• Optimize engineering processes with agentic AI: Diagnose workflow bottlenecks, then implement agentic automation, templates, and “golden paths” that reduce cycle time and deployment time while maintaining reliability. • Team enablement for agentic AI & AI-native development: Coach teams to apply AI-native development using Claude Code or other tools safely and effectively, pairing on real tasks, guiding PRs/diff review, and driving measurable improvements. • Agentic orchestration & decomposition: Design robust multi-agent workflows, including the use of commands, hooks, skills, and model selection for repeatable outcomes. • Assessment & evaluation design: Design skill assessments to diagnose current-state engineering and agentic-AI proficiency, define modular entry points, and measure improvement over time (pre/post assessments, competency rubrics, and program effectiveness metrics). • Claude Code CLI mastery: Operate Claude Code CLI as a daily driver for parallel workstreams and tasks (multi-file refactors, parallel tasks, debugging loops, test creation, and documentation updates). • Agentic hierarchies & context management: Implement scalable agentic tooling hierarchies, context retrieval and context management for long running and complex workflows (retrieval patterns, state handling, summarization, context hygiene) to prevent drift and improve reproducibility. • DevSecOps for agentic engineering: Embed DevSecOps principles and practice into agentic workflows (least privilege, secrets hygiene, dependency/supply-chain awareness, policy-compliant usage, auditability). • Terraform & IaC: Provision and manage cloud infrastructure (AWS/GCP/Azure) using Terraform, enabling secure environments that support agentic development (ephemeral environments, CI runners, permissions). • Software architecture & engineering excellence: Apply strong architecture judgment; guide refactors and implementation patterns suitable for AI-native development; enforce testing and quality standards. • Stay current in agentic software development: Continuously evaluate emerging agentic tooling, model capabilities, and workflow patterns; synthesize learnings into updated playbooks, curriculum, and client recommendations. • Training assets, teaching & knowledge transfer: Create practical training artifacts (labs, playbooks, troubleshooting guides, examples) and deliver instruction through workshops, live training, and office hours so teams can adopt standardized workflows consistently.