Developer Workflows in AI Age - Local or Cloud

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
- 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?
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.