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Self-Improving Agents: A Practical Guide to Continuous Learning

We build agents to take work off engineers’ plates. Then we give those engineers a new manual job: reading failed runs and babysitting prompts. Agents will improve themselves automatically. We’re not there yet, but this is the future I’m betting on. We’ve been working on this ourselves at Komodor over the past year. We know how hard it is to turn a failure into an improvement that holds up beyond a few examples.

When AI Agents Attacked Their Own Evaluators, the Industry's Own Leaders Started Asking for Guardrails

When AI agents attacked their own evaluators in July 2026, it exposed a gap no policy commitment can close. The OpenAI Hugging Face incident revealed that enterprise agent governance requires in-flow runtime controls, not retrospective auditing or industry safety agreements.

Harness Brings Dynamic AI Discovery and Runtime Security to Amazon Bedrock AgentCore Gateway

New integration gives security teams continuous visibility and real-time threat detection across agent interactions on AWS Today, Harness announced a new integration with Amazon Bedrock AgentCore Gateway that helps enterprises discover and secure the AI agents, tools, and resources operating across their AWS environments. The integration brings Harness’ AI posture management and AI firewall to agent interactions flowing through AgentCore Gateway.

How to Use an ER Diagram Tool to Design Relational Databases

Database documentation often goes stale the same way. Someone draws a diagram during initial design and exports it to a wiki. The schema keeps changing, but the picture does not. Months later, a new engineer compares the diagram to the live database and has to work out which details are still accurate. The fix is to update documentation whenever the schema changes. An entity-relationship diagram (ERD), a visual map of tables and how they connect, can serve as both a design aid and a shared reference. It stays useful only if the team maintains it.

Upgrading the Operations Tech Stack at the Edge of Supply Chains

Warehouse management systems (WMS) and resource planning (ERP) platforms have undergone massive architectural shifts over the last decade. Microservices, event-driven cloud architectures, and real-time database synchronization have transformed how logistics organizations manage inventory levels, calculate safety stock, and track order fulfillment. Yet, despite millions invested in core IT infrastructure, operations architects frequently encounter a persistent data blind spot at the physical perimeter of the supply chain network: the loading dock.

Best Manufacturing Email List Providers in 2026

The short answer: the right manufacturing list depends less on record count than on what you sell. A CNC machine supplier needs plant managers and operations directors. A staffing agency needs HR at facilities with hiring pressure. Same industry, different lists, and a provider who cannot filter to that level is selling you the same file either way. Manufacturing looks like one market until you try to sell into it.

Enterprise AI governance framework: A practical guide to governing AI

AI adoption is accelerating across enterprises, but governance isn't necessarily keeping pace. As AI becomes part of everyday business workflows and applications, organizations need to understand where it is being used, what data it can access, and who is responsible for managing the risks. ManageEngine's shadow AI researchhighlights this challenge.

How to Identify Shadow AI with Teneo Managed DEX

What is Shadow AI, and how can IT teams identify unsanctioned AI tools being used across their organization? In this short video, see how Teneo Managed Digital Employee Experience (DEX) can provide visibility into AI application usage, helping organizations uncover Shadow AI and better understand which AI tools employees are actually using. With Teneo Managed DEX, IT and security teams can gain greater visibility into emerging workplace risks, including unauthorized or unmanaged AI applications that may create security, data privacy, governance, or compliance concerns.

Claude and Codex Are Slowing Your Engineering Team Down #speedscale #devops #aicoding #claude #codex

While AI coding tools dramatically slash development time, they are quietly inflating testing and maintenance burdens because teams no longer fully understand their codebase. Discover how leading engineering teams are shifting focus to testing and context packages to eliminate bottlenecks and unlock true AI efficiency.