Level Guides

Understanding and purposefully leveraging AI tools to boost personal and organizational productivity.

Building server-side systems — from basic CRUD APIs to distributed systems at scale.

Understanding core blockchain principles and designing, developing, and deploying smart contracts and decentralized applications.

Designing, deploying, and operating services on cloud infrastructure while optimizing cost and security.

Recognizing digital threats, protecting personal and organizational information, and practicing safe behavior.

Collecting, cleaning, and analyzing data to extract meaningful insights and support decision-making through statistical thinking and visualization.

Designing and operating pipelines that collect, transform, store, and serve data, building the infrastructure that enables data-driven decision-making across organizations.

Reading, understanding, creating, and communicating data, transforming raw numbers and charts into meaningful insights for work and life.

Bridging development and operations to deliver software reliably at speed.

Entering, calculating, analyzing, and visualizing data using spreadsheets.

Building user-facing web applications — from HTML/CSS basics to large-scale frontend architecture and design system leadership.

The engineering discipline of designing, building, and evaluating models that learn patterns from data to solve real-world problems.

Building functional applications, automations, and digital products using visual development platforms without writing traditional code.

Designing digital products end-to-end — from visual design and prototyping to design system management and cross-functional collaboration.

Analyzing problems and translating them into computer-executable instructions.

Crafting and refining instructions for AI language models to produce accurate, relevant, and high-quality outputs across diverse tasks.

Systematically verifying and assuring software quality. Encompasses test design, automation, and process building to prevent defects and ensure product reliability.

Designing user experiences through research, prototyping, and iterative testing.

Systematically understanding users through interviews, surveys, behavior analysis, usability tests, and JTBD frameworks, focused on generating actionable insights that inform product decisions and reduce the risk of building the wrong thing.

Systematically tracking changes in code and documents so multiple people can work at the same time without conflicts.