Title: Command Line - By builders, for builders.
Open Graph Title: Command Line
Description: Founded in 2026, Command Line is a technical blog from Microsoft where we share how we build and what we learn—from both our wins and failures
Open Graph Description: Founded in 2026, Command Line is a technical blog from Microsoft where we share how we build and what we learn—from both our wins and failures
Opengraph URL: https://commandline.microsoft.com/
Domain: commandline.microsoft.com
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| Conversation From custom infrastructure to hosted agents What we learned rebuilding Novo’s clinical trials data agent on Microsoft Foundry: a simpler operating model, a stronger session isolation, and a direct path from tracing to evaluation and optimization. 2026.11.11 | https://commandline.microsoft.com/from-custom-infrastructure-to-hosted-agents/ |
| Deep Dive The check that catches agent failures can also train them In our second post on ThinkingBox, we look at expanded model evaluations, the price of dependable runs, and reinforcement learning on terminal-state rewards. 2026.11.06 | https://commandline.microsoft.com/thinkingbox-part-two-expanded-model-evals-reinforcement-learning-rewards/ |
| Deep Dive Nine engineers, 1,211 pull requests in a day: Lessons from building Copilot Cowork Plus a case study where we put everything together by moving our runtime from Python to Rust while live. 2026.11.02 | https://commandline.microsoft.com/how-we-built-copilot-cowork-python-to-rust-migration/ |
| Conversation GitHub Universe 2026: Highlights from the developer’s developer conference The hero at the heart of the two-day event was the developer community. 2026.10.29 | https://commandline.microsoft.com/github-universe-2026-recap/ |
| Conversation Thinking about the evolution of forward-deployed engineers over the last 24 months The rapid pace of AI model development and technology maturity is changing the definition of forward-deployed engineering. 2026.10.28 | https://commandline.microsoft.com/thinking-about-the-evolution-of-forward-deployed-engineers-over-the-last-24-months/ |
| Conversation The new primitives of agentic software delivery This goes beyond code generation. We’re connecting people, AI, and feedback across the software development lifecycle. 2026.10.27 | https://commandline.microsoft.com/new-agentic-software-delivery-primitives/ |
| Conversation Cheap code, precious trust: Code modernization at scale The promise—and challenges—of agentic software engineering, from large-scale code migration to language modernization. 2026.10.26 | https://commandline.microsoft.com/agentic-software-engineering-large-scale-code-migration-language-modernization-spec-driven-development/ |
| Conversation Building a fully autonomous meeting invite capability for Autopilot How the Microsoft-Decision-1 model helped get this across the finish line. 2026.10.23 | https://commandline.microsoft.com/building-a-fully-autonomous-meeting-invite-capability-for-autopilot/ |
| Conversation We can build it. Can we judge it? As agentic AI shortens the path from idea to shipped code, journey evaluation becomes a critical design skill. 2026.10.20 | https://commandline.microsoft.com/mini-foundry-design-journey-evaluation/ |
| Conversation What will the next generation of developers do when AI writes the code? Microsoft and Carnegie Mellon University are betting that the junior developers we train today will be the senior engineers of tomorrow. 2026.10.15 | https://commandline.microsoft.com/praise-preceptor-ai-accelerated-software-engineering-cmu/ |
| Deep Dive Copilot to autopilot: Why no single safeguard is enough We designed a layered model that lets an AI agent resolve production network incidents on its own within defined identity, authorization, tooling, and human-approval boundaries. 2026.10.13 | https://commandline.microsoft.com/ai-agent-copilot-autopilot-layered-model-production-network-incidents-on-call-engineers/ |
| Deep Dive Introducing Microsoft-Decision-1, our model for fast decision-making Our new decision-scoring model delivers top performance in latency and quality on structured decision tasks to outperform both LLMs and other decision models. 2026.10.09 | https://commandline.microsoft.com/microsoft-decision-1-model-foundry/ |
| Deep Dive Bringing local models and sandboxed tools to Windows and GitHub Copilot Coming soon, GitHub Copilot will determine when a task is best handled by on-device intelligence and when it should leverage cloud-scale models. 2026.10.07 | https://commandline.microsoft.com/local-models-sandboxed-tools-github-windows/ |
| Deep Dive Beyond violation rates: Are your AI evaluations measuring the right things? Structured evaluation design can improve both the breadth of behaviors tested and the interpretability of the resulting failures, leading to practical advantages for generating diverse, traceable, and actionable evaluations. 2026.10.05 | https://commandline.microsoft.com/structured-ai-evaluation-design-assert-vs-petri-bloom/ |
| Deep Dive Building an agentic system and a learning loop around customer IP We worked with Kantar to turn 30 years of metrics and frameworks into an agentic system that evaluates and helps optimize ads. 2026.10.05 | https://commandline.microsoft.com/kantar-link-ai-content-optimizer-advertising-learning-loop/ |
| Deep Dive Azure Content Understanding: Building on lessons from a decade of Document Intelligence Trust in document understanding is built one edge case at a time. Here’s what a decade of teaching machines to read taught us about what LLMs can and can’t do. 2026.10.02 | https://commandline.microsoft.com/azure-content-understanding-document-intelligence-perception-grounding-confidence-reasoning-system/ |
| Conversation LLM-as-translator pattern: Adding natural language understanding to an existing system without rewriting it Modernizing an existing implementation can be expensive and disruptive. Instead, consider introducing an abstraction layer to give your legacy system a modern facelift. 2026.09.30 | https://commandline.microsoft.com/llm-as-translator-pattern-natural-language-understanding-conversational-search-existing-system/ |
| Open Source Introducing run-assert-eval: Find the risk, fix it, prove it Today, we’re introducing run-assert-eval, a skill that discovers the risks that matter for a given agent, measures how often the agent fails, generates runtime policy directly from those findings, and reruns the eval to prove whether the fix worked. 2026.09.24 | https://commandline.microsoft.com/run-assert-eval-responsible-ai-agent-risk-discovery-at-runtime/ |
| Open Source PyRIT: Democratizing AI red teaming through open-source tooling Learn how the Python Risk Identification Tool for generative AI evolved over time to open up AI red teaming to subject matter experts from virtually any domain. 2026.09.10 | https://commandline.microsoft.com/pyrit-python-risk-identification-tool-ai-red-teaming-subject-matter-experts/ |
| Conversation Designing product simplicity for the AI era Shared design components aren’t enough to ensure a seamless product experience. Can designers create consistency by embracing simplicity over complexity? 2026.08.31 | https://commandline.microsoft.com/design-product-simplicity-seamless-ux-ui-agentic-ai-azure-developer-services-foundry/ |
| Open Source Your agent’s guardrails have a bypass Agents are moving into production faster than the governance around them. Today’s controls are framework-specific, mostly observe-only, and fail open when they crash. To help address this, we created Agent Hooks: an open, framework-neutral governance contract with conformance testing on both sides. What follows is the contract and the story of proving “deny means deny” inside a real framework core. 2026.08.27 | https://commandline.microsoft.com/agent-hooks-framework-neutral-ai-governance-contract/ |
| Deep Dive One requirement, many failure paths: Evaluate, control, and optimize with ASSERT and ACS A safety requirement might appear simple while the runtime failure surface is complex. ASSERT helps identify coverage bugs; ACS fixes the policy. 2026.08.24 | https://commandline.microsoft.com/safety-requirements-failure-paths-assert-acs/ |
| Deep Dive Stop restricting the agent. Start restricting its environment. Human review improves safety but limits autonomy. Standing credentials preserve autonomy but increase risk. With Azure SRE Agent, we found a safer middle by moving control out of the model and into the runtime around it. 2026.08.21 | https://commandline.microsoft.com/azure-sre-agent-restricting-environment-ai-safety/ |
| Open Source How we built ThinkingBox to measure whether agents finish the job ThinkingBox separates the execution framework from the benchmark package. This split lets builders update the harness and benchmark independently. 2026.08.19 | https://commandline.microsoft.com/thinkingbox-bench-agent-benchmarking/ |
| Conversation Watch TypeScript creator Anders Hejlsberg on The Peterman Pod Following the release of TypeScript 7.0, Hejlsberg joins host Ryan Peterman to discuss the process of porting from JavaScript to Go, the pros and cons of agentic AI for coding, and more. 2026.08.17 | https://commandline.microsoft.com/typescript-7-0-anders-hejlsberg-peterman-pod/ |
| Open Source Who spent all the tokens? Real-time, run-scoped cost control for AI agents Budget caps and gateways can’t stop a runaway AI agent mid-run. TokenOps enforces one shared, run-scoped budget in real time, before the bill arrives. 2026.08.13 | https://commandline.microsoft.com/tokenops-real-time-run-scoped-cost-control-ai-agents/ |
| Experiments 🌿 Agent Terrarium: Bringing AI agents to life An open-source desktop companion app, this weekend project questions whether working with agents should simply feel transactional. 2026.08.07 | https://commandline.microsoft.com/agent-terrarium-rust-human-agent-interaction/ |
| Deep Dive Tool search: Finding the right tool at the right time As you add more tools to AI agents, the advantage comes from making the right tools discoverable at the right moment without paying the full cost of exposing everything upfront. 2026.07.29 | https://commandline.microsoft.com/tool-search-toolboxes-foundry/ |
| Conversation From research to reality: An interview with Microsoft VP of Security Research Taesoo Kim The leader of the new Microsoft Security FORGE (Frontier Offensive Research & Generative Exploitation) Labs, Kim takes us behind the scenes of codename MDASH and explains why a multi-model agentic approach may be the key to winning the security game. 2026.07.27 | https://commandline.microsoft.com/taesoo-kim-interview-mdash-security-research/ |
| Experiments A wind farm you can talk to: Building a real-time 3D digital twin on Microsoft Fabric With geometry, telemetry, and language feeding into a single simulation, it’s the time spent making architectural decisions that matters. 2026.07.13 | https://commandline.microsoft.com/a-wind-farm-you-can-talk-to-building-a-real-time-3d-digital-twin-on-microsoft-fabric/ |
| Experiments How my dev machine built 1,111 word-processing features and forgot to add a ruler What happens when one of the founders of Writely sets up a complex agentic loop and lets it run largely independently in pursuit of an online, collaborative word processor? 2026.07.08 | https://commandline.microsoft.com/dev-machine-foundry-word-processor-agentic-ai-sam-schillace/ |
| Deep Dive Where the agent decides, and where the tools actually run Where does a judgment step go inside an app that already has a deterministic state machine, a tool surface, and a CI pipeline? 2026.06.22 | https://commandline.microsoft.com/langgraph-squad-azure-container-apps-brain-hands-graph-state-architecture/ |
| Deep Dive The durable asset is the loop you own. OpenEnv is its protocol. In the agentic AI era, the real durable asset isn’t the model you rent. It’s the learning loop you own. And OpenEnv is the right protocol for reinforcement learning environments (RLEs). 2026.06.19 | https://commandline.microsoft.com/openenv-protocol-reinforcement-learning-environments-evals-recursive-self-improvement/ |
| Open Source Introducing the Agentic Resource Discovery specification Developed in collaboration with GoDaddy, Google, Hugging Face, and others, this new open specification lets AI clients find resources relevant to a given task automatically. 2026.06.17 | https://commandline.microsoft.com/agentic-resource-discovery-specification-ard/ |
| Deep Dive Information-flow control: Moving toward secure, autonomous agents A deterministic security system, information-flow control (IFC) offers a promising path towards secure and autonomous agents. 2026.06.16 | https://commandline.microsoft.com/information-flow-control-moving-toward-secure-autonomous-agents/ |
| Conversation Watch Satya Nadella on a No Priors x Latent Space crossover special Long-time listener, first-time caller. Dive into a detailed conversation that breaks down the news from Build and what it means for the developer ecosystem. 2026.06.04 | https://commandline.microsoft.com/satya-nadella-no-priors-latent-space-engineering-podcast-build-2026/ |
| Conversation Five ways we’re confusing AI capability and AI reality—and how to bridge the gap Microsoft partnered with Lectures on Tap to present Build on Tap, where CTO Kevin Scott addressed a growing perceptual disconnect in the tech industry. 2026.06.02 | https://commandline.microsoft.com/kevin-scott-build-2026-lectures-on-tap/ |
| Conversation 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. 2026.06.02 | https://commandline.microsoft.com/new-rules-for-builders-agentic-ai-development-jay-parikh-build-2026/ |
| Deep Dive Composing a new platform for agent-first devices New interaction technology enables new types of computers. 2026.06.02 | https://commandline.microsoft.com/project-solara-build-2026/ |
| Conversation Microsoft Scout: From personal project to enterprise-ready personal agent Omar Shahine and Jakob Werner talk shop about building an always-on, enterprise-secure, personal AI agent. 2026.06.02 | https://commandline.microsoft.com/project-lobster-openclaw-personal-ai-assistant-enterprise-secure/ |
| Open Source The agent optimization loop and how we built it in Foundry By reframing the challenge of AI agent optimization, we arrived at a new understanding of what moves the needle and built out a plausible and novel solution. 2026.06.02 | https://commandline.microsoft.com/the-agent-optimization-loop-and-how-we-built-it-in-foundry/ |
| Deep Dive Grounding at scale: Engineering the retrieval system for the agentic web Today at Build, we introduced Web IQ, a new grounding system for the agentic web. 2026.06.02 | https://commandline.microsoft.com/grounding-system-agentic-web-engineering-retrieval/ |
| Open Source Turn specs into evals for any agent with ASSERT Adaptive Spec-driven Scoring for Evaluation and Regression Testing (ASSERT) is an open-source framework for converting natural language behavior requirements into executable evaluations of AI models and agents. 2026.06.02 | https://commandline.microsoft.com/assert-written-intent-executable-evals/ |
| Open Source Introducing Agent Control Specification: Portable runtime governance for AI Agents ACS is an open, vendor-neutral standard that defines how runtime governance is applied across the agent lifecycle, independent of framework, runtime, or policy engine. 2026.06.02 | https://commandline.microsoft.com/agent-control-specification-runtime-governance/ |
| Deep Dive Disposable agents, durable memory: The architecture behind Squad What we learned building Squad: a file-backed, human-led agent team where memory is inspectable, orchestration is explicit, and governance moves from prompts into code. 2026.05.28 | https://commandline.microsoft.com/squad-github-copilot-agent-teams-architecture-durable-memory/ |
| Open Source Inside the Microsoft Agent Framework: How we designed a layered SDK Agent loops, workflows, and harnesses let developers choose the right architecture to support simple assistants and complex multi-agent systems. 2026.05.28 | https://commandline.microsoft.com/agent-framework-layered-sdk-loops-workflows-harnesses/ |
| Deep Dive Introducing Microsoft’s EngThrive framework: Understanding developer productivity in the agentic AI era By looking at Speed, Ease, Quality, and Thriving, EngThrive aims to make it faster and easier for engineers to do great work. 2026.05.28 | https://commandline.microsoft.com/engineering-thrive-engthrive-productivity-measurement-framework-agentic-ai-era/ |
| Conversation How Excel got agentic: An interview with Microsoft Director of Science Mukul Singh We sat down with Microsoft Director of Science Mukul Singh to learn how his team leveraged two years of research to bring agentic capabilities to Excel and beyond. 2026.05.28 | https://commandline.microsoft.com/mukul-singh-excel-agent-mode-copilot-research-into-product/ |
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