Updates and recent posts about LangChain..

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@laura_garcia shared a post, 3 weeks, 2 days ago

Software Developer, RELIANOID

🚀 𝗦𝗖𝗔𝗟𝗘 𝟮𝟯𝘅 – 𝗦𝗼𝘂𝘁𝗵𝗲𝗿𝗻 𝗖𝗮𝗹𝗶𝗳𝗼𝗿𝗻𝗶𝗮 𝗟𝗶𝗻𝘂𝘅 𝗘𝘅𝗽𝗼

📅 March 5–8, 2026 | 📍 Pasadena, California SCALE 23x – Southern California Linux Expo is back — North America’s largest community-run open source conference! Four days of: 🔹 Open source innovation 🔹 DevOps & cloud-native deep dives 🔹 Cybersecurity insights 🔹 Hands-on technical workshops 🔹 Real commu..

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@laura_garcia shared a post, 3 weeks, 3 days ago

Software Developer, RELIANOID

We’re heading to Big Data & AI World 2026

We’re heading to Big Data & AI World 2026 📍 4–5 March 2026 | London Part of Tech Show London 2026, this event brings together data and AI leaders focused on responsible, scalable AI and measurable business outcomes. At RELIANOID, we enable secure, high-performance infrastructures ready for AI-driven..

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@kala shared a link, 3 weeks, 4 days ago

FAUN.dev()

Realtime Prompting Guide

OpenAI shipsgpt-realtimeand declares GA for theRealtime API. It's a speech-to-speech model that tightens instruction-following, steadiestool calling, and lifts voice fidelity. Latency drops. True realtime agents become possible. The release prescribesprompt skeletons,JSON envelopetool outputs,sessio.. read more

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@kala shared a link, 3 weeks, 4 days ago

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Introducing helm

helm usesTypeScripttypes to registerskillsas typed functions with structured I/O. Permissions follow a clear precedence: exact→wildcard→skill→global. Agents get a keywordsearchtool and a code-execution tool that runs JS inside anSESsandbox. A recursiveproxyforwards calls overIPCto the parent, which .. read more

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@kala shared a link, 3 weeks, 4 days ago

FAUN.dev()

Do you need an MCP to build your native app?

Do you need an MCP to build your native app? Surprisingly, modern agents succeed either way. The real difference is how much time, cost, and context you waste along the way... read more

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@kala shared a link, 3 weeks, 4 days ago

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The Pentagon is making a mistake by threatening Anthropic

Anthropic's Claude Gov, optimized for national security uses, has fewer restrictions than regular versions. The Pentagon is threatening retaliation if Anthropic does not waive these restrictions by Friday, including invoking the Defense Production Act or declaring Anthropic a supply chain risk. Anth.. read more

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@kaptain shared a link, 3 weeks, 4 days ago

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Spotlight on SIG Architecture: API Governance

Kubernetes SIG Architecture’s API Governance crew is tightening the screws on stability, consistency, and cross-cutting sanity across the whole API surface. Not just REST. They’re eyeing the overlooked stuff too - CLI flags, config formats, anything that shapes how users and tools touch the system. .. read more

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@kaptain shared a link, 3 weeks, 4 days ago

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Before You Migrate: Five Surprising Ingress-NGINX Behaviors You Need to Know

The K8s blog exposesIngress-NGINXdefaults that clash withGateway API. These include case-insensitive prefix regexes. Host-wide annotation effects. Path rewrites. Slash redirects. URL normalization. Kubernetes retiresIngress-NGINXinMarch 2026.Gateway API 1.5graduatesListenerSetand theHTTPRoute CORS.. read more

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@kaptain shared a link, 3 weeks, 4 days ago

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I Built a Production-Grade Kubernetes Platform in 48 Hours.

A dev built a production-grade Kubernetes platform in 48 hours, encountering challenges and solutions along the way. The setup included multiple layers such as infrastructure, cluster, platform, delivery, and observability, each requiring troubleshooting and adjustments. The process involved deployi.. read more

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@kaptain shared a link, 3 weeks, 4 days ago

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From Chaos to Clarity: How We Built a Self-Healing CI/CD Pipeline That Talks to JIRA

Transitioning JIRA tickets to trigger deployments was key for this team struggling with manual deploys, leading to significant savings in time and reduction in errors. The architecture involved a JIRA Controller Pipeline, a Project Deployment Pipeline, and a JIRA Manager Pipeline, all aimed at seaml.. read more

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.