An ActiveState survey of 307 enterprise technology leaders found 94% of organizations using AI coding tools now depend on more open source software as a result, just as AI models surface more open source vulnerabilities that can be exploited in hours. Half admit dependencies reach production without review or approval, 32% traced a security incident to an unmanaged dependency in the past two years, and 83% say the cost of managing those risks is rising. Read the full findings on the paradox at the center of AI-assisted development:buff.ly/o59H71K #Cybersecurity #OpenSource #SupplyChainSecurity #AICoding

GemDB has added a Visual Studio Code extension that lets developers and AI agents use Python code to generate schemas for its object database, so objects persist exactly as they exist in application code and any change to the code changes the schema without mapping, migration or a DBA. Adding a field to an object now replaces what used to require join tables, foreign key definitions and backfill scripts, which matters as the pace of application development accelerates. Read the full article on what GemDB Code includes and where it fits in DevOps workflows: buff.ly/p67yvoB #Databases #DevOps #AIAgents #DeveloperTools

mabl today extended its test automation platform with a harness that enforces guardrails and testing standards for AI agents while using a knowledge graph to assess the impact of a code change, identify the tests needed to validate it and surface coverage gaps before a pull request is even made. Its agents saved development teams about 100,000 engineering hours in the last 90 days, but as Belcher cautions, DevOps teams cannot rely on AI coding tools to validate the code they create. Read the full article on why validating AI-generated code has become the bottleneck: buff.ly/77IVqvt #DevOps #AITesting #SoftwareDevelopment #AIAgents

Blitzy this week added a chat interface that lets DevOps teams express intent in natural language, with a software engineer describing a desired outcome that is automatically converted into a prompt assigning a task to an AI agent, and the ability to ask agents to explain how and why certain tasks were performed. A Build Prompt Strength scoring tool evaluates the draft against defined quality standards, and the platform's knowledge graph spans architecture, dependencies, business logic and data flows mapped back to actual code, which becomes critical when a pull request can span hundreds of thousands of lines. Read the full article on how agentic engineering handles review at that volume: buff.ly/Jym3xdt #DevOps #AIAgents #AICoding #SoftwareDevelopment

ScienceLogic's 2.7 update to its Skylar AI platform adds deeper visibility and control over AI agents automating IT operations, with a catalog that traces how requests were routed through an MCP server and a gatekeeper tool that inspects and quarantines suspicious content before an agent sees it. Very few IT teams let agents autonomously perform tasks without supervision, but as they gain confidence, those teams are evolving into supervisors of agents that handle work previously done by administrators and engineers. Read the full article on why IT management is never going to be the same again: buff.ly/wX5iq7g #Observability #AIAgents #AIOps #ITOperations

BAND today made available a desktop application that lets developers manage and collaborate with multiple coding agents, since each one runs in isolation and coordinating tasks between them has been the hard part. The app gives agents a way to communicate, divide responsibilities, delegate work and share context while giving developers a view of projects, blockers and progress, connecting agents across harnesses, machines and environments without standardizing on a single stack. Read why coordination, not code generation, is the bottleneck DevOps teams now face: buff.ly/T2E1SmD #DevOps #AIAgents #SoftwareDevelopment #AICoding