Engineering leaders face a constant barrage of questions that pull them away from strategic work. A team lead asks about scorecard compliance. A PM wants a status update on a migration. Someone needs incident trend data for a quarterly review. Each question is reasonable. Each requires context switching, digging through dashboards, or pinging someone on your team for a report.
What if you could just ask?
The Cortex MCP acts as your AI chief of staff, bringing your entire engineering organization's data directly into your chat interface or IDE. Instead of waiting for reports or asking your team to pull data, you get immediate answers to the strategic questions that inform your decisions.
Here are the strategic questions that engineering leaders are already asking, organized by the decisions they inform.
Strategic questions, instant answers
The power of having a chief of staff is that you can ask anything and get a thoughtful response grounded in real data. The Cortex MCP provides that capability, meeting you where you work and turning complex organizational questions into simple queries.
Understanding organizational health
Your job as an engineering leader is to spot patterns before they become problems. These questions help you understand whether your organization is improving or degrading over time.
"Show me MTTR trends over the last quarter. How has it changed?"
Incident response either gets faster or it doesn't. If MTTR is climbing, something in your system has degraded. This gives you the trend line and a clear signal to investigate process or tooling gaps before it becomes a bigger issue.
"Which teams have the most failing Scorecards right now?"
This surfaces which teams are struggling with compliance or buried in technical debt. Instead of waiting for teams to escalate problems, you have a clear view of which teams need support. That visibility lets you have proactive conversations about priorities, staffing, or process changes before compliance gaps become production incidents.
"How has deployment frequency changed over the last six months for the Platform team?"
Deployment frequency serves as a proxy for both velocity and confidence. When you track this over time, you get clear evidence of whether your investments in tooling and process improvements are actually working. If deployment frequency is climbing, teams are shipping faster. If it's flat or declining despite investments, you need to investigate what's slowing them down.
"What should I be worried about in my organization right now?"
Sometimes you need the big picture. This open-ended question lets your AI chief of staff analyze patterns across your organization and surface the most critical concerns, whether that's reliability issues, compliance gaps, or velocity problems.
Proving ROI on AI investments
AI tooling investments demand evidence, not faith. If you're rolling out GitHub Copilot or similar tools across your organization, these questions ground the conversation in metrics that matter.
"How has AI adoption impacted MTTR and deployment frequency over the last quarter?"
This connects AI spending directly to concrete business outcomes by comparing metrics before and after tool adoption. When MTTR drops and deployment frequency climbs after rolling out Copilot, you have hard data to justify continued investment. When the metrics stay flat despite the spend, you know to dig into adoption rates, training gaps, or whether the tool fits your team's workflow."
"Which teams have adopted AI tools, and how does their velocity compare to teams that haven't?"
This reveals whether AI adoption is actually delivering the productivity gains you expected. The comparison between adopters and non-adopters gives you a clear control group to measure impact. If teams using AI tools show meaningfully higher velocity, you have validation to expand the rollout. If there's no significant difference, you need to understand why.
Planning and tracking initiatives
Cross-organizational initiatives are where strategic priorities either gain momentum or stall. Your chief of staff helps you plan, track, and course-correct when needed.
"Help me plan an initiative to improve our production readiness standards."
Your AI chief of staff can help you think through the steps needed to drive change across your organization. It can analyze your current scorecard data, identify the biggest gaps, suggest phased approaches, and help you estimate the scope of work needed.
"Which services are blocking completion of the modernization Initiative?"
When an initiative stalls, you need to know exactly what's holding it up and who needs support. Instead of chasing status updates in Slack, you get a real-time view of progress and blockers.
"Show me the teams that are falling behind on the security compliance Initiative. What's missing?"
This surfaces not just who's behind, but what specific gaps are preventing completion. You can then target your support and resources to the actual blockers rather than guessing where teams need help.
Spotting bottlenecks before they escalate
Velocity problems rarely announce themselves clearly. Teams slow down for reasons that aren't visible from sprint reports. These questions help you see what's actually in the way.
"Where are the biggest bottlenecks slowing down the Checkout team?"
When a team's velocity drops unexpectedly, this surfaces the patterns that sprint metrics miss: services with high incident rates, missing documentation, or blocked Initiatives. You get signal, not speculation, about where to focus your attention.
"Show me services with the highest incident rates in the last month."
High incident rates point to deeper reliability issues. This tells you where to invest in stability before those services become everyone's problem, letting you be proactive rather than reactive about reliability investments.
"What security standards should I be thinking about for my organization?"
Your AI chief of staff can help you think strategically about what matters for your specific context, drawing on Cortex's understanding of your services, teams, and current compliance state to suggest relevant standards and priorities.
Your AI chief of staff gets smarter with every connection
The Cortex MCP becomes more powerful when combined with other Model Context Protocols. Connect your calendar, project management tools, or communication platforms, and your AI chief of staff gains even more context about your organization.
Imagine asking questions like "What should I focus on this week based on my calendar and our current incident trends?" or "Summarize what happened across engineering this month for my board update." As more tools adopt MCP, your chief of staff becomes increasingly capable of connecting disparate information and providing strategic insights.
Meet your organization where you work
The traditional approach to engineering leadership means constantly context-switching between dashboards, Slack channels, and spreadsheets. You ping your team for data. You wait for reports to be built. You spend meetings asking for status updates that could have been answered in seconds.
Your AI chief of staff changes that dynamic. Whether you're working from your IDE, a chat interface, or on the go, you have immediate access to the data that informs your decisions. You can explore hunches, validate assumptions, and get the context you need without pulling your team away from their work.
The questions in this post are just a starting point. The real power comes from having a strategic partner that understands your organization and can help you think through the challenges that matter most. Try asking about what you're actually curious about, and see what insights emerge.
Ready to meet your AI chief of staff? Get started with the Cortex MCP today.
