01
Shared intuition.
Spot gaps and contradictions in source material.
Arula Academy / Learning area 03
AI for business analysis.
Turn documents and data into clear requirements, useful insights, and communication people can act on.
Explore the coursesFor analysts, product owners, and business teams4 courses & practical tracks
Field notes / 03
A question to carry
Turn a plausible conclusion into a supported one.
Follow the evidence from the source to the decision.
From information to understanding.
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.
Express requirements and findings precisely.
03
Everyday habits.
Keep conclusions traceable to their evidence.
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 a task you work with: requirements, documentation, or data. Each track provides a scenario and source material to investigate.
03.01 / Practical learning
Requirements analysis
Turn meeting notes and policy documents into stories, acceptance criteria, and traceable requirements.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot
03.02 / Practical learning
Technical documentation
Extract business rules, create diagrams, and review documentation for completeness.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot
03.03 / Practical learning
301-P · Executable intent
Diagnose what a requirement fails to decide, write criteria that carry their own evidence and hold the product claim to what the evidence supports.
In this track
Explore the course Course 301-P · listed in AI-assisted software engineering
03.04 / Practical learning
Data analysis
Profile, clean, query, and visualize operational data while checking the quality of the results.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot and Python
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
Make sense of the inputs
- 02
Express the finding clearly
- 03
Keep the evidence traceable
Keep exploring
Context engineering.
Give AI the right information. Separate evidence from assumptions, keep context focused, and evaluate what comes back.