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Articole: 17
  1. AI-Assisted Development: The Accountability Layer

    Veracode’s 2025 GenAI Code Security Report found security flaws in 45% of AI-generated code outputs across 100+ models and four programming languages.

  2. AI SDLC Governance: Three Layers for Engineering Leaders

    The same AI tooling.

  3. AI-Augmented CI/CD: Shift Left Security With Bounded Risk

    Code reviews are a bottleneck.

  4. Orchestrating AI Agents: A Subagent Architecture

    Single-agent AI coding hits a ceiling.

  5. Agent-Ready Websites: The 5-Layer Implementation Stack

    Every website serves two audiences: humans and machines.

  6. How Does Context Engineering Drive Multi-Agent Reliability?

    In June 2025, Shopify CEO Tobi Lütke introduced the term “context engineering” as a more precise alternative to prompt engineering.

  7. Open-Weight LLMs Reach the Structured Output Quality Ceiling

    Three models entered a pre-registered blind evaluation: Gemma 4 26B-A4B at $0.00042 per run, Claude Haiku 4.5 at $0.0119, and Claude Sonnet 5 at $0.0399.

  8. AI Approval Gates: Engineering Oversight at Machine Speed

    In April 2026, a PocketOS coding agent deleted a production database and its only backup in nine seconds, triggering a 30-hour outage (Crane, 2026).

  9. AI Agents in Legacy Systems: ROI Without Modernization

    You run a company with SAP, mainframe, or AS400 systems that work but won’t win awards.

  10. What a Null Result Taught Us About AI Agent Evaluation

    A Google Research paper demonstrates that repeating the entire user prompt verbatim can lift accuracy by up to 76 percentage points at zero output cost.

  11. Why Your AI Agent Failed in Production

    Your AI agent just approved a $50,000 invoice for office supplies.

  12. RAG for Legacy Systems: 7,432 Pages to 3s Answers

    Your legacy system documentation is 20 years old, 7,432 pages, and locked in PDFs.

  13. SRE for AI Agents: Error Budgets, Trust, and 90 Trials

    AI tooling budgets hit record highs.

  14. AI Adoption in Engineering: Breaking the 50% Plateau

    Purpose-built AI tooling cuts per-task cost 21-68%, yet only 13% of organizations have AI agents broadly integrated into workflows (BCG, 2025) and self-reported velocity diverges from measured outcomes by 39 percentage points (Becker et al., 2025).

  15. AI-Governed DNS Migration Without Maintenance Windows

    DNS migrations fail in production because teams discover errors after the nameserver switch, not before it.

  16. AI Delivery Decision Frameworks: Type 1, Type 2, DACI

    A bench mismatch, a scope gap, a stakeholder escalation: each gets treated as a hard blocker requiring structural intervention, when most warrant fast iteration instead.

  17. AI Supply Chain Attacks: New Vectors in Dependencies

    A CI pipeline trusts 400 packages.