Continuous integration

Evidence (4)

• 6The New Stack·8/5/2026framework_update
  Software companies shift toward internal dev tools

  The article argues that as AI generates more application code, software engineers will increasingly focus on building the platforms, guardrails, and feedback loops that control and support code generation. It frames this as an expansion of platform engineering, with internal developer platforms merging delivery infrastructure and agentic AI controls into one shared layer.

• 3InfoQ·8/4/2026framework_update
  Microservices Platforms and Team Topologies

  Chris Richardson explains how internal platforms and Team Topologies can speed up microservices delivery while reducing cognitive load on stream-aligned teams. He outlines six platform patterns spanning security, observability, build, and deployment, and highlights common pitfalls in platform engineering.

• 7The New Stack·7/27/2026research
  How Anthropic uses evals to guide product development

  Anthropic says evaluation suites have become the core artifact for building frontier AI products, replacing traditional product requirements documents for many teams. The company relies on representative eval sets, continuous testing, and hands-on model use to catch capability jumps, failures, and unintended behaviors as Claude evolves from chatbot to coding assistant.

• 6The New Stack·7/22/2026product_launch
  Harness launches AI Agent Development Lifecycle service for governed agent deployment

  Harness has launched its AI Agent Development Lifecycle (DLC) service to help teams ship AI agents through familiar governance, testing, and security pipelines. The company says the approach focuses on making the delivery pipeline deterministic with quality gates, eval scores, and full audit records, rather than trying to make agent behavior itself reproducible.