The Difference Between Agentic AI and GenAI
Not all AI is agentic. Steffen Hoellinger, Airy’s CEO, breaks down the difference between agentic AI and generative AI, highlighting how AI agents utilize streaming data to reason and act.
Systems | Development | Analytics | API | Testing
Modern Software Development For Today's Systems & Applications
Is Data Integration the Real Engine Behind Effective AI Agents? #aiagents
Jay Mishra, our Chief Product and Technology Officer, explains why quality data is the true driving force behind successful AI agents. He also shares how Astera AI Agent Builder seamlessly connects to both internal and external data sources, ensuring that your AI agents are data-driven and ready to deliver powerful results.
What's the difference between Agentic AI and LLMs?
In this clip, Angie Jones explains how agentic AI goes beyond language prediction to actually take action — and what that means for the future of software development and testing.
Securing AI Interactions: Crossing the Hurdles of MCP Authorization
The rise of large language models (LLMs) and AI-powered applications brings incredible potential, but also poses significant security challenges. These applications have gotten much more useful with the emergence of agentic approaches and the ability to call out to different libraries, systems, and most importantly, to different APIs in order to take actions. They have moved from being a question answering resource to being able to do work, shop on your behalf, book travel, and update code.
Introducing Asgardeo MCP Server
Today, we're excited to officially release the Asgardeo MCP Server, enabling developers to securely manage their Asgardeo organizations using natural language—right from their favorite code editors like VS Code, Claude Desktop, Cursor, Windsurf, and other MCP-compatible clients. Asgardeo already supports Login Flow AI and Branding AI, making it easier to build secure, customized login and registration experiences using plain language.
From silos to AI success: 4 global enterprises on Fivetran + Snowflake
Global enterprises HubSpot, Saks, DocuSign, and Oldcastle Infrastructure modernized their data infrastructure on Fivetran and Snowflake, achieving AI-driven innovation, scalability, and millions in ROI.
EP 23 | From Poker Tables to Boardrooms: AI, Risk, and Business Communication with David Daneshgar
In high-stakes environments like professional poker and startup entrepreneurship, precision, timing, and strategy are everything. And nobody knows that better than David Daneshgar. In this episode of The AI Forecast, we’re joined by David Daneshgar, a World Series of Poker champion and now Co-founder and CEO of Whippy, a company using AI to transform how businesses communicate with their customers.
MCPs, Agents and the Future of Software Testing with Angie Jones
In this LIVE episode of Test Case Scenario, host Jason Baum, along with co-hosts Marcus Merrell and Evelyn Coleman, engages in a compelling conversation with Angie Jones, Global Vice President of Developer Relations, Block, Inc. They delve into the transformative impact of agentic AI and Model Context Protocols (MCPs) on software development and testing.
A Vision for the Future: Qlik's New Agentic AI Experience
The future of data and analytics will be nothing like the experience we're used to today. We are at the beginning of a transformation that will fundamentally reshape how businesses use data, make decisions, and create value. At the center of this revolution is Agentic AI. Agentic AI fundamentally changes the way we work with data – moving from passive, reactive AI systems to autonomous, goal-oriented agents capable of reasoning, planning, and executing complex tasks across diverse data landscapes.
Django AWS deployment with Elastic Beanstalk
Almost every web application is built for end-users to view and use. The application deployment process is an important operation in software development because it allows software to fulfill its purpose. This tutorial is primarily for software companies and developers to aid them in deploying and scaling web applications and services using a platform that automatically handles deployment with ease. Therefore, in this tutorial, we will be deploying a Django application to AWS.