I have to confess to actually listening to this snippet from Dean Bodart and it resonated. Treating an AI agent like a "new starter" without the knowledge of how you do things in your business is a good analogy. I've hired a lot of new starters in my time and some are definitely better than others, especially if they have decent experience and some learn quicker, especially from a good and experienced coach. However, it's a good idea to make sure that the new starter is well-vetted and well-trusted and isn't sharing the intellectual property that you're teaching it with your competitors. It might be too late. But I'm sure you've at least masked the PII and IP in your training data.

Unlocking the potential of AI-driven code reviews - AI can analyze code changes faster and more accurately than humans. - This reduces errors, saves time, and boosts team productivity significantly. - Try integrating an AI code review tool into your workflow today. - Be cautious of over-reliance; always have a human review for context. - How has AI impacted your coding processes or team dynamics? #AI #CodeReviews #SoftwareDevelopment #TechTrends #Productivity #Automation #MachineLearning #DevOps #Innovation #Collaboration️;

🚀 From Hours to Minutes — AI in Action We used to spend hours deploying 25+ microservices one by one. With AI-assisted scripting, I built an automated deployment process that: ✅ Deploys all services end-to-end ✅ Monitors real-time progress ✅ Sends completion notifications What once required constant manual effort now runs seamlessly — Demonstrating how AI can elevate engineering efficiency while keeping human insight at the core. #AI #DevOps #Automation #Microservices #EngineeringExcellence #Productivity

DevOps teams automate workflows with AI agents, but someone still needs to watch the watchers. Tabnine's solution: centralized policies that audit every AI decision before it ships. Tabnine just launched Agentic - their new AI agents that go beyond code suggestions. These agents now handle: 🔧 Complete refactoring workflows 🐛 Automated debugging processes 📝 Documentation generation 🔍 Code review and compliance checks The game-changer? You're not locked into one AI model. Connect your preferred LLM. Pay a flat monthly fee plus usage. Simple. But here's the real insight - AI-generated code without governance creates technical debt faster than you can manage it. Tabnine's answer: centralized policies with full audit trails. Every AI decision gets tracked. Every change gets reviewed against your standards. Every team stays within budget with customizable quotas. This isn't just about automating tasks anymore. It's about scaling quality control as AI becomes your primary coding partner. The question isn't whether AI will write most of your code. It's whether you'll have systems in place to manage what it creates. How is your team preparing for AI-first development workflows? #DevOps #AIcoding #TechnicalDebt 𝐒𝐨𝐮𝐫𝐜𝐞: https://lnkd.in/dX5JNXd2

When Marc shared this story, it hit deep. In DevOps and AI, we face the same truth every day. You build something from scratch - a CI/CD pipeline, a monitoring stack, or a custom ML model. You pour your heart into it. But then technology evolves. New tools emerge. AI copilots are starting to handle deployments more efficiently, predicting incidents before they occur. And suddenly… your “perfect system” starts holding you back. Sometimes, the smartest move isn’t fixing - it’s letting go. Because in tech (and in life), At times, leaving isn’t losing - it’s leading. #Leadership #DevOps #AI #Innovation #Automation #Mindset #SudheerWrites

In many companies, AI projects resemble never-ending lab experiments — teams keep testing and refining models, yet they never reach real users. The main reason? A lack of a clear delivery framework. That’s exactly where DevOps makes the difference: — it automates processes, eliminating manual steps in code building, testing, and deployment; — it ensures quality control through automated testing, monitoring, and rapid issue detection; —it unifies code, data, and models into a single CI/CD pipeline, reducing the time from experiment to release; — it guarantees safe deployment with canary releases, rollbacks, and controlled updates. Together with Devtorium, a software development company, AppRecode prepared an article explaining how CI/CD, IaC, and automation help turn ideas into production-ready solutions faster. Follow the link in the comments to read the full post on our blog and learn how to bring DevOps and AI together in your own projects. #AI #DevOps #Automation #SoftwareDevelopment #CICD

Messy requirements. Conflicting priorities. Tests that take forever to design, only to break the moment something changes. These are some of the biggest frustrations in QA. 😣 That’s why we created a free training, Turning Requirements into Reliable Tests with AI-Augmented Design. Here’s what you’ll dive into: 👉 Lesson 1 with Noelle R. How to move from AI hype to AI execution — responsibly, ethically, and with trust. 👉 Lesson 2 with Jonathon Wright How to deal with ambiguous or conflicting requirements and create testable assets that align with real business rules. 👉 Lesson 3 with Ian Sharp How to use GenAI to automate test design, shrinking weeks of manual work into minutes. The result: ✅ Faster test creation ✅ Better alignment with business goals ✅ Tests that scale as requirements evolve Start the FREE course now. 👇👇👇 https://lnkd.in/eEWBreVa #SoftwareTesting #QATesting #TestAutomation #AITesting #QualityAssurance #SoftwareQuality #BDD #ATDD #GenAI #DevOps #ContinuousTesting #TestDesign #Keysight #KeysightGenerator #TestGuildCourse #LearnWithTestGuild Keysight Technologies

🤖 From code reviews to CI/CD pipelines, AI agents are transforming how developers work, often in subtle but powerful ways, and changing the rhythm of software delivery. Instead of flashy changes, agents are quietly reshaping workflows by:  - Automating code suggestions & reviews  - Monitoring builds and deployments in CI/CD pipelines.  - Reducing repetitive tasks so devs can focus on higher-value coding  - Offering predictive insights that prevent issues before they surface    The question is: Are we witnessing just another round of workflow optimization, or the beginning of a fundamental shift in software development where human + AI collaboration becomes the new standard?    👉 How are AI agents impacting your workflows right now? #Impero #AI #SoftwareDevelopment #DevOps #Automation

🤖 AI-Assisted Test Generation: Smarter, Faster, Better QA In today’s fast-paced software world, testing can’t slow you down. AI-Assisted Test Generation changes the game: ✅ Automatically generates test cases from requirements or code ✅ Detects edge cases humans might miss ✅ Optimizes regression and performance testing ✅ Speeds up CI/CD pipelines The result? Faster releases, higher quality, and smarter testing. The future of QA isn’t just automated—it’s intelligent. #AI #SoftwareTesting #TestAutomation #QualityAssurance #DevOps #Innovation #ContinuousTesting

Last week, I watched an AI tool perfectly suggest deployment steps — rollback included. It was fast, accurate, and honestly impressive. But as the process unfolded, something hit me… AI can optimize, accelerate, and even predict — …but it still can’t align. It doesn’t step into a last-minute call with Delivery, QA, and SRE to balance risk versus business pressure. It doesn’t rebuild trust after a 2 AM incident. It doesn’t navigate those gray areas where leadership, communication, and context matter more than clean code. AI will continue making us faster and more efficient — no doubt. But delivery still depends on people who can: ✅ See the bigger picture ✅ Communicate across silos ✅ Build trust when things get messy ✅ Make judgment calls when data isn’t enough That human layer — empathy, collaboration, and accountability — remains the hardest part to automate. Curious to hear from you: How is AI changing (or not changing) the way your teams deliver software? Have you seen moments where human judgment made all the difference? #Leadership #SoftwareDelivery #AIDriven #TechLeadership #DevOps #EngineeringCulture