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News FAUN.dev() Team
@kala shared an update, 4 months, 1 week ago
FAUN.dev()

GitHub Copilot Adds GPT-5.2 With Long-Context and UI Generation

GitHub Copilot GPT-5.2

OpenAI unveils GPT-5.2 for GitHub Copilot, enhancing software engineering with improved long-context reasoning and UI generation, integrated with Microsoft Azure and NVIDIA.

GitHub Copilot Adds GPT-5.2 With Long-Context and UI Generation
News FAUN.dev() Team
@kala shared an update, 4 months, 1 week ago
FAUN.dev()

GPT-5.2 Quietly Beats Human Experts at Knowledge Work

Azure GPT-5.2

OpenAI releases GPT-5.2, enhancing professional tasks with improved speed and cost-effectiveness, now available for paid users in ChatGPT and via API.

OpenAI unveils GPT-5.2, the most advanced frontier model for professional work and long-running agents
 Activity
@kala added a new tool GPT-5.2 , 4 months, 1 week ago.
Story
@laura_garcia shared a post, 4 months, 1 week ago
Software Developer, RELIANOID

RELIANOID at CII Delhi International Technology Summit 2025

16–17 December 2025 - New Delhi, India Our team continues a packed December schedule, and we’re excited to add another key event: the CII Delhi International Technology Summit 2025. Focused on “Accelerating the Techade”, this summit brings together industry, government, and research leaders to shape..

CII Delhi International Technology Summit relianoid
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@anjali shared a link, 4 months, 1 week ago
Customer Marketing Manager, Last9

OTel Updates: OpenTelemetry Proposes Changes to Stability, Releases, and Semantic Conventions

OpenTelemetry proposes stability changes: stable-by-default distributions, decoupled instrumentation, and epoch releases for production deployments.

otel_stability_update
Story
@laura_garcia shared a post, 4 months, 1 week ago
Software Developer, RELIANOID

deploy the RELIANOID Load Balancer Community Edition v7 on Azure using Terraform

🚀 New Technical Guide Available! You can now deploy the RELIANOID Load Balancer Community Edition v7 on Azure using Terraform in just a few minutes: ✔️ Install prerequisites (Terraform, Azure CLI, SSH keys) ✔️ Use the official Terraform module from the Registry ✔️ Automatically provision all Azure r..

terraform_relianoid_community_azure_img2
 Activity
@tairascott gave 🐾 to Helm 4 or Nelm? What's the difference , 4 months, 1 week ago.
 Activity
@tairascott gave 🐾 to Hidden Correlations Traditional Monitoring Misses , 4 months, 1 week ago.
 Activity
Link
@anjali shared a link, 4 months, 1 week ago
Customer Marketing Manager, Last9

How to Track Down the Real Cause of Sudden Latency Spikes

Sudden latency spikes rarely have a single cause. This blog shows how to uncover the real source using traces, histograms, and modern debugging signals.

track_latency
LangChain is a modular framework designed to help developers build complex, production-grade applications that leverage large language models. It abstracts the underlying complexity of prompt management, context retrieval, and model orchestration into reusable components. At its core, LangChain introduces primitives like Chains, Agents, and Tools, allowing developers to sequence model calls, make decisions dynamically, and integrate real-world data or APIs into LLM workflows.

LangChain supports retrieval-augmented generation (RAG) pipelines through integrations with vector databases, enabling models to access and reason over large external knowledge bases efficiently. It also provides utilities for handling long-term context via memory management and supports multiple backends like OpenAI, Anthropic, and local models.

Technically, LangChain simplifies building LLM-driven architectures such as chatbots, document Q&A systems, and autonomous agents. Its ecosystem includes components for caching, tracing, evaluation, and deployment, allowing seamless movement from prototype to production. It serves as a foundational layer for developers who need tight control over how language models interact with data and external systems.