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Practical AI-Enabled Observability for Agents and LLMs

You’re told to “go build agents” without clear guidance on what that actually means, how to do it well, or how to know if it is working. You are not a data scientist. You are a software engineer. In this talk, a Datadog AI product leader Shri Subramanian breaks down what changes when you move from building applications to building AI agents, and why familiar approaches like traditional testing and linear delivery fall short. We will explore how agent development shifts the focus from code alone to data, prompts, and evaluation, and why functional reliability matters just as much as operational reliability.

The Next Phase of Agentic AI

The Enterprise AI Survey conducted by Digitate in collaboration with Sapio Research states that the journey of enterprise automation and AI adoption has evolved significantly. The initial waves focused primarily on improving accuracy, efficiency, and reducing costs. Now, the next phase, Agentic AI, is transforming this shift from mere automation to dynamic collaboration.

Operating agentic AI with Amazon Bedrock AgentCore and Datadog LLM Observability: Lessons from NTT DATA

This guest blog post is by Tohn Furutani, SRE Engineer at NTT DATA. Over the past year, the conversation around generative AI has shifted from single-shot use cases—such as summarization, Q&A, and chat interfaces—to agentic AI systems that can make decisions based on context, plan multistep actions, invoke tools, and adapt as conditions change.

AI agent observability: The developer's guide to agent monitoring

Most "agent observability best practices" content reads like a compliance checklist from 2019 with "AI" pasted over "microservices." Implement comprehensive logging. Establish evaluation metrics. Create governance frameworks. Not a single line of code. No mention of what happens when your agent silently picks the wrong tool on turn 3 and you need to figure out why.

Kosli and Adaptavist Partner to Automate Governance for AI driven Software Delivery

Today, Kosli and Adaptavist announce a strategic partnership to help regulated enterprises automate governance for AI driven software delivery - making it automated, continuous, and evidence-driven rather than a manual checkpoint that sits apart from DevOps and CI/CD. Adaptavist brings deep enterprise DevOps transformation expertise: assessment and strategy, DevSecOps integration, developer experience, and implementation across Atlassian, GitLab, and AWS.

Deterministic by Design: How Harness Grounds AI Agents in Structured Data | Harness Blog

When AI agents operate across a multi-module platform like Harness (from CI/CD to DevSecOps to FinOps), the number one goal is to give you answers that are correct, consistent, and grounded in real data. Getting there requires a deliberate architectural choice: when a question can be answered from structured platform data, the agent should use a schema-driven Knowledge Graph rather than raw API calls via MCP. The principle is simple: if the data is modeled, retrieval should be deterministic.

How Uninterruptible Power Tech is Shielding Automated Supply Chains from Grid Failures

Modern supply chains are unrecognisable from those of just a decade ago. Today, vast warehouses operate with precision choreography, relying heavily on autonomous robotics, advanced sensor networks, and real-time edge computing. However, this hyper-efficiency has a distinct and growing vulnerability. As operations become entirely dependent on continuous electricity, any disruption to the power supply can bring a highly automated logistics hub to a grinding halt.

From AI Idea to Real System: What Changes Along the Way

Most companies don't struggle with the idea of AI. They struggle with what to do with it. The potential is clear-automation, predictions, better decisions. But translating that into something useful inside a business is where things become less obvious. That's usually when ai ml consulting services start to make sense.

IREX Enhances FireTrack AI Module for Faster, More Accurate Fire Detection

WASHINGTON, DC - IREX, a global developer of ethical AI and intelligent video analytics, has announced a significant upgrade to its FireTrack fire and smoke detection module, expanding its capabilities across a wide range of environments. As outlined in an article on TNW, the updated solution is designed to work seamlessly with existing camera infrastructure, eliminating the need for additional hardware while extending its use to critical infrastructure, public institutions, residential and commercial properties, and natural environments such as parks and forests.

Top Shopify Plus Search and Discovery Tools for Scalable eCommerce Operations in 2026

On-site search is not primarily a user experience problem. It is a data infrastructure and operations problem that happens to affect how shoppers navigate a storefront. For Shopify Plus merchants running catalogs of thousands of SKUs across multiple collections, search and discovery tooling sits at the intersection of product data management, behavioral analytics and real-time content delivery. When that infrastructure is weak, the symptoms show up as missed conversions and abandoned sessions.