Founder & Architect
The big-picture path — system design, databases, distributed systems, and production engineering for technical leaders.
Programming Fundamentals
Enough programming fluency to evaluate technical decisions.
Understanding how programs store and manage data
How programs make decisions and repeat actions
Organizing code into reusable, composable units
Ordered collections of data and how to work with them
Key-value data structures for modeling real-world entities
Handling operations that take time: callbacks, promises, and async/await
Catching and recovering from errors gracefully
System Design
Architecture patterns, scaling strategies, and cost modeling.
The fundamental pattern of modern networked applications
Separating concerns into presentation, business logic, and data layers
Choosing between a single deployable unit and many small services
Storing computed results to avoid expensive recomputation
Growing your system by adding machines or upgrading existing ones
A single entry point that routes, authenticates, and rate-limits API requests
Understanding system behavior through logs, metrics, and traces
Estimating infrastructure costs and making efficient architecture decisions
Databases
Data storage decisions that shape your entire architecture.
Organizing data into tables with rows and columns
Primary keys, foreign keys, and relationships between tables
Speeding up queries with B-tree and hash indexes
Ensuring data consistency with atomic operations
How databases optimize and execute your queries
Using caches to reduce database load and improve response times
Copying data across multiple servers for reliability and performance
Distributed Systems
The hard problems of building systems at scale.
Understanding the fundamental tradeoffs in distributed system design
Understanding consistency models and how distributed systems converge
How distributed systems copy data across nodes for reliability and performance
How distributed systems choose a single coordinator node
How distributed nodes agree on a single value despite failures
Designing operations that are safe to retry without side effects
Handling transient failures with smart retry strategies
Decoupling services with asynchronous message passing
Preventing cascade failures by failing fast when services are down
Controlling request volume to protect services from overload
Production Engineering
Shipping and operating software — the founder's operational playbook.
Automated testing on every push and automated releases to production
Packaging applications into portable containers that run anywhere
Running code without managing servers using functions as a service
Understanding what your application is doing in production through logs, metrics, and traces
Safely reverting bad deployments and responding to production incidents
Defining reliability targets and learning from failures through blameless postmortems