Ways to use Autopilot speed up software delivery

AI
1

I’m interested in understanding the best ways in which autopilot can be used to speed up software delivery in terms of reducing design & development time, testing time & documentation time

2

Hey @ShreeramK4150

Pega Gen AI Autopilot can significantly accelerate software delivery by reducing effort across design, development, testing, and documentation. Below are some of the most effective ways it can be leveraged:

1. Reducing Design Time

  • AI-driven case design: Autopilot can generate initial case life cycles, stages, and steps based on business requirements or natural language inputs.

  • Suggested data models: It can recommend data objects, fields, and relationships aligned with the use case.

  • UI recommendations: Proposes optimized layouts and components following best practices, reducing manual design decisions.

Impact: Faster transition from requirements to a working design baseline, with reduced dependency on manual modeling.

2. Accelerating Development

  • Reusable component suggestions: Identifies existing assets that can be reused instead of building from scratch.

  • Guided configuration: Provides contextual recommendations while building features, reducing trial-and-error.

Impact: Developers spend less time on trial and error work and spend more time on business-specific logic instead.

3. Improving Testing Efficiency

  • Test case generation: Guides a developer through generating functional test cases based on application flows and scenarios.

  • Data-driven testing support: Suggests relevant test data combinations to improve coverage.

Impact: Faster test creation, better coverage, and reduced regression effort.

4. Enhancing Overall Productivity & Quality

  • Consistent best practices: Ensures alignment with platform standards and guardrails.

  • Faster onboarding: New developers can ramp up quickly with AI guidance.

  • Reduced rework: Early suggestions and validations minimize design and development errors.

Autopilot acts as an intelligent assistant across the development lifecycle, helping teams:

  • Move quickly from requirements to design

  • Reduce manual configuration effort

  • Improve testing speed and coverage

  • Access accurate, up-to-date documentation for any Pega topic

Overall, it enables faster delivery, improved quality, and better developer productivity, especially in low-code environments like Pega. Let me know if this answers your query

Thanks,

Roshan Raj A K

3

1. Reducing Design & Development Time

Autopilot shifts the developer experience from manual assembly to conversational refinement, bridging the gap between business objectives and technical implementation.

  1. Instant Case Type Generation: Instead of building workflows from scratch, you provide a business use case, and Autopilot auto-generates Case Types, Data Models, and Personas.
  2. Conversational Refinement: You can ask the AI to “add a manager approval step” or “create fields for a customer address” directly in App Studio, drastically cutting initial drafting time.
  3. Sample Data Provisioning: Developers can rapidly create sample Data Records using Autopilot. This means you can build and prototype functionality without waiting on backend teams to build integrations or external APIs

Pegasystems Documentation

2. Reducing Testing Time

Testing is often the biggest bottleneck in delivery pipelines, but Autopilot turns this into an automated, AI-driven process.

  • Automated Test Scenarios: The platform automatically generates test cases and refines Gherkin/Cucumber scripts (human-readable, natural language) for case-level and application-level tests.