#aiagents

[pravaai]

AI agents are transforming work—but they're also creating a new attack surface.

As AI becomes more autonomous, security must evolve too.

At PRAVA AI, we believe AI security starts with: ✅ Identity verification ✅ Zero Trust access ✅ Real-time threat detection ✅ Data protection ✅ Continuous monitoring

Don't just build AI. Secure it from day one.

Predict. Prevent. Protect.

How is your organization securing AI agents?

[aistorynews]

AWS Transform brings agentic AI to cut enterprise tech debt

AWS Transform debuts as an agentic AI workbench for migration and continuous modernization, automating tech debt fixes across portfolios

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#AIAgents #OpenAI #VideoGeneration

[jorgenguldmann]

The layer has a name: Ontology.

Traditional BI answers “𝗪𝗵𝗮𝘁 𝗵𝗮𝗽𝗽𝗲𝗻𝗲𝗱?” Semantic models answer “𝗛𝗼𝘄 𝘀𝗵𝗼𝘂𝗹𝗱 𝘁𝗵𝗲 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗺𝗲𝗮𝘀𝘂𝗿𝗲 𝗶𝘁?” Taxonomies answer “𝗪𝗵𝗮𝘁 𝗸𝗶𝗻𝗱 𝗼𝗳 𝘁𝗵𝗶𝗻𝗴 𝗶𝘀 𝘁𝗵𝗶𝘀?” Knowledge graphs answer “𝗪𝗵𝗮𝘁 𝗶𝘀 𝗮𝗰𝘁𝘂𝗮𝗹𝗹𝘆 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱, 𝗿𝗶𝗴𝗵𝘁 𝗻𝗼𝘄?” 𝗢𝗻𝘁𝗼𝗹𝗼𝗴𝗶𝗲𝘀 𝗮𝗻𝘀𝘄𝗲𝗿 “𝗛𝗼𝘄 𝗮𝗿𝗲 𝗮𝗹𝗹 𝗯𝘂𝘀𝗶𝗻𝗲𝘀𝘀 𝗰𝗼𝗻𝗰𝗲𝗽𝘁𝘀 𝗰𝗼𝗻𝗻𝗲𝗰𝘁𝗲𝗱?” Your AI agent doesn’t know what a customer is. It knows you have a table called CUST_MASTER_V2. Closing that gap takes…

The layer has a name: Ontology.

[aistorynews]

monday.com AI Teammates go live at scale on Bedrock

monday.com AI Teammates now run in production on Amazon Bedrock. See the architecture, guardrails, and metrics behind near‑autonomous code

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#AIAgents #AIUpdate #Automation

[bitpixelcoders]

Why Businesses Are Investing in Custom LLM Agent Development

Artificial Intelligence is evolving beyond chatbots. Modern LLM agents can understand business context, retrieve company knowledge with RAG, connect to APIs, and automate complex workflows across customer support, sales, HR, finance, and enterprise operations.

Instead of simply answering questions, intelligent AI agents help organizations reduce repetitive work, improve response times, and make better use of their data. With the right architecture and integrations, businesses can build scalable AI solutions that grow alongside their operations.

If you're exploring enterprise AI or planning your next automation project, learn more about custom LLM agent development here:

🔗 LLM agent development

[joelekm]

The Next CEO Won’t Be Human AI Agent Swarms Are Replacing Management | ZentrASI

This video breaks down the shift from traditional management to AI-powered multi-agent systems that can execute entire business workflows autonomously. Instead of relying on human teams and slow approval chains, companies are now using coordinated AI agents that research, analyze, and execute tasks in real time through an orchestration layer. We also explore how enterprises are already deploying these systems, and how “governance as code” keeps them safe, controlled, and compliant.

[aistorynews]

Snowflake Postgres general availability collapses data silos

Snowflake Postgres general availability moves operational data into the AI Data Cloud, cutting pipelines and feeding CoWork and CoCo for

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#AIAgents #OpenAI #VideoGeneration

[bitpixelcoders]

Building an AI Agent in 2026 Starts with the Right Strategy

AI agents are becoming one of the most exciting technologies for businesses and developers. Unlike traditional chatbots, modern AI agents can understand user requests, retrieve information, connect with APIs, and automate complete workflows across different business applications.

Whether you're creating an AI assistant for customer support, sales, HR, internal operations, or productivity, the development process should begin with a clear business objective. From there, choosing the right Large Language Model (LLM), implementing Retrieval-Augmented Generation (RAG), integrating business tools, and continuously testing your workflows are key steps toward building a reliable AI solution.

Successful AI agents aren't defined by the language model alone—they combine smart architecture, trusted knowledge sources, automation, and continuous improvement to solve real-world problems.

If you're interested in learning how to build an AI agent from scratch, this practical guide walks through the entire process step by step.

Read here: AI agents in 2026