Generative AI as the force multiplier for software development

1. © 2023 Thoughtworks | Confidential
Generative AI:
The force-multiplier
for SDLC
Kumar Sankara Iyer
Technical Director
kumarsi@thoughtworks.com
Soumya Ranjan Mishra
Lead UI Consultant
soumya.mishra@thoughtworks.com
1

2. © 2023 Thoughtworks | Confidential 2
Generative AI - The force multiplier for SDLC
How will AI co-piloting
change how we build
software?

3. © 2023 Thoughtworks | Confidential 3
What’s your fluency?
Generative AI Fluency
I know ChatGPT
but never used it
I use ChatGPT
occasionally
I utilize ChatGPT
to boost my
productivity at
work.
I also employ
other AI tools for
my creative
endeavors.
I'm engaged in
developing my
own Intellectual
Property utilizing
various AI tools

4. © 2023 Thoughtworks | Confidential
10%
The value of 90% of my skills
just dropped to $0. The
leverage for the remaining
10% went up 1000x. I need to
recalibrate.
4
4
© 2021 Thoughtworks
Kent Beck, design pattern trailblazer, test-driven
development advocate, extreme programming co-
founder.
https://twitter.com/KentBeck/status/1648413998025707520

5. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Foundation models and AI productivity tools
are reshaping how technologists work
AI breakthroughs like ChatGPT and Microsoft Copilot
are transforming the software industry.
AI-driven tools and foundation models enhance
software development across design, requirements,
testing, release, and operations, improving quality
and efficiency.
Product
Design
Requirement
Analysis
Ideation
Prototype
Research
Design
Facilitation
Documentation
Collaboration
Development
Delivery
&
Monitor
Support
Commit
Copilots
Documentation
IDE
CI/CD
Host
Observability
Operations
Research
Marketing
Customer
Support
Open Sourced
Closed Sourced
Foundation
Models

6. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
SDLC, what can be co-piloting with AI?
Analyze Architect Code
Discovery
& Inception
Feature
Design
Backlog
Development
Domain
Modelling
Architecture
Design
API Design
Detailed
Design
Coding Post-code
Customer
Research
Test
Test Case
Design
Test
Automation
Defect
Analysis
Delivery
Support
Deployment
Release
Monitor
AI Co-piloting Use Cases
Product Ideation
Product Definition
Prototype
Feature
Breakdown
UX Design
Non-functional Req
Acceptance
Criteria
Prioritization
Iteration Plan
Release Plan
Milestone Design
Eventstorming
Domain Patterns
Bounded Context
Sequence Diagram
Component Design
Design Patterns
Documentation
API Definition Code Design Code Generation
Unit Test
Generation
Code Review
Commit Comments
Root Cause
Analysis
Defect Analytics
Defect
Documentation
Automation Test
Code Generation
Test Case
Generation
Release Documentation
Update Documentation
Deployment Script Generation
Log Analysis
Customer Support
Customer Sentiment Analysis

7. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Using ChatGPT to run customer research
Prompt
I am interviewing employees of a government institution.
They were recently assigned as product owners of different
products within the organization, but they don’t really
understand what that means.
As part of an enablement project that aims to provide the
institution with the best product owner practices in an agile
context, I am interviewing these new POs to understand the
problem and their level of knowledge.
My user research goals are: Identify their level of
understanding of the Product owner role and Agile practices
. Understand their current role and responsibilities. Learn
about their professional motivations and
interests.Understand their overall sentiment about getting
this new position. Learn about their current availability to
perform the new role
Using the following link as a reference:
https://docs.google.com/document/d/1noNbxsHgeRaKtLL3G
0GmvtFOYFQMbrCSr4G9knhJoBE/edit?usp=sharing
I want you to give me: A detailed synthesis per user aligned
with my research goals. Other interesting findings you think
should called out. One or two textual quotes each of the
users said during the interview that support your synthesis.
And specify where in the interview they said that quote
Identify key themes of data. Identify patterns.
More details
Research Assisted by ChatGPT
ChatGPT can aid researchers in
planning their projects, crafting
effective survey questions, and
designing outreach efforts.
Leveraging prompt engineering, it
can also help conduct interviews
and surveys, and even provide
real-time transcription and
translation services.
But its most significant contribution
might be in data analysis. With its
language processing skills, it can
sift through vast amounts of data
to extract crucial insights quickly,
saving researchers significant time.
This allows researchers to focus
more on interpreting results and
implementing changes. In essence,
ChatGPT can make customer
research more efficient and
impactful.

8. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Articulating product value a LLM tool
Prompt
Help me create a product elevator pitch for a financial planning
app for managing student loan targeting university students. I
want this product to focus on financial education, expense
calculation, monthly personal financial goal achievement, and
social competition or gamification, use the following format
1. For whom...
2. Who expect or are struggled with...
3. Our product provides...
4. That brings value of...
5. Unlike the competitors who ...
6. Our product is different because...
Prompt
Based on the elevator pitch you provided me, write an example
release tweet for young university students

9. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Converting ambiguous business language into software requirements.
Prompt
I'm seeking inspiration to
develop a comprehensive
financial planning app
specifically designed for
university students. The aim
is to provide them with
essential knowledge and
tools for effective personal
finance management,
investing, and saving. The
app should particularly focus
on assisting students in
planning for their student
loans while leveraging
partnerships with prominent
financial service providers to
recommend relevant financial
services tailored to their
needs.
Could you suggest key
features that would make
this app truly valuable for
university students? Please
provide the features in the
format of 'verb-ing whom
to...' and organize them into
groups win markdown.
Feature Brainstorming Using GPT
More Facilitated Requirement
Discussion using online
collaboration tool
Prompt
I want to go
deep into
“Facilitating
access to
student-
friendly
financial
services.” and
provide me a
list of potential
Agile user
stories

10. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Utilizing AI to Enhance Architectural Decision-Making through Domain Model Creation
By using UML tool: http://www.plantuml.com/plantuml/uml/
Prompt
I am designing an OKR system. Based on the following requirements, please
design the domain model according to your understanding and return it
using PlantUML.
As a team leader, I want to be able to create and update long-term and
short-term goals for the team, so that they can be translated into
quantifiable OKRs.
As an employee, I want to be able to create and update my OKRs to align my
goals with the team's and the company's goals.
As a team leader, I want to be able to assign OKRs to each employee and set
deadlines and priorities so I can track the progress of the entire team.
As an employee, I want to be able to update my OKR progress in a timely
manner and report my progress to the team in order to maintain team
transparency and collaboration.
As a team leader, I want to be able to track the progress of each employee's
OKRs and associate it with their performance so that I can assess each
employee's performance.
As a team leader, I want to be able to regularly review the effectiveness of
the OKR system and make necessary adjustments so that I can continuously
improve the effectiveness and value of the entire system.
As a team leader, I want to be able to provide support and guidance to help
employees achieve their OKRs to support the development of the employees
and the success of the team.
As an employee, I want to receive real-time feedback and support so that I
can continuously improve my performance and achieve my OKRs.
Iterative Feedback
Credit: Fengda Wang (Reference)

11. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Coding with LLM through prompt engineering
Prompt
Please use Spring + Java + JDBC to write code based on the following user stories and
API.
// POST /teams/{teamId}/objectives
// ObjectiveDTO: { "name": string, "description": string, "type": string }
// ObjectiveResponse: { "id": string, "name": string, "description": string, "type": string }
User Story: Update OKR Progress
As an employee,
I want to update my OKR progress in the OKR system
So that I can maintain transparency and collaboration within the team and report my
progress to the team.
AC 1: Update progress for a single OKR
Given that I am logged into the OKR system and have an ongoing OKR,
When I input new progress information for an OKR,
Then the system should save and display the updated progress information.
AC 2: Update progress for multiple OKRs at once
Given that I am logged into the OKR system and have multiple ongoing OKRs,
When I input new progress information for multiple OKRs simultaneously,
Then the system should save and display the updated progress information for all
OKRs.
AC 3: Add comments when updating progress
Given that I am logged into the OKR system and have an ongoing OKR,
When I input new progress information for an OKR and add comments,
Then the system should save and display the updated progress information along with
the comments.
AC 4: View OKR update history
Given that I am logged into the OKR system and have an ongoing OKR,
When I view the update history of an OKR,
Then the system should display all update records for that OKR, including update time,
progress, and comments.
AC 5: Error handling for updating progress
Given that I am logged into the OKR system and have an ongoing OKR,
When I input incorrect progress information for an OKR (e.g., negative number or
exceeding 100%),
Then the system should prompt me that the entered progress information is invalid
and ask me to re-enter the correct progress information.
Iterative Feedback
through Prompt
Engineering
Credit: Fengda Wang (Reference)

12. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
Thoughtwork estimated productivity uplifting across SDLC stages
Requirements Analysis Development Testing Deploy
20%
40%
60%
80%
100%
Automation
potential
Use AI to research,
ask question and
document
requirements
Write stories, draw
diagrams, generate
acceptance criteria
etc.
Super auto-complete
for generating code,
identifying risks,
documentation, debug
etc.
Generate test cases
and test code.
Generate test data or
stress data to mimic
real data patterns.
New age deployment
strategies are moving
towards zero touch
deployment.
Generative coding can
help build automation
scripts.
We performed an exercise to do requirement gathering and analysis to see augmentation potential.

13. © 2023 Thoughtworks | Confidential
Prompt Engineering Rule
P.I.A.D.O
13
P
I
A
D
O
Purpose: Identify the broader purpose
and context of the task.
Input: Organize the inputs and
information in a structured manner.
Details: Provide additional details and
specifications as needed.
Output: Suggest the desired output
format or result.
Action: Define a clear and direct action
to be taken.
Credit: Zichuan Xiong

14. © 2023 Thoughtworks | Confidential 14
Generative AI - The force multiplier for SDLC
Showcase Time!!!
The Chain of Thought Instructions & Generated Knowledge

15. © 2023 Thoughtworks | Confidential
Generative AI - The force multiplier for SDLC
The Efficient way to use LLM
Using chain of thoughts and generated knowledge prompting approaches can be a significantly useful tool for programming.
In particular to use LLMs well, we need to learn how to construct prompts to get the best results. This experience suggests
that it's useful to interact with the LLM like a junior partner, starting them with architectural guidelines, asking them to show
their reasoning, and tweaking their outputs as we go.
Key Rule: We should never put anything that may be confidential into the prompt, as that would be a security risk. Business
rules, any code from a real project - all of these must not be entered while interacting with LLM.

16. © 2023 Thoughtworks | Confidential
Thank You!
Kumar Sankara Iyer
Technical Director
kumarsi@thoughtworks.com
Soumya Ranjan Mishra
Lead UI Consultant
soumya.mishra@thoughtworks.com
16
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