01
Shared intuition.
Distinguish a passing test from sufficient confidence.
Arula Academy / Learning area 04
AI-assisted software engineering.
Understand, test, improve, and secure software. Keep intent clear and engineering decisions grounded in evidence.
Explore the coursesFor engineers and engineering teams7 courses & practical tracks
Field notes / 04
A question to carry
The tests pass. What have you actually proved?
Clear intent. Bounded changes. Independent review.
Build with evidence.
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.
Make scope, acceptance criteria, and ownership explicit.
03
Everyday habits.
Review independently and retain evidence of decisions.
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.
Bring experience reading and working with code. Choose a focused testing or security track, or explore structured delivery and multi-repository practice.
04.01 / Practical learning
Test optimization
Find coverage gaps, strengthen tests, and establish meaningful quality gates.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot · Java and Angular tracks
04.02 / Practical learning
Secure software development
Identify vulnerabilities, assess threats, and validate secure implementations.
In this track
View course materials Course guide & exercises on GitHubGitHub Copilot · Java and Angular tracks
04.03 / Practical learning
AI-DLC in practice
Explore a structured delivery path from shared intent to reviewed work and retained learning.
In this track
Explore the course Arula Workbench
04.04 / Practical learning
301 · Tooled judgment
Diagnose the diff, review named risks, eval the evidence gaps, define defect specs, plan, run and repeat on the new implementation diff.
In this track
Explore the course Course 301 · payments validation fixture
04.05 / Practical learning
301-P · Executable intent
Write specifications that can be built, evaluated and signed. The product track, paired with 301 on the same payments fixture.
In this track
Explore the course Course 301-P · payments validation fixture
04.06 / Practical learning
501 · Ways of working
Operate the AI-DLC process on a real engagement: name the accountability, set the gates, route the conversation to a record and close the loop with a signed verdict.
In this track
Explore the course Course 501 · Meridian engagement
04.07 / Practical learning
Meridian Engineering: Trust the Balance
Use a cross-stack consistency problem in JHipster’s public banking sample to derive context, write and audit specifications, execute a bounded change and review code against evidence.
In this track
Explore the shipping-case lab Lab 3 · JHipster · Java and React
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
Understand the change
- 02
Build and test deliberately
- 03
Review the evidence
Keep exploring
Building AI agents.
Build agents that use tools, coordinate tasks, critique their work, and improve through deliberate evaluation.