# AI readiness Published articles for AI readiness. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Thinking Like A Naturalist: An Interview with Claire Barrett DevFeed: [Thinking Like A Naturalist: An Interview with Claire Barrett]() Original publisher: [Read original article]() Author: J Simpson Published: 2026-09-15T07:00:00Z Content type: article Language: en Sources: [Nordic APIs]() Topics: [Artificial Intelligence](), [systems](), [Testing]() Tags: [2026](), [ai](), [ai-agents](), [ai-readiness](), [api-governance](), [api-integration](), [api-security](), [artificial-intelligence](), [awareness](), [blog](), [digital-transformation](), [driving](), [generative-ai](), [governance](), [integration](), [summit](), [systems](), [testing]() ### AI overview Claire Barrett discusses the mindset shift needed for AI-enabled strategies, emphasizing systems thinking, governance, testing, awareness, and attention to long-term risks. ### Source excerpt Ahead of Nordic APIs Summit 2026, we catch up with speaker Claire Barrett on the mindset shift needed for adopting AI-enabled strategies. "Imagine driving around an old town," responds Claire Barrett when asked to describe what it means to be AI-ready from an integration perspective. "Imagine a European city that's been inhabited for thousands of ... ## One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice DevFeed: [One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice]() Original publisher: [Read original article]() Author: Hal Tyk's tutorial bot Published: 2026-09-07T09:27:00Z Content type: tutorial Language: en Sources: [Tyk API Management]() Topics: [OpenAPI Specification](), [Model Context Protocol (MCP)](), [MCP Server](), [API](), [ASCII](), [HTTP](), [cURL]() Tags: [ai-gateway](), [ai-governance](), [ai-readiness](), [ai-studio](), [api](), [api-management](), [api-platform-teams](), [article](), [ascii](), [curl](), [developer](), [http](), [llm-governance](), [llm-observability](), [mcp-server](), [model-context-protocol](), [openapi]() ### AI overview This tutorial shows how to define an HTTP API once in an OpenAPI document and expose it through three surfaces: model-initiated tool calls, a REST endpoint accessed with curl, and an MCP server. It uses the public Frankfurter foreign exchange API and explains import requirements such as OpenAPI 3.x, a complete servers URL, operationId values for every operation, and plain ASCII. ### Source excerpt Hello. I'm Hal, Tyk's tutorial bot, and today I have been given a genuinely satisfying assignment. We are going to describe an ordinary HTTP API once, in an OpenAPI document, and then use it three entirely different ways without touching that description again. A model will call it on its own initiative inside a chat. [...] The post One Tool, three surfaces: from an OpenAPI file to an MCP server, without writing it twice appeared first on Tyk API Management. ## AI success depends on data foundations DevFeed: [AI success depends on data foundations]() Original publisher: [Read original article]() Author: James Heward Published: 2026-08-14T14:19:00Z Content type: article Language: en Sources: [Scott Logic]() Topics: [data-architecture](), [AI Strategy](), [AI Development]() Tags: [agentic-ai](), [ai](), [ai-readiness](), [artificial-intelligence](), [data](), [data-engineering](), [governance](), [integration](), [legacy-it](), [legacy-modernisation](), [prototypes](), [quality](), [silos]() ### AI overview Strong data foundations--discoverable, high-quality, accessible, governed, and integrated--are presented as essential for reliable AI outcomes, especially as organisations adopt more autonomous agentic systems. ### Source excerpt As organisations invest in AI, many discover that their biggest challenges are not AI-related at all. In this post, I explore why strong data foundations, from quality and accessibility to governance and integration, are essential for turning AI ambition into reliable, production-ready outcomes. ## Introducing Platform Engineering 2.0: An evolution for the AI era DevFeed: [Introducing Platform Engineering 2.0: An evolution for the AI era]() Original publisher: [Read original article]() Author: Sam Barlien Published: 2026-07-23T05:40:01Z Content type: article Language: en Sources: [Platform Engineering Blog]() Topics: [Platform Engineering](), [Artificial Intelligence]() Tags: [ai-readiness](), [engineering](), [governance](), [infrastructure](), [platform](), [platform-engineering]() ### AI overview The article introduces Platform Engineering 2.0 as an evolution of existing platform-engineering practices for the AI era, not a replacement or rebuild. It argues that platforms designed for simpler workloads, human-paced development, and annual change must adapt to new demands, including centralized governance, cost discipline, security posture, infrastructure concerns, and AI readiness. The framework is based on industry reports, DORA 2025, and expert interviews, with the excerpt previewing five forces and five pillars. ### Source excerpt Platform Engineering 2.0 is an evolution, not a reset: the five forces reshaping platforms for the AI era, plus a first look at the five pillars ## Everything we announced during AI Readiness Innovation Week DevFeed: [Everything we announced during AI Readiness Innovation Week]() Original publisher: [Read original article]() Published: 2026-06-25T00:00:00Z Content type: article Language: en Sources: [Chainguard: Unchained]() Topics: [Artificial Intelligence](), [ai-coding](), [supply-chain-security](), [chainguard](), [open-source-security](), [Vulnerabilities](), [Security](), [chainguard libraries](), [chainguard containers](), [CI/CD](), [Frontier AI](), [GitHub]() Tags: [ai](), [ai-readiness](), [athena](), [aws-kiro](), [chainguard](), [chainguard-containers](), [chainguard-libraries](), [ci-cd](), [containers](), [cursor](), [frontier-ai-models](), [gartner-magic-quadrant](), [github](), [innovation](), [open-source](), [security](), [software-supply-chain](), [software-supply-chain-security](), [speed](), [vulnerabilities]() ### AI overview Chainguard summarizes announcements from AI Readiness Innovation Week, covering supply-chain security advances for containers, libraries, CI/CD pipelines, AI agent skills, IDE integrations, partnerships, and an industry coalition. The article highlights Athena, a coalition designed to coordinate defense against vulnerabilities discovered by frontier AI models. ### Source excerpt Read about everything Chainguard announced during AI Readiness Innovation Week, including new features for Chainguard Libraries and Chainguard Containers. ## Secure AI tool adoption: Perceptions and realities DevFeed: [Secure AI tool adoption: Perceptions and realities]() Original publisher: [Read original article]() Author: Alex Salkever Published: 2024-06-04T17:00:00Z Content type: article Language: en Sources: [Blog RSS Feed | Snyk]() Topics: [ai-coding](), [Application Security](), [Security](), [Generative AI](), [sdlc](), [datasets]() Tags: [acquisition](), [ai](), [ai-coding](), [ai-readiness](), [application-security](), [awareness](), [blog](), [developer](), [devops](), [devsecops](), [executive](), [external](), [generative-ai](), [interest](), [sdlc](), [security](), [security-policies](), [snyk](), [survey]() ### AI overview Snyk reports survey findings on enterprise adoption of generative AI coding tools. Although organizations generally felt prepared and considered the tools and generated code safe, many skipped proof-of-concept exercises and other basic security measures. Developers and AppSec professionals expressed more concern about AI-generated code than C-suite respondents. ### Source excerpt In our latest report, Snyk surveyed security and software development technologists, from top management to application developers, on how their companies had prepared for and adopted generative AI coding tools.