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nodesource

How We Designed a Node.js Production Debugging Experience with AI

Jun 11, 2026 By Mafe Serna In NodeSource
Earlier this year, our team launched the N|Solid Extension, a Node.js production debugging and observability tool designed for modern development environments. The goal was simple: help developers investigate production issues without constantly switching between dashboards, monitoring platforms, and their editor. Instead, runtime telemetry, diagnostics, security insights, and AI-assisted workflows could live directly where developers already spend most of their time.
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antino

How is Agentic AI rewriting Retail Banking?

Jun 11, 2026 By Radhakanth Kodukula In Antino
Your customers are no longer comparing you to the bank down the street. They are comparing you to Amazon, Netflix, and every hyper-personalized digital experience they interact with daily. And most banks are losing that comparison. Quite literally! Somewhere between the legacy core systems, the compliance overhead, and the quarterly earnings pressure, a tectonic shift has started. Agentic AI is no longer a concept in a research paper.
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ClearML

Inside NERSC at Berkeley Lab: How a DOE Office of Science User Facility Is Exploring ClearML for Scientific AI Workflows

Jun 11, 2026 By Adam Wolf In ClearML
NERSC, the mission high-performance computing center for the U.S. Department of Energy Office of Science, is using ClearML as part of the AI infrastructure stack for Perlmutter, the upcoming Doudna supercomputer, and the broader American Science Cloud. Here is a look at what they are exploring and why it matters for AI for science at scale.
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kong

How We Used Agentic AI to Fix Kong Gateway's Flakiest Tests

Jun 10, 2026 By Datong Sun In Kong
Each change to Kong Gateway's codebase triggers a comprehensive test suite that runs more than 17,000 * 2 = 34,000 test cases among the two primary architectures (x86 and ARM) we support. This process takes about 23.5 hours on a single machine. But we don't wait that long. A large fleet of machines runs the suite in parallel, and we shard the work aggressively so each commit finishes in a fraction of that time. That setup works well, right up until flaky tests get involved.
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Why Control Is Your New Competitive Advantage In The Age of AI | Perforce 2026

Jun 10, 2026 By Perforce In Perforce
When AI Starts Shipping Code: Why Control Is Your New Competitive Advantage AI systems are already generating code, creating tests, and orchestrating infrastructure changes across enterprise software delivery. But faster execution without control creates a new kind of risk. In this webinar, Perforce CTO leaders explore why uncontrolled AI execution is emerging as one of the biggest operational risks in modern software delivery — and what leading enterprises are doing about it.
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smartbear

Building Confidence Across APIs and AI Agents with the Swagger Contract Testing Kiro Power

Jun 10, 2026 By Matt Bonner In SmartBear
There is a specific kind of confidence that comes with deploying software. Not just “the tests passed” confidence, but the kind that comes from knowing the services your application depends on still behave the way you expect them to. Preserving that integrity becomes harder as systems grow, teams move faster, and AI agents become active participants in delivery workflows.
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tricentis

Practical applications for NeoLoad MCP: 3 use cases

Jun 10, 2026 By Annie Millerbernd In Tricentis
As AI-aided software development lifecycles pick up speed, performance teams are left with the familiar challenge of too much work, too few specialists, and results that take too long to analyze. Over the past year, Tricentis NeoLoad has shipped capabilities designed to address each of these problems directly. What started with Augmented Analysis accelerating root cause identification grew into a fully connected Model Context Protocol (MCP) architecture.
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thoughtspot

Agentic Analytics in Finance: Lessons from Navan and EcoLab

Jun 10, 2026 By Mayank Sinha In ThoughtSpot
Finance leaders are operating in one of the most demanding macro environments in recent memory. Interest rates are moving faster than most models anticipated, reshaping the cost of capital almost overnight. Supply chain fragility has also turned working capital management into a moving target, and geopolitical uncertainty is changing how you plan for the future. Yet for many finance functions, the analytics stack hasn't kept pace with that urgency.
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thoughtspot

How Thrive Learning Scaled 56K Users with Agentic Analytics

Jun 10, 2026 By Lindsay Lukens In ThoughtSpot
Live from Snowflake Summit '26, tech leaders from around the globe gathered to discover how the world’s most innovative companies are making AI real for business. But few sessions delivered as much raw, practical insight as the one presented by Frankie Woodhead, Chief Product & Technology Officer at Thrive Learning. Heading up a fast-growing, £20m ARR LearnTech business that serves over 500 global customers and 5 million users, Woodhead didn't give a standard product pitch.
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