds of verifier-backed environments spanning math, code, science, logic, and agentic tasks.

The model was trained on a high-performance cluster of 512 NVIDIA H200 GPUs across 64 nodes, supported by Prime Intellect’s Sandboxes execution engine, deterministic compute orchestration, and Lustre-backed distributed storage. The result is a model that surpasses many larger systems in reasoning benchmarks while remaining fully open-source.

Prime Intellect released not only the model weights but also the full training recipe: PRIME-RL, Verifiers, the Environments Hub, datasets, and evaluation suites. INTELLECT-3 is positioned as a foundation for organizations seeking to post-train or customize their own frontier-grade models without relying on proprietary AI labs.