Generating code is easy, but building software takes knowledge and processes. While AI is dramatically changing how we build software, context and fundamentals matter – developers need all the guardrails to make Agentic workflows work the right way. There are lots of decision points: - Run AI Models in the cloud or locally - Balancing privacy & cost concerns - Choices in Agentic harness - IDE, Terminal or Browser workflows? - Spec out project details or build ad hoc? - Bridging the gap between Design & code - Prescriptive guidance through Skills - Delegate work with Sub-Agents - Squad of Agents with varying responsibilities - Pitching Agents against each other - Bring grounded context with MCPs - How to validate AI’s work? - Human code reviews or architectural guidance? Let’s have an honest conversation and see real-world AI-powered workflows. Modern development stacks should provide tooling to embrace Agentic workflows, irrespective of where developers are on the AI adoption spectrum. With contextual expertise to light up AI-human loops, the right guardrails can make developers ultra productive with AI – upwards and onwards.