Agentic AI

ASPICE MAN.3 – Project Management: Simple BP-Wise Guide for Delivery Team Audits ASPICE audits can sometimes feel complicated because of the terminology and process language. But MAN.3 – Project Management becomes much easier if we translate each Base Practice (BP) into three simple questions: What should the team do? → What evidence should I see? → What should I ask? This article provides a simple, practical guide that delivery managers, project managers, technical program managers, Agile coaches, and ASPICE auditors can use during an internal audit. Note: Always align the BP numbering and wording with the specific Automotive SPICE version and process model used by your organization. What is ASPICE MAN.3? MAN.3 – Project Management focuses on planning, executing, monitoring, and controlling the project so that project objectives can be achieved. In simple terms: MAN.3 ensures that the project is properly planned, monitored, risks and issues are managed, dependencies are controlled,...

AI Governance: A Comprehensive Guide for Technical Leaders AI governance is one of the most important topics in enterprise AI. While building an AI model is a technical challenge, ensuring it is safe, trustworthy, compliant, ethical, and accountable is a governance challenge. Think of AI governance as the "corporate rulebook" for designing, deploying, and operating AI systems responsibly. What is AI Governance? AI governance is the framework of policies, processes, roles, controls, and technologies that ensure AI systems are developed and used responsibly, ethically, securely, and in compliance with laws and organizational standards. Its goal is to ensure AI systems: Are safe and reliable Respect privacy Produce fair outcomes Are transparent and explainable where appropriate Comply with regulations Include human oversight when needed Deliver business value while minimizing risks Why is AI Governance Important? Imagine an AI-powered loan approval system t...

What Is Agentic AI? A Deep-Dive Explanation Artificial Intelligence is evolving rapidly. The first wave of AI helped automate repetitive tasks. The second wave helped generate content and answer questions. Now we are entering the third wave: Agentic AI Agentic AI represents a shift from systems that respond to prompts to systems that pursue goals and execute tasks autonomously . Instead of acting like assistants, these systems behave like digital teammates . Simple Definition of Agentic AI Agentic AI refers to intelligent systems that can: understand goals plan tasks make decisions use tools collaborate with other agents learn from feedback execute workflows with minimal supervision In short: Traditional AI answers questions Agentic AI completes objectives Why Agentic AI Is Different from Traditional AI Traditional AI systems are reactive. Example: You ask a chatbot to summarize a document → it summarizes once. Agentic AI systems are proactive. Example: You ask an agent to prepare a l...

How to Use This For each Leadership Principle: Prepare 1–2 strong STAR stories Include metrics Show ownership Show technical/program depth Focus on impact 1. CUSTOMER OBSESSION What Amazon Wants Customer-first thinking Long-term customer impact Prioritization based on customer value Questions Asked Tell me about a time you improved customer experience. Describe a customer escalation you handled. Tell me about a time customer feedback changed priorities. Strong TPM Story Themes Production issue affecting users Reducing latency or downtime Improving release quality Faster issue resolution Improving delivery predictability Sample Answer Direction We observed repeated customer complaints around delayed OTA feature availability in connected vehicle releases. I analyzed release bottlenecks and introduced dependency tracking plus automated readiness reviews. This reduced release delays significantly and improved customer satisfaction metrics. 2. OWNERSHIP ...

Most frequently used TPM words -   D riving enterprise agility Stakeholder Alignment Execution Governance Large cross-functional initiative Execution efficiency Innovation speed Creating clarity around goal Establish regular Review Leading Agile Transformation Scaling Agile practicies Business outcomes Trust, credibility and structured communication Consistent follow through Bringing clarity to complex problem Using data efficiently Delivery slippage Unclear ownership Unmanaged dependencies Daily execution Review Risk esclation matrix Re-baseline milestone Leadership alignment session Establising faster decision making channels Business Impact Strategic alignment Customer/business value Time Sensitivity Cross-functional impact Risk exposure Delivery predictability Improve collaboration Reduce release delay Establish scalable execution governance structured program operating model Quartely planning cadence Agile maturity coaching Executive level governance Review Dependency man...

1️⃣ Tell me about a complex cross-functional program you led end-to-end. 🎯 What Adobe is testing: Scale Stakeholder alignment Predictability Business impact ✅ Strong Answer (Structured) Situation: I led execution across 35 Agile teams delivering North America automotive platform releases. Task: The goal was to improve release predictability and reduce cross-team dependency spillover during PI execution. Action: Established dependency mapping 6 weeks before PI start Introduced risk heatmap reviews with engineering and product leaders Standardized Definition of Ready across teams Built a delivery dashboard tracking predictability metrics Result: Improved predictability by 25% Reduced carryover by 30% Achieved on-time delivery of strategic releases Adobe Tie-in: At Adobe scale, I would apply the same governance rigor to cloud platform releases across globally distributed teams. 2️⃣ How do you manage dependencies across multiple engineering teams? 🎯 What Adobe is testing: Systems thinkin...