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@sancharini shared a post, 1 week, 4 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.

Software Testing Basics for Developers
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@eon01 published a course, 1 week, 4 days ago
Founder, FAUN.dev

Practical MCP with FastMCP & LangChain

FastMCP ChatGPT GPT LangChain Python

Engineering the Agentic Experience

Practical MCP with FastMCP & LangChain
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@kala added a new tool FastMCP , 1 week, 4 days ago.
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@kala shared an update, 1 week, 4 days ago
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FastMCP 3.0 Released: Community-Driven Enhancements Unveiled

FastMCP

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, 4 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..

London OWASP Training Days 2026
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@dwisiswant0 started using tool GNU/Linux , 1 week, 4 days ago.
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@laura_garcia shared a post, 1 week, 5 days ago
Software Developer, RELIANOID

Finance: Resilience. Trust. Continuity

Downtime isn’t just costly—it’s a trust killer. 💸 In financial services, outages can cost millions, invite regulatory penalties, and damage customer confidence. Our latest blog dives into the true cost of downtime and why resilience, security, and compliance must be non-negotiable. #FinancialServic..

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@dwisiswant0 shared a post, 1 week, 6 days ago

The most practical, fast, tiny command sandboxing for AI agents

Need to run one sketchy command without a full container? Here is the most practical, lightweight way to lock down one risky command in your AI pipeline. No daemon, no root, no image build.

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@laura_garcia shared a post, 1 week, 6 days ago
Software Developer, RELIANOID

🚀 Deploy RELIANOID Community Edition v7 on Microsoft Azure using Terraform.

⚡ Infrastructure ready in minutes ⚡ Official Terraform module ⚡ Fully automated Azure deployment Simple. Fast. Reproducible. #Terraform#Azure#DevOps#IaC#LoadBalancer#CloudInfrastructure#RELIANOID https://www.relianoid.com/resources/knowledge-base/community-edition-v7-administration-guide/deploy-reli..

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@laura_garcia shared a post, 2 weeks ago
Software Developer, RELIANOID

🚀 See you at DeveloperWeek — February 18–20, 2026!

🚀 See you at DeveloperWeek — February 18–20, 2026! The world’s largest independent software development & AI engineering conference lands in San Jose, bringing together developers, architects, and tech leaders shaping the future of software. From AI & cloud-native to DevSecOps and developer experien..

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Gemini 3 is Google’s third-generation large language model family, designed to power advanced reasoning, multimodal understanding, and long-running agent workflows across consumer and enterprise products. It represents a major step forward in factual reliability, long-context comprehension, and tool-driven autonomy.

At its core, Gemini 3 emphasizes low hallucination rates, deep synthesis across large information spaces, and multi-step reasoning. Models in the Gemini 3 family are trained with scaled reinforcement learning for search and planning, enabling them to autonomously formulate queries, evaluate results, identify gaps, and iterate toward higher-quality outputs.

Gemini 3 powers advanced agents such as Gemini Deep Research, where it excels at producing well-structured, citation-rich reports by combining web data, uploaded documents, and proprietary sources. The model supports very large context windows, multimodal inputs (text, images, documents), and structured outputs like JSON, making it suitable for research, finance, science, and enterprise knowledge work.

Gemini 3 is available through Google’s AI platforms and APIs, including the Interactions API, and is being integrated across products such as Google Search, NotebookLM, Google Finance, and the Gemini app. It is positioned as Google’s most factual and research-capable model generation to date.