Day 1: Selecting and Designing AI Micro-Apps

Micro-App Use-Case Selection

• Choose narrow repeatable work problems
• Define target users and outcomes
• Estimate value before building
• Reject cases needing complex systems

Inputs Outputs and User Flow

• Specify required user inputs
• Design simple guided interaction steps
• Define acceptable output formats
• Handle missing inputs clearly

Prompt Logic for Micro-Apps

• Separate instructions from user content
• Apply conditional prompt branches
• Use reusable structured prompt blocks
• Prevent uncontrolled prompt expansion

Day 2: Building No-Code AI Logic

No-Code Data Connections

• Connect approved data sources only
• Map fields between simple components
• Validate imported data before use
• Avoid unnecessary sensitive data transfer

Rules Actions and Human Approval

• Define rules for routine outcomes
• Require approval for high-impact actions
• Route exceptions to named owners
• Log decisions for later review

Interface and Experience Design

• Use clear labels for user choices
• Provide instructions at decision points
• Display limitations before submission
• Make correction paths easy

Day 3: Testing and Releasing Micro-Apps

Functional and Quality Testing

• Test expected and unusual inputs
• Compare outputs with acceptance criteria
• Check failure messages and recovery
• Record defects before release

Security Privacy and Access

• Limit access by user role
• Protect credentials and connection secrets
• Avoid storing unnecessary prompt data
• Review third-party service exposure

Micro-App Release and Improvement

• Pilot with representative users
• Collect errors and usability feedback
• Measure value against baseline
• Plan controlled updates after learning

• Case analysis applying Micro-App Use-Case Selection to realistic work
• Hands-on workshop developing No-Code Data Connections with evidence
• Peer review challenging Security Privacy and Access against clear criteria
• Final lab producing Micro-App Release and Improvement for workplace use