Introducing Command Line, and the new rules for builders - Command Line
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Introducing Command Line, and the new rules for builders
Introducing Command Line, and the new rules for builders
Agentic AI is here, and the traditional software development lifecycle is broken. Get ready for what comes next by shifting your workflows and your mindset.
By Jay ParikhEVP of CoreAI, Microsoft
Welcome to Command Line, a new blog where we’ll share what Microsoft builds, how our technical teams operate, and what we learn along the way. Build 2026 felt like the right time to roll this out, as we bring together engineering leaders from around the world to dive deep on building, deploying, and operating scalable AI systems. For those on the ground in San Francisco, you’ll notice that the vibe has shifted along with the locale. And that seems only fitting since the entire SDLC has changed dramatically, too.
To kick things off officially on Command Line, I thought I’d share some of the things we’ve learned about building in the agentic AI era. Things are evolving quickly, and the old rules no longer apply. Manual review processes are breaking under a flood of PRs that our workflows weren’t designed to accommodate. Build time iteration is being met with runtime learning loops as agents improve post-deployment. And the focus is shifting from shipping code to orchestrating systems.
Things are evolving quickly, and the old rules no longer apply.
This is more than a productivity boost. It’s an entirely different relationship with code, tools, and decision-making. Throw out the old playbook. We need to develop a new set of rules for builders.
Here are 10 things that feel important and true today. Time will tell how durable they prove to be. We’re in a time of seismic disruption, so we all need to constantly challenge our assumptions.
1. Build agent-first by default
As you develop your proficiency with AI tools, you’ll probably find yourself reaching for the Copilot CLI in GitHub or agent mode in VS Code more often than not. Many senior engineers on our own teams and across the industry no longer write code by hand, and even small tweaks are made via agents when it’s more efficient.
2. Context and skills are your most important asset
When you first start using an agent in your repo, you’ll notice long sessions with higher failure rates. Start by prompting the agent to populate the knowledge base of Markdown files about your repo, verify the output to ensure correctness, and then set up a continuous improvement agent so that knowledge base memory is updated after each agent session. Things start to compound rapidly.
If you’re doing something repeatedly with an agent, wrap it into a reusable skill and share it. Team skills compound the same way code libraries do. If the same agent failure shows up twice, promote the correction into a reusable skill, test, eval, prompt, or workflow with a clear trigger.
3. Plans are the real work
When you invest in a good plan, the agent can often one-shot the implementation. Shift your energy from typing out code to shaping clear, scoped roadmaps. Human judgment lives in the plan. Execution runs on autopilot.
4. Prototypes replace detailed PRDs
Learning by doing should become the default. Experiment with live demos and prototypes to establish ground truth and guide your decisions before you commit to building. Think demos, not memos.
5. Taste, not time, is the crucial limited resource
When building is cheap, the discipline of deciding what’s worth building becomes more critical, not less. Product judgment and prioritization are the highest-leverage skills on the team. Additionally, with near-zero cost to prototype, deciding what to build now includes seeing concrete options upfront.
6. Tackle the important but overlooked
AI-forward velocity reclaims bandwidth for critical, high-value engineering debt...