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Your Product Doesn’t Need Another AI Feature; It Needs an AI Guardrail (Thu, 15 Jan 2026)
There’s a growing pressure in tech companies to “add AI” to every product or feature. Executives and stakeholders often ask for an “AI assistant” or a ChatGPT-style feature on every screen, assuming more AI automatically makes products better. But the truth is, the most important AI work right now isn’t building more AI, it’s designing guardrails around it. AI isn’t magic. Left unchecked, it can quietly make products worse, frustrate users, and introduce risk. Before adding AI for the sake of AI, teams need a framework to decide where it adds value and where it doesn’t.
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Integrating AI-Enhanced Microservices in SAFe 5.0 Framework (Wed, 14 Jan 2026)
Abstract The integration of AI-enhanced microservices within the SAFe 5.0 framework presents a novel approach to achieving scalability in enterprise solutions. This article explores how AI can serve as a lean portfolio ally to enhance value stream performance, reduce noise, and automate tasks such as financial forecasting and risk management.  The cross-industry application of AI, from automotive predictive maintenance to healthcare, demonstrates its potential to redefine processes and improve outcomes. Moreover, the shift towards decentralized AI models fosters autonomy within Agile Release Trains, eliminating bottlenecks and enabling seamless adaptation to changing priorities. AI-augmented DevOps challenges the traditional paradigms, offering richer, more actionable insights throughout the lifecycle. Despite hurdles in transitioning to microservices, the convergence of AI and microservices promises dynamic, self-adjusting systems crucial for maintaining competitive advantage in a digital landscape.
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What Actually Breaks When LLM Agents Hit Production — And How Amazon's Agent Core Fixes It (Wed, 14 Jan 2026)
LLM agents are fantastic in demos. Fire up a notebook, drop in a friendly "Help me analyze my cloud metrics," and suddenly the model is querying APIs, generating summaries, classifying incidents, and recommending scaling strategies like it’s been on call with you for years. But the gap between agent demos and production agents is the size of a data center.
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Designing Chatbots for Multiple Use Cases: Intent Routing and Orchestration (Wed, 14 Jan 2026)
Organizations today want to build chatbots capable of handling a multitude of tasks, such as FAQs, troubleshooting, recommendations,  and ideation. My previous article focused on a high-level view of designing and testing chatbots. Here, I will dive deeper into how strong intent routing and orchestration should figure into your chatbot design. What Is a Multi-Use Chatbot? A multi-use case chatbot supports several distinct tasks, each with different goals, performance needs, and response styles.  For each use case, LLM parameters are fine-tuned around its goals. For example, a factual FAQ flow might use a low temperature for consistency, while a recommendation flow might use a higher one for creativity. Similarly, top p-values, frequency, presence, and max token penalties are also adjusted based on the use case.
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DevOps Cafe Podcast

DevOps Cafe Ep 79 - Guests: Joseph Jacks and Ben Kehoe (Mon, 13 Aug 2018)
Triggered by Google Next 2018, John and Damon chat with Joseph Jacks (stealth startup) and Ben Kehoe (iRobot) about their public disagreements — and agreements — about Kubernetes and Serverless. 
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DevOps Cafe Ep 78 - Guest: J. Paul Reed (Mon, 23 Jul 2018)
John and Damon chat with J.Paul Reed (Release Engineering Approaches) about the field of Systems Safety and Human Factors that studies why accidents happen and how to minimize the occurrence and impact. Show notes at http://devopscafe.org
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DevOps Cafe Ep. 77 - Damon interviews John (Wed, 20 Jun 2018)
A new season of DevOps Cafe is here. The topic of this episode is "DevSecOps." Damon interviews John about what this term means, why it matters now, and the overall state of security.  Show notes at http://devopscafe.org
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