01
Shared intuition.
Recognize missing, misleading, or stale context.
Arula Academy / Learning area 02
Context engineering.
Give AI the right information. Separate evidence from assumptions, keep context focused, and evaluate what comes back.
Explore the coursesFor developers and analysts2 courses & practical tracks
Field notes / 02
A question to carry
What does AI need to know before it answers?
Relevant evidence. Clear boundaries. A fresh perspective.
Better context. Better judgment.
01 / What learning should change
The same promise.
Applied to your practice.
Build understanding you can explain, a language you can share, and habits you can use without a prescribed prompt.
02
A common language.
Explain what a task needs and what it excludes.
03
Everyday habits.
Scope each request and verify the response.
The goal is independence. Take these habits into unfamiliar work. The decisions remain yours.
02 / Courses & practical tracks
Choose the work
you want to get better at.
Choose the developer or analyst track. Both explore how context shapes a result through a practical investigation.
02.01 / Practical learning
Context for development
Target relevant context, reuse it, isolate tasks, and match the approach to the work.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot · Developer track
02.02 / Practical learning
Context for analysis
Investigate a reliability scenario, challenge a flawed prior analysis, and build an evidence-backed conclusion.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot · Analyst track
03 / Make it your practice
Carry the learning
into real work.
Use each exercise to develop a way of thinking you can return to when the task, the tools, or the context changes.
- 01
Find the relevant context
- 02
Keep each task focused
- 03
Verify against the source
Keep exploring
AI for business analysis.
Turn documents and data into clear requirements, useful insights, and communication people can act on.