Foundation Checklist
An interactive engineering management roadmap & readiness tool. Track your progress while gaining deep domain understanding across People, Product, and Process.
Leadership Readiness Progress
Your progress is saved automatically in local storage.
How it works
Check the box on any card or inside its modal to mark it complete. Click "View Details" to open deep topic insights.
Engineering Leadership & AI Governance Diagnostic
Benchmark your organization across People Leadership, AI Upskilling & Architecture, and Responsible Governance. Receive an instant Archetype Scorecard and curated checklist priorities.
Frame system architecture trade-offs using ADRs. Balance rapid AI integration and speed to market with long-term security, ethical data governance, and operational scale.
Manage technical debt as an explicit risk portfolio. Maintain dedicated capacity (15-20%) for architectural refactoring and modernization.
Establish automated quality gates, AI-assisted development guardrails, shift-left security checks, and robust CI/CD pipelines to ensure repeatable, resilient releases.
Conduct weekly psychological-safety-first 1-on-1s. Use Situation-Behavior-Impact (SBI) to deliver timely, actionable feedback.
Define clear IC vs Management tracks, design Individual Development Plans (IDPs), and nurture top-tier engineering talent retention.
Build fair, objective hiring rubrics and structure cross-functional stream-aligned teams to minimize cognitive overload.
Translate executive strategy into realistic milestones, clear critical-path sequencing, and transparent delivery forecasts.
Maintain RAID logs, facilitate SAFe Program Increment (PI) planning, and aggressively unblock cross-team dependencies.
Run blameless postmortems using the 5 Whys. Convert outages into automated remediation tasks and error budget policies.
Connect daily pull requests to enterprise OKRs. Ensure engineers understand the customer problem and product vision.
Rigorously evaluate core vs context capabilities, Total Cost of Ownership (TCO), vendor lock-in risks, and time-to-market.
Map end-to-end software delivery flows. Eliminate waiting times, handoff friction, and process bottlenecks using Lean principles.
Measure Deployment Frequency, Lead Time, Change Failure Rate, and MTTR to drive systematic delivery improvements.
Track developer sentiment, eNPS, overtime trends, and context-switching load to prevent burnout and maintain sustainable velocity.
Pair system performance (latency, error rates) with user conversion, feature adoption, and responsible AI model cost efficiency.
Practice "What you don't change, you choose." Foster extreme accountability alongside psychological safety and empathy.
Guide team members with structured probing questions instead of dictating solutions. Build independent problem-solving agency.
Champion cross-team domain guilds (AI Upskilling & Governance, Frontend, Agile Leadership) to eliminate knowledge silos and establish best practices.