Path 04 · 10 lessons · 112 min
Develop and operate at enterprise scale
Connect prototypes to a secure platform and your infrastructure requirements. Plan compliant delivery, availability, recovery, and ownership.
- 01
Connect the complete software lifecycle
Follow one feature from a user need to operation and feedback. Identify the decisions that code generation cannot settle by itself.
- 02
Keep requirements traceable as software changes
Connect a user outcome to decisions, acceptance criteria, implementation, and evidence. Update the connections when assumptions change.
- 03
Platform engineering for AI development
Give people and agents supported ways to create, change, and operate services. Treat the platform as a maintained product.
- 04
Define the infrastructure beyond a prototype
Assess identity, networks, data, recovery, and operation. Connect a generated deployment to the company’s actual infrastructure requirements.
- 05
Design software for a cloud native environment
Connect repeatable infrastructure, replaceable processes, durable state, and observable behavior. Assess cloud native design beyond container packaging.
- 06
Choose availability across zones and regions
Compare high availability, Multi-AZ, and multi-region designs. Trace the complete request path and test the failure each design must withstand.
- 07
Set and test RTO and RPO
Define acceptable interruption and data loss. Compare recovery strategies and measure a complete recovery exercise against business requirements.
- 08
Coordinate AI development across teams
Manage shared contracts, review capacity, and change ownership. Measure the delivery system when many teams generate changes.
- 09
Make a release decision with evidence
Check the version, target, remaining risk, and recovery method. Separate merge, deployment, and user exposure when the system requires it.
- 10
Measure the delivery system
Combine delivery flow, instability, service outcomes, and effort. Use explicit definitions when evaluating AI’s effect.