Path 01
Understand AI development
Explore ideas with the tools that suit the task. Learn what to check before a prototype gets real data or permissions.
Support exploration and recognize when the responsibilities change.
AI SOFTWARE DEVELOPMENT, UNDERSTOOD
Explore with AI.Build for production.
Help people turn ideas into prototypes. Learn what to verify before connecting company data, granting API access, and running a service.
Find your starting pointOpen to everyone. No sign-up.
SEE THE WHOLE SYSTEM
01Explore ideasPeople · tools · prototypes04Verify the platformData · access · controls05Operate and improveOperate · learn · improve
Room to explore. A clear route to a maintained service.
50 lessons7 learning paths7 interactive labs Languages · 10
MAKE IT RELEVANT
What is your responsibility?
SEVEN CONNECTED LEARNING PATHS
Learn the skills for your next decision.
Complete a learning path in sequence, or select the topic you need.
Path 02
Build with intent
Turn an unclear request into a small, reviewable change. Work with context, tests, code review, and existing systems.
Leave with a repeatable development workflow.
Path 03
Make risk visible
Data boundaries, agent permissions, software supply chains, and evidence that makes governance practical.
Match controls to the consequences of failure.
Path 04
Develop and operate at enterprise scale
Connect prototypes to a secure platform and your infrastructure requirements. Plan compliant delivery, availability, recovery, and ownership.
Define how teams can deliver and operate software with AI.
Path 05
Operate and improve
Maintenance, observability, incident management, SOC and SIRT. Close the loop with bounded self-healing and verified improvement.
Connect service ownership to a complete feedback loop.
Path 06
Choose your operating model
Compare responsibilities, total costs, supplier evidence, and exit options. Make an investment decision you can explain.
Evaluate options against your actual constraints.
Path 07
Put Taiga to work
Eight practical scenarios: start a product, bring existing code, shape work, review evidence, and handle the moments that need you.
Apply the curriculum to real Taiga workflows.
MAKE THE IDEAS TANGIBLE
One decision. Visible consequences.
Trace a change through the SDLC. Compare the costs of different operating models. Practice a code review decision before the real PR arrives.
Practice labCHANGE #042Illustration
Who can export customer data?
IntentOnly an authorized team manager
ControlServer checks the permission
EvidenceNegative authorization test
DecisionOwner reviews the release
A GOOD PLACE TO BEGIN
Your next useful lesson.
Vibe coding: uses and limits
Help people explore ideas with AI. Use a banking prototype to understand why live data and API permissions need security evidence.
Understand AI development
Review AI-generated code
Inspect the actual change, its trust boundaries, and its evidence before you accept it.
Build with intent
Compare responsibilities before products
Compare an assistant, an internal delivery platform, and a software factory. Identify which work each option performs and which responsibilities remain.
Choose your operating model
Good judgment deserves good sources.
Every lesson pairs explanation with practice and source material. We distinguish general engineering principles from Taiga’s own workflows. The choice of tools stays yours.
How we write