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@laura_garcia shared a post, 2 weeks, 4 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, 5 days 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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@kala shared an update, 2 weeks, 5 days ago

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OpenAI Hires OpenClaw Creator Peter Steinberger; Project Moves to Independent Foundation

#OpenCla... #autonom... #AI #OpenAI #Peter S...

Peter Steinberger, creator of OpenClaw, is joining OpenAI to work on bringing AI agents to a broader audience, while OpenClaw will move to an independent open-source foundation and continue development outside OpenAI’s direct control.

OpenAI Hires OpenClaw Creator Peter Steinberger; Project Moves to Independent Foundation

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@kala shared an update, 2 weeks, 6 days ago

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OpenClaw Lightweight Alternative Launches: A 10MB AI Assistant That Runs on $10 Hardware

#OpenCla... #AI agen... #PicoCla... #$10 har... #Go

Sipeed has released PicoClaw an OpenClaw micro alternative that uses 99% less memory than . , an open-source AI assistant written in Go that runs in under 10MB of RAM and boots in about one second. Designed for low-cost Linux boards starting around $10, it supports multiple LLM providers, chat platform integrations, and automation workflows. The project is MIT-licensed and available on GitHub.

OpenClaw Alternative Launches: A 10MB AI Assistant That Runs on $10 Hardware

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.