"Agents become increasingly helpful over time, require less repetitive clarification, and handle more complex tasks."
— Tim Bond, chief product officer at Adeptia, on how an AI knowledge base helps AI agents gradually understand how systems are used in practice. Read the full story here.
You can’t fire a bot: The blunt truth about AI slop and your job
Stop blaming the bot for slop. In this episode, Writer’s Matan Paul Shetrit explains why you're now an AI editor and why specialized models are the future of the enterprise. Next week, we will talk about the latest in Generative AI with Inception Labs' Ermon Stefano. Tune in to join the conversation!
Deploy a working RAG pipeline with a pre-built IaC template
Accelerate your generative AI projects with a Retrieval-Augmented Generation solution template. This AWS deployment uses Elastic Cloud for retrieval and AWS Lambda for orchestration, provisioned automatically with Terraform.
Week in review: Why AI coding agents failed (at first)
AI agents have become the software industry’s latest fascination. Backed by large language models (LLMs), this new class of AI is unlocking data-driven decision-making and autonomous actions, transforming enterprise software practices and business workflows in the process.
However, it wasn’t always this way, writes TNS contributor Bill Doerrfield in this week’s feature story.
According to Ajay Prakash, a senior staff software engineer at LinkedIn, AI agents initially faced a major gap. “Out of the box, AI coding agents weren’t effective,” Prakash tells The New Stack. They lacked context and awareness of internal systems, frameworks, and practices, he adds.
Agentic knowledge bases have emerged to close that gap.
The agentic AI race is on, and most organizations are at risk of losing it. Not because they lack ambition, but because they’re fighting three wars simultaneously without a unified strategy.
Imagine you could use an operating system that’s as easy as ChromeOS yet as powerful as Linux. What would you do with that? The easier question might be, “What could you not do?”
Building a self-service developer platform the thoughtful way March 12 | Virtual
As more organizations move workloads on-premises, demand for a “public cloud-like” experience is driving the adoption of Kubernetes-based internal platforms. In this session hosted by Charles Humble, Broadcom’s Jad El-Zein will show how to automate full-stack Kubernetes deployments with a single git commit.
Scaling real-time AI & ML workloads for performance and efficiency March 18 | Virtual
In this webinar, DragonflyDB co-founder and CEO Oded Poncz will explain why real-time context is now the core data primitive for intelligent systems. We’ll cover where traditional infrastructure falls short, what modern AI/ML workloads demand, and how purpose-built systems enable predictable, efficient scale.
At HumanX, every track is designed to meet you where you work, whether it’s tech, marketing, finance or HR – and take you where AI is going. Join this AI conference to discover the content and cutting-edge takeaways relevant to your role, and walk away with practical insights that help you turn ideas into results.
Attend the Red Hat Summit to find clarity in the complexity of a changing technology landscape. Immerse yourself in the open source community and emerging innovation. Connect with peers and industry leaders as you explore sessions on AI, automation, emerging technologies, and more.
