LeadX Leadership Program
Technical Deep Dive for Executives — Build technical depth without coding. Bridge strategy ↔ engineering. Enable better project governance & funding decisions.
10 Weeks
Flexible schedule
No Coding
Concepts & strategy
1-on-1 CTO
Mentorship included
Program Overview
A technical-awareness accelerator for senior leaders designed to bridge the gap between business strategy and engineering execution in the digital-AI era.
Build Technical Depth Without Coding
Master cloud architecture, data systems, AI engineering, and scalability patterns through natural-language learning focused on concepts, strategy, and real-world application.
Enable Better Project Governance
Learn to read architecture diagrams, evaluate technical proposals, translate engineering complexity into ROI models, and make informed funding decisions with confidence.
Inspire Innovation & Product Ideation
Apply technical design thinking to shape new product opportunities. Ideate next-gen data-driven and AI-augmented products with technical feasibility in mind.
Bridge Strategy ↔ Engineering
Engage technical teams with fluency and confidence. Enhance collaboration across business–engineering boundaries and govern projects with architectural literacy.
10
Comprehensive Modules
10
Week Duration
100%
Natural Language
1:1
CTO Mentorship
Curriculum Deep Dive
10 comprehensive modules designed to build technical fluency without coding
Context & Framing
Recalibrate leadership mindset for the digital-AI era
The Cognitive Enterprise: from automation to intelligence
Technology as a strategic advantage
Translating technical literacy into boardroom outcomes
Case: How technical fluency reshaped Amazon, Palantir, and Tesla
Foundations of Modern Engineering
Demystify the core building blocks of today's tech stack
Cloud Fundamentals: elasticity, cost models, regions & availability zones
DevOps & CI/CD: how releases, sprints, and pipelines really work
APIs, Microservices, and Containers: the new architecture of scale
Observability: metrics, logs, and traces for operational control
Data Engineering 101: pipelines, warehouses, lakes, lakehouses
Data & Intelligence
Link data maturity to business strategy
Lifecycle: ingestion → curation → analytics → AI
Vector Databases, Embeddings & Knowledge Graphs (why they matter)
From BI Dashboards to Predictive Systems
AI Stack Overview: LLMs, Fine-Tuning, Agents, RAG
Data Governance, Risk, and Compliance (GRC) implications
Software, Systems & Scalability
Understand how scalable systems are designed and funded
Architectural decisions and trade-offs
Serverless, Edge, and Event-Driven Systems
Cost modeling: CAPEX vs OPEX vs Usage-Based AI costs
Resilience, latency, and throughput—why these drive product reliability
Case: Scaling a SaaS platform on AWS (live walkthrough)
AI Engineering for Leaders
Convert AI hype into actionable product and funding strategy
Anatomy of an AI system: data, model, inference, feedback loop
Foundation vs Domain Models: build vs fine-tune decisions
Agentic AI and Autonomous Workflows
How to fund AI projects—budgeting for experimentation and compute
Case: ROI framework for GenAI and Automation investments
Security, Privacy & Compliance
Equip leaders with technical understanding of digital risk
Identity, Authentication, Authorization (IAM)
Encryption, secrets management, and data privacy
Cloud security and shared responsibility
Compliance frameworks (ISO, SOC2, GDPR, AI Act)
Risk mitigation & budget prioritization
Technical Design Thinking for Product Ideation
Apply technical concepts to shape new product opportunities
Systems Thinking for Product Leaders
Ideating with APIs, Graphs, and Data Flows
From Use Case → Technical Blueprint → MVP
Case Labs: Build a data-driven executive dashboard
Design a small RAG system for internal knowledge
Framework: Tech Feasibility vs Market Viability vs Organizational Readiness
Managing Technical Teams & Vendors
Enhance collaboration across business–engineering boundaries
Reading and challenging architecture diagrams
Understanding velocity metrics and sprint data
Technical KPIs for executive oversight
Partner evaluation: what to look for in vendors and integrators
Budget governance and cost observability
Strategic Foresight & Funding
Equip leaders to plan, evaluate, and sponsor tech initiatives
How to write and read a technical business case
Translating engineering complexity into ROI models
Funding innovation portfolios (core vs horizon projects)
KPI design for innovation funding cycles
Governance checklist for board reporting
The Executive Simulation
Integrate all concepts into one hands-on exercise
Scenario: "Funding an AI-Powered Product Platform"
Teams analyze architecture, cost, compliance, and ROI
Decision presentation to simulated board
Module 10: Future Frontiers
Inspire visionary thinking
Agentic Systems and the Next Decade of Leadership
The Graph-Native Enterprise
AI + OR + Cloud = Cognitive Operations
Building internal innovation cultures