AI-generated code

Checkmarx Fusion: Hybrid AppSec Scanning Meets Frontier AI

Checkmarx Fusion: Hybrid AppSec Scanning Meets Frontier AI

Checkmarx has launched Fusion, a hybrid scanning architecture that pairs its deterministic AppSec engines with Anthropic’s Claude models via Amazon Bedrock. The product targets regulated enterprises where data residency has blocked AI-powered security adoption. ECI Research data shows nearly two-thirds of practitioners say AI-assisted development has increased security risk, making the timing strategic.

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The 2026 Artifact Management Enforcement Gap | ECI Research

The 2026 Artifact Management Enforcement Gap | ECI Research

Cloudsmith’s second annual Artifact Management Report finds that AI-generated code has become near-universal, but governance hasn’t kept pace. Three in four organizations generate SBOM data without using it for real-time security enforcement. ECI Research examines what the EU Cyber Resilience Act deadline means for teams still relying on manual remediation.

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Why Standard Software Still Matters in the AI Era | ECI Research

Why Standard Software Still Matters in the AI Era | ECI Research

anynines CEO Julian Fischer argues that AI-generated software feeds on knowledge created by the standard software ecosystem rather than replacing it. ECI Research data shows engineering teams spend most of their time on maintenance, not innovation, making the promise of AI prototyping seductive but incomplete. The vendors that survive will be those who can prove their products contain judgment, accountability, and operational depth that no prompt can reproduce.

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AI Code Visibility Gap Widens as Production Use Hits 44.7%

AI Code Visibility Gap Widens as Production Use Hits 44.7%

Flux’s AI Code Generation Reality Check finds nearly half of organizations are running AI-generated code in production, while 35% can’t ship it confidently due to inadequate visibility. ECI Research examines the governance and tooling gaps this creates, and what engineering leaders should do next.

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AI Code Governance: GitLab Report Reveals a Control Crisis

AI Code Governance: GitLab Report Reveals a Control Crisis

GitLab’s AI Accountability Report surveyed 1,528 developers and technology buyers and found that AI code generation has outpaced the controls needed to manage it. Eighty percent of organizations adopted AI coding tools before building governance policies, and 43% cannot reliably distinguish AI-generated code from human-written code in their own codebase. The accountability phase of AI-assisted development has arrived, and most enterprises are not ready.

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LocalStack App Inspector Transforms Local Cloud Debugging

LocalStack App Inspector Transforms Local Cloud Debugging

LocalStack has launched App Inspector, a capability that surfaces data flows, event paths, and resource dependencies inside a local AWS emulation container. The feature targets the growing quality assurance gap created by AI-generated code, enabling developers to catch misconfigurations before they reach production. For ITDMs, the economics of local validation over live-cloud debugging are straightforward and the compliance benefits are immediate.

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CRA Compliance and Trustable Software: What OCX 2026 Revealed

CRA Compliance and Trustable Software: What OCX 2026 Revealed

The Eclipse Foundation’s OCX 2026 made clear that CRA compliance is a product development problem, not a legal checkbox. Manufacturers face a hard deadline, open source maintainers face an inbound wave of questionnaires, and AI-generated code is adding new layers of compliance debt. Here’s what ITDMs and developers need to act on now.

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