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Learn to examine compiled programs through one interactive lesson per session. Labs and quizzes cover file formats, machine instructions, program behavior, and analysis tools, while recorded observations provide evidence for completing each lesson and resuming later.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learn to read programs you compiled yourself
• Study binary formats and machine instructions
• Check analysis claims against observed output

Build an interactive page that explains a process as a machine viewed from an angle. A tested simulation keeps movement, numbers, and explanations consistent, while controls let readers step through operations and explore failures.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Explain a cache or queue through an interactive machine
• Show what fails when one process step breaks
• Create a standalone visual explanation page

Create static SVG diagrams, scalable images for lessons, READMEs, and manuals. It uses real system names, nine diagram types, and consistent colors and arrows, with checks for readable labels, accessible descriptions, and valid markup.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Add a diagram of system interactions to a README
• Explain state transitions in a manual
• Illustrate data flow from logs or specifications

Apply shared visual and writing rules to course pages, figures, and manuals. Check colors, fonts, labels, layouts, plain technical English, dark themes, keyboard focus, touch targets, and reduced-motion behavior against defined reference values.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Applying consistent colors and fonts to course pages
• Checking dark theme colors and text readability
• Standardizing figure labels and card layouts

Create a substantial technical manual for one exact system version. Organize authoritative sources, record offline inputs and outputs, explain behavior with figures, and audit the text and supporting evidence for consistency.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Documenting a protocol or file format at a fixed version
• Building reproducible offline request and response records
• Adding a section with figures and traceable sources

Create animated lesson diagrams, sliders that update figures, and interactive panels that explain how systems work. It also builds moving dot patterns for page headers, with rules for readability, themes, and reduced motion.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Animate a process in a lesson
• Explore a formula with a slider
• Show a system's behavior through one control

Run a local check of test evidence and retain source paths in the result. The workflow stops when required evidence is missing, keeping the findings tied to their sources.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking local test evidence
• Keeping source paths in check results
• Stopping a check when evidence is missing

Review Orchard deployment manifests, the files describing deployment settings, and keep source paths in the result. The workflow stops when evidence is missing, tying review findings to the available source material.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing Orchard deployment manifests
• Keeping source paths in review results
• Stopping a review when evidence is missing

Learn to create, discover, invoke, secure, evaluate, package, and port Agent Skills through one interactive lesson at a time. Practical checkpoints and quizzes track demonstrated progress in a local file, so later sessions resume where you stopped.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learn to build and invoke a minimal Agent Skill
• Understand discovery and automatic routing
• Check permission, sandbox, and trust boundaries

Study AI engineering through interactive terminal lessons with explanations, coding exercises, and quizzes. The tutor follows your recorded progress, revisits previous material, adapts to your answers, and logs results and topics that need review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Resuming lessons from recorded progress
• Learning concepts through coding exercises
• Checking understanding with lesson quizzes

Review database migration files before merging changes. It gathers evidence about what the changes do, rollback limits, database locks, and risks from large data volumes, then reports blockers when evidence needed for a decision is missing.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review database changes before merging
• Check rollback limits
• Assess database locks and data-volume risks

Review deployment evidence and recovery conditions when assessing a release. The skill directs the agent to consult the accompanying restore reference and include a timestamp in its decision, providing a narrowly defined release review procedure.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing deployment evidence
• Checking recovery conditions for a release
• Preparing a release decision with a timestamp

Publish an approved Orchard release while retaining source paths in the result. The skill requires work to stop when supporting evidence is missing, making evidence availability a condition for proceeding.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Publish an approved Orchard release
• Retain source paths in publication results
• Stop release work when supporting evidence is missing

Review a release proposal by reading its deployment diff and quoting changed replica settings, which describe running instance counts. The review surfaces the specific configuration changes for inspection.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Review a release proposal's deployment diff
• Inspect changes to replica settings
• Quote changed settings in a release review

Evaluate an Agent Skill bundle before release by checking structure, activation conditions, output quality, scripts, safety, file integrity, and host compatibility. Receive a detailed JSON report that distinguishes local evidence checks from production readiness backed by external attestation.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing a skill bundle before distribution
• Evaluating activation accuracy and output improvements
• Checking scripts, safety, and distributed files

Design and test rules for activating skills through human requests, AI selection, applications, or other skills. Check eligibility before matching descriptions, then return a JSON decision showing the selected channel, score, and policy reason.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Separate explicit requests from automatic skill selection
• Test allowed callers and skill composition limits
• Check cases where no skill should activate

Test your understanding of a phase in AI Engineering from Scratch through eight multiple-choice questions. Receive a score, explanations for incorrect answers, and specific lessons to review before continuing your studies.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Checking your understanding after completing a phase
• Assessing readiness for the next phase
• Finding lessons to review from incorrect answers

Study Model Context Protocol (MCP), which connects AI applications with external tools, through guided lessons and exercises. Inspect requests and responses, practice implementation and security checks, and record progress alongside observed results.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learn MCP fundamentals through requests and responses
• Practice building MCP clients and servers
• Study authorization, security, and operational failures

Prepare for four Claude certification tracks through guided lessons, practical exercises, quizzes, and mock exams. The tutor checks understanding and learner-created work, records progress, and uses assessment results to guide review.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Choosing a certification track for a learning goal
• Resuming lessons from saved progress
• Completing guided exercises without writing code

Take a ten-question interactive quiz across five AI and machine learning areas. Use the results to find a starting point in a 523-lesson curriculum, identify topics to review, and estimate the time for your learning path.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Find where to begin studying AI and machine learning
• Skip familiar material in the curriculum
• Identify areas that need review

Build a catalog from multiple skill directories using an explicit priority order. Review duplicate names, selection decisions, and omitted entries before loading the instruction text of the chosen skill.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Cataloging project and user skill directories together
• Checking duplicate skill names before activation
• Reviewing catalog limits and omitted entries

Review proposed file operations, commands, network access, secret handling, or destructive actions against explicit sandbox rules that define permitted activity. Receive a JSON verdict and the exact rule behind it without performing the proposed action.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Reviewing requested file operations before execution
• Checking commands or network access against sandbox rules
• Reviewing actions involving secrets or destructive changes

Find relevant lessons in AI Engineering from Scratch from a topic, question, or bug. Get a short selection of lessons, necessary prerequisites, and the next learning command, with dedicated routes for specialized subjects.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Finding lessons on a topic you want to learn
• Locating lessons that explain a bug's underlying cause
• Choosing what to study next based on your progress

Learn AI engineering by building a project one stage at a time. The tutor guides predictions, learner-written code, automated checks, and reflection, then records progress so the next session can continue from the right stage.

한국어 요약은 준비 중입니다. 영어 요약을 표시하고 있습니다.

• Learn AI engineering through hands-on projects
• Resume a project from the next unfinished stage
• Find coding mistakes with step-by-step hints