# guardrails Published articles for guardrails. This is one page of public article previews, not the complete archive. Follow Next page to continue. Summaries are not the original full articles. ## Building an Internal Developer Platform with Artificial Intelligence DevFeed: [Building an Internal Developer Platform with Artificial Intelligence]() Original publisher: [Read original article]() Author: Ben Linders Published: 2026-09-17T11:11:00Z Content type: news Language: en Sources: [InfoQ]() Topics: [internal developer platform](), [AI Development](), [AI search](), [agent observability](), [OpenTelemetry](), [telemetry]() Tags: [agent](), [agents](), [artificial-intelligence](), [culture-methods](), [developer-experience](), [developer-platform](), [distributed-tracing](), [guardrails](), [internal-developer-platform](), [logging](), [logs](), [metrics](), [news](), [opentelemetry](), [platform-artificial-intelligence](), [platform-engineering](), [prometheus](), [traces]() ### AI overview This news article covers a KubeCon presentation about using AI agents as an internal developer platform. It discusses semantic search across sources such as Git, Slack, Jira, repositories, pull requests, and wiki pages; guardrails for controlling actions; and logs, metrics, and traces for understanding agent behavior. The speakers also describe OpenTelemetry conventions for GenAI and related observability tools. ### Source excerpt Agents are becoming the new developer platform, using semantic search with data from tools like Git, Slack, and Jira for context. Things to consider are setting guardrails to block or allow things, and using logs, metrics, and traces to understand agent behavior. By Ben Linders ## How Coding Agents Are Shifting the Focus of Software Engineering DevFeed: [How Coding Agents Are Shifting the Focus of Software Engineering]() Original publisher: [Read original article]() Author: Dr Milan Milanović Published: 2026-09-03T15:00:51Z Content type: opinion Language: en Sources: [Tech World With Milan Newsletter]() Topics: [Software Engineering](), [AI-assisted coding](), [future of software](), [AI Development]() Tags: [agent](), [architecture](), [coding-agents](), [future-of-software](), [guardrails](), [junior-developer](), [software-engineering]() ### AI overview This commentary argues that coding agents are making code generation, testing, refactoring, and bug investigation cheaper and faster. As a result, software engineering increasingly emphasizes judgment, specification, verification, architecture, ownership, team scope, and managing technical debt. ### Source excerpt Since the beginning of writing software, it has been a hard thing to do. ## Want to use AI agents safely? Start with design DevFeed: [Want to use AI agents safely? Start with design]() Original publisher: [Read original article]() Author: Colin Eberhardt Published: 2026-08-18T13:12:00Z Content type: opinion Language: en Sources: [Scott Logic]() Topics: [Artificial Intelligence](), [AI Strategy](), [Security](), [Monitoring](), [Architecture & Design](), [Resilience]() Tags: [agentic-ai](), [agents](), [ai](), [artificial-intelligence](), [auditability](), [design](), [end-to-end-process](), [featured](), [governance](), [guardrails](), [monitoring](), [observability](), [operational-resilience](), [quality](), [risk-management](), [security](), [service-design](), [systems](), [trust]() ### AI overview This article argues that organisations adopting AI agents should begin with process and system design rather than controls alone. It explains that design should account for human and machine strengths, establish proportionate guardrails, and define how observability and monitoring evolve as the system matures. ### Source excerpt Concerns about control are one of the biggest barriers to adopting agentic AI, particularly in regulated environments. In this post, we discuss how organisations can harness AI safely by designing processes around the strengths of both humans and machines, then applying the right controls, guardrails and monitoring. ## Are REA's Architecture Principles still relevant in an AI-assisted world? DevFeed: [Are REA's Architecture Principles still relevant in an AI-assisted world?]() Original publisher: [Read original article]() Author: Jarrod Boyes Published: 2026-08-14T05:19:28Z Content type: article Language: en Sources: [REA Group]() Topics: [AI-assisted coding](), [systems](), [Development](), [Software]() Tags: [ai-assisted-coding](), [architecture](), [guardrails](), [software](), [systems](), [tech]() ### AI overview REA reviews whether its architecture principles remain relevant as AI-assisted coding and broader AI integration become part of software delivery. The review concludes that the principles still provide a strong foundation, while stronger guardrails and contextual adjustments are increasingly important. ### Source excerpt Are REA's Architecture Principles still relevant in an AI-assisted world? Introduction At REA, we use a set of architectural principles to guide how we build and evolve the systems behind our products. My colleague Shane previously shared these principles in the article Scaling technology with architectural principles. Every year we review these principles, not because we expect them to change every time, but because we want to test them against the environment we're working in now. ## Unlocking your data: the value is in collaboration DevFeed: [Unlocking your data: the value is in collaboration]() Original publisher: [Read original article]() Author: Sam Perridge Published: 2026-08-12T14:59:00Z Content type: opinion Language: en Sources: [Scott Logic]() Topics: [data](), [datasets](), [Artificial Intelligence](), [decision-making](), [systems]() Tags: [ai](), [business-intelligence](), [claude](), [collaboration](), [data](), [data-democratisation](), [data-engineering](), [data-maturity](), [data-platform](), [datasets](), [decision-making](), [governance](), [guardrails](), [reporting](), [self-service]() ### AI overview This opinion article argues that organisations unlock more value from data when datasets are connected and insights are accessible across teams. It describes a progression from paper records and siloed systems to connected and democratised data, including self-service analytics and AI, while emphasising governance and practical adoption. ### Source excerpt Organisations often focus on collecting data and connecting systems, but the greatest value comes from helping datasets work together and making insights accessible to the people who need them. In this post, I explore the journey from siloed data to democratised access, showing how self-service analytics and AI can unlock hidden value, while strong governance provides the guardrails for confident decision-making. ## Self-Hosted LLM Inference: Serving, Benchmarking and Agent Guardrails DevFeed: [Self-Hosted LLM Inference: Serving, Benchmarking and Agent Guardrails]() Original publisher: [Read original article]() Author: Philipp Lehmann (philipp.lehmann@gruppe.ai) Published: 2026-08-07T07:00:00Z Content type: article Language: en Sources: [Philipp Lehmann]() Topics: [Self-hosted](), [Large Language Model](), [Inference](), [model-serving](), [benchmarking](), [LLM evaluation / benchmarking](), [API]() Tags: [agents](), [api](), [benchmarking](), [guardrails](), [inference](), [llm](), [ollama](), [security](), [self-hosted](), [testing]() ### AI overview This article examines self-hosted LLM inference for infrastructure work, focusing on data locality, local-versus-hosted model tradeoffs, repeatable benchmarking on personal tasks, model serving, and guardrails for agents that can propose or apply changes. ### Source excerpt Ollama OpenAI-compatible /v1/chat/completions: a repeatable benchmark on your own tasks and a dry-run plus --approve guardrail for infrastructure agents. ## High Frequency Trading and Lessons for Agentic AI DevFeed: [High Frequency Trading and Lessons for Agentic AI]() Original publisher: [Read original article]() Author: Phil Venables Published: 2026-05-02T12:45:05Z Content type: opinion Language: en Sources: [Risk and Cyber]() Topics: [Artificial Intelligence](), [AI Strategy](), [systems](), [benchmarking]() Tags: [agentic-ai](), [agents](), [ai](), [automated](), [benchmarking](), [cybersecurity](), [financial](), [guardrails](), [risk]() ### AI overview The article argues that lessons from high-frequency and algorithmic trading controls can inform deterministic guardrails for mostly non-deterministic agentic AI systems as they evolve from chatbots into systems that act. It also argues that benchmarking should focus on outcomes such as control effectiveness rather than input budgets alone. ### Source excerpt I suspect I'm not the only former or current financial markets technologist that sees parallels between the world of high frequency / algorithmic trading controls and what is needed for appropriate deterministic guardrails around our, mostly, non-deterministic agentic AI systems. As we transition from chatbots to systems of agents, that don't just talk but act, we are entering a regime of automated risk that the financial markets have navigated, mostly successfully, for decades.... ## Ways in which GenAI has changed the way I write code so far DevFeed: [Ways in which GenAI has changed the way I write code so far]() Original publisher: [Read original article]() Author: Julien Published: 2026-04-30T11:19:11Z Content type: opinion Language: en Sources: [Thoughts, stories and ideas.]() Topics: [genai](), [Orchestration](), [Vibe coding](), [Claude Code](), [coding](), [junie]() Tags: [ai](), [claude](), [development](), [genai](), [guardrails](), [implementation](), [orchestration](), [repository](), [tests](), [workflow]() ### AI overview The author describes how generative AI has changed their home coding workflow, including stack and IDE choices, Git usage, and the ability to turn more ideas into pet projects. They use Claude and orchestration tools such as Maestro for implementation, with tests and Markdown guardrails guiding and reviewing AI-generated code. ### Source excerpt AI has fundamentally transformed my developer workflow, from stack choices and IDE preferences to how git is used. I using Claude and orchestration tools like Maestro to guide implementation while tests serve as guardrails. ## Temporal as a control plane for production agentic AI systems DevFeed: [Temporal as a control plane for production agentic AI systems]() Original publisher: [Read original article]() Author: Joshua Smith Published: 2026-04-23T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Orchestration](), [Artificial Intelligence](), [control-plane](), [Architecture & Design]() Tags: [agentic](), [agentic-ai](), [ai](), [cost](), [enterprise](), [guardrails](), [observability](), [orchestration](), [temporal-voices](), [versioning]() ### AI overview The article explains how Temporal can help turn agentic AI prototypes into production systems. It describes agent patterns including conversational agents and event stream processors, and discusses orchestration, guardrails, observability, versioning, and cost controls. ### Source excerpt Learn how Temporal bridges the gap between agentic AI demos and production-ready systems -- with guardrails, observability, versioning, and cost controls built in. ## Temporal Ruby SDK Reaches General Availability with Rust Core and Deterministic Fiber Scheduler DevFeed: [Temporal Ruby SDK Reaches General Availability with Rust Core and Deterministic Fiber Scheduler]() Original publisher: [Read original article]() Author: Chad Retz Published: 2025-10-16T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Ruby](), [SDKs](), [Rust](), [Programming](), [cancellation](), [Code](), [Open Source]() Tags: [announcements](), [asynchronous](), [cancellation](), [fiber](), [guardrails](), [open-source](), [ruby](), [rust](), [scheduler](), [sdk](), [workflows]() ### AI overview Temporal Ruby is now generally available, providing Ruby developers with a native-feeling SDK for building durable software and Workflows. The article introduces its programming model and demonstrates Activities, deterministic fibers, durable timers, cancellation, and updates, while also discussing the Rust-powered implementation and execution guardrails. ### Source excerpt Temporal Ruby SDK is GA. Build durable Ruby Workflows with native APIs, a Rust-powered core, a deterministic fiber scheduler, and guardrails for safe execution. ## The agentic future with Temporal: A fireside chat DevFeed: [The agentic future with Temporal: A fireside chat]() Original publisher: [Read original article]() Author: Jeroen Vollenbrock Published: 2025-09-22T00:00:00Z Content type: article Language: en Sources: [Temporal Blog]() Topics: [Artificial Intelligence](), [Testing](), [Software Engineering](), [reliability]() Tags: [agentic-ai](), [ai](), [cost](), [guardrails](), [how-to](), [manager](), [testing]() ### AI overview A fireside chat among Temporal, Essent, and Navara examines the practical challenges of building agentic AI systems. It discusses testing unpredictable outputs with evaluations and guardrails, deciding which tasks should use LLMs versus deterministic code, and limiting agent actions to improve control and reliability. ### Source excerpt Key takeaways on agentic AI: testing unpredictable systems, hybrid workflows with Temporal, context engineering, cost tradeoffs, and practical next steps.