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Agility and
Generative AI
Friends or foes?
30 Settembre 2023 Torino
Emiliano Soldi
@AgileTriathlete
https://www.EmilianoSoldi.it
https://www.linkedin.com/in/emilianosoldi/
Performance
Time
Foreign Element
Transforming Idea
Late Status Quo
Resistance
Chaos
Integration
New Status Quo
Source: The Satir Change Mode
Virginia Satir (1916-1988)
was an acclaimed American
author and therapist who
pioneered family therapy.
She developed the Satir
Change Model, a five-stage
process to guide constructive
personal and organizational
change, aiming to normalize
the turbulence of change
and allow growth through
a natural process of
destabilization, confusion
and realignment.
How many of these
great moments
did we have?
Then, all stopped in a matter of days…
Virtual Stand-ups
Teams used video conferencing
to hold daily stand-ups.
Members discussed work done,
obstacles, and plans. Coaches
pushed concise communication
for efficient virtual stand-ups
Focus on Individual
Coaches promoted open
communication and
frequent one-on-one
check-ins. They created
virtual spaces for social
conversations, building
camaraderie
Flexible Hours
Coaches enabled teams to
set core collaboration hours
but work flexibly to
accommodate personal
needs and time zones
Virtual Pair/Mob
Programming
Teams used screen sharing to
enable remote pair and mob
programming. Coaches facilitated
role rotation, equal participation,
and real-time code editing
Re-prioritize Value
Coaches worked with POs
to reprioritize based on
changing needs. They
guided teams to focus on
delivering immediate value,
adapting the backlog as
circumstances evolved
“Definition of Done”
Coaches helped teams adapt
the definition of "done" for
remote work. They
encouraged considering
virtual testing and
collaboration in acceptance
criteria
…yet, we adapted
Virtual walls didn't stop standups
Coaching happened through chat,
collaboration via remote tools, new
rituals were created
Human connections remained healthy
How was it possible?
Video conferencing, screen sharing, digital whiteboards
and team chat tools
TOOLS
Soft and behavioral competences have been improved:
communication, active listening, empathy
SKILLS
People focused more on results vs presence, seeing that being
remote did not hamper productivity or quality
VALUE
Management have been forced to empower distributed
teams without micromanaging
MINDSET
Organizations invested more on building trust and
connections among remote people
TRUST
Diversity was 1st priority in hiring the best talents, regardless
of place; co-location was no longer a constraint
HETEROGENEOUSNESS
Knowledge
Technology
Culture
And…we definitely realized that agility
isn't a place, but a mindset
Our very principles stood firm
despite disrupted plans
…and, even in isolation,
we delivered value
Technology has been the Enabler
And, what’s
happening
today?
We are at the inflection point
of a big breakthrough
…which is, hopefully,
less “traumatic” but still
impactful on people and
companies’ lives
Unlike Corona, it builds
quietly yet profoundly
beneath the surface,
promising seismic change
to businesses
Are you ready to enter the era
of Generative AI Co-Piloting?
Source: Accenture Research based on analysis of Occupational Information
Network (O*NET), US Dept. of Labor; US Bureau of Labor Statistics.
Potential AI impacts
on work distribution
of all working hours that
account for language
tasks
62%
can be transformed into
more productive activity
through GenAI
65%
of total working hours
could probably be
impacted by GenAI
40%
Work
time
distribution
by
major
occupation
Early AI adopters see 2-3 pts yearly labor
productivity gains, indicating generative AI
meaningfully boost productivity
Workers impacted by partial AI automation
will likely redirect some of their freed capacity
to boost productive output
Workers displaced by AI will likely find new jobs
in occupations arising from AI or enabled by
demand stimulated by related productivity gains
These
phenomena
have
plenty
of
historical
precedent
Economist David Autor studied that 60% of workers today
are employed in jobs not existing in 1940, implying that
over 85% of employment growth happened since then,
is explained by technology-driven advancements
Goldman Sachs ! Economic Research -The Potentially Large Effects
of Artificial Intelligence on Economic Growth (Briggs/Kodnani)
Generative AI – A public Case Study
CONTEXT RESULTS INSIGHTS
➢ Empirical evaluation of the impact of
Generative AI on low and high skilled
customer care agents within a
Fortune 500 enterprise software
company specialized in business
process software for small and
medium-sized businesses in the
United States
➢ Research that studied a step-wise
introduction of a generative AI-based
conversational assistant in a customer
care center, analyzing data from more
than 5000 customer support agents
in answering and engaging with their
customers
Generative AI applied in that context,
brought positive impacts empirically
measured on worker productivity, customer
sentiment and overall employee retention
Average increase of worker productivity
by 14%, due to their augmented capacity
in retrieving and analyzing relevant data
and resolution advices in past tickets
New hired people were able to acquire,
and use, in 2 months the same quantity of
knowledge that other employees got in 6
months without the assistance of GenAI
Source: “Generative
AI at Work”, Erik
Brynjolfsson, Danielle Li
& Lindsey R. Raymond
- National Bureau of
Economic Research
More experienced, highly
skilled customer support
agents saw little or no benefit
from using it
Less experienced, lower-skilled
customer service agents saw big
gains in their job performance
AI chatbot is basically
mimicking company's top
performers, therefore levelling
newbies and low performers’
knowledge to high-skilled ones
Additional Source: This company adopted AI. Here's what happened to its human workers
Tacit Knowledge
Tacit or implicit knowledge —
as opposed to formal, codified
or explicit one—is knowledge
that is difficult to express or
extract, and thus more
difficult to transfer to others
by means of writing it down or
verbalizing it. This can include
personal wisdom, experience,
insight, and intuition
- Wikipedia -
Prompt Engineering – Some Patterns
Persona
Acting
Act as Persona X
Act as a nutritionist,
I am going to tell you
what I am eating, and
you will tell me about
my eating choices,
indicating main
attributes and if there
are healthy
alternatives
Assume
Audience
Assume that
I am Persona Y
Assume that I am a
10 years old child
that knows anything
about Informatics and
Computers.
Explain large
language models and
Chatbot
to me
Question
Refinemen
t
Better version
of the Question
From now on,
whenever I ask a
question, suggest a
better version of the
question to use
instead
(Optional) Prompt me
if I would like to use
the better version
instead
Flipped
Interaction
I would like you to ask
me questions to
achieve X
You should ask
questions until
condition Y is met or
to achieve this goal
Ask questions to help me
diagnose a problem with
my Internet
Ask questions till you
have enough information
to identify the two most
likely causes. Ask one
question at a time
Prompt engineering is
crafting prompts that produce
better LLM responses. Key
techniques include:
✓ Providing necessary
context and background
✓ Framing the question
clearly and directly
✓ Guiding with examples
and constraints
Carefully engineered,
prompts, steer the LLM to
generate useful outputs
EXAMPLE
Why all this matters
Agile practitioners?
What reported from now on, needs to be intended
as a first exploration on how LLMs and related bots,
can be used for possibly improve how to help people
in embracing Agile principles and learn
how to apply its ways of working
For no reasons at all this must be intended
as a substitution of Agile roles, any Agile core activities,
nor avoiding or delegating any related responsibilities
Disclaimer
• Generative AI in certain
circumstances can produce
hallucinations by filling in blanks
with inaccurate information
• Due to data they have been
trained with, LLMs’ responses can
contain bias (e.g., age, gender,
cultural, racial, etc.)
• Outdated training datasets lead to
LLMs not having current, real-
world knowledge, which can cause
reliability and accuracy problems
• Large language models can
potentially generate content that
violates copyright laws (e.g.,
trademark infringement, rights
violations, etc.)
• Generative AI could expose user
proprietary and confidential data
due to possible limited protections
of some providers
Work in Progress
Have you ever been told
that you don’t know “their business”
or are too theoretical?
Today you can
drastically accelerate specific
domain knowledge growth…
Do you need an assistant who,
invited to your Scrum Events,
listens, elaborates, collects key
topics and decisions,
sends summaries over slack
and opens tickets in Jira?
Having SMs finally doing their Job and not secretariat?
Source: Spinach.io
What about Generalizing-Specialist? T-Shaped people?
How many of them did you meet since now?
>> Team members who possess a wide range of skills and expertise while also specializing in a particular area <<
Rapid upskilling: Generative AI
quickly provides customized
explanations on new topics,
enabling just-in-time learning
Personalized training: LLMs
generate tailored content
and recommendations based
on individual needs and
learning styles
Interactive learning: LLM
Chatbots allow interactive
Q&A to deepen topics
and aid learning
Reduced dependency: AI
provides on-demand
information, reducing reliance
on training sessions or experts
Cost and time savings:
Automated training content is
more efficient than conventional
programs
Targeted coaching: AI provides
personalized coaching advice,
sample dialogues, and practice
scenarios tailored to specific skill
gaps
How
GenIA
Can
Help?
Product Owner Persona
A Steep Learning Curve
When I first started as a Product Owner, I felt
overwhelmed. I struggled to elicit requirements,
write coherent user stories, prioritize the backlog,
and provide clear specifications
It was a seemingly impossible balancing act
LLM chatbots can generate interactive simulations to help product owners
explore requirements scenarios and uncover potential problems early
POs can setup an agile requirements simulator based on LLM chatbot
o submit user stories and then test them by to validating completeness,
consistency, and testability
The simulator could also help POs prioritize and estimate user stories
to create realistic sprint plans and manage stakeholder expectations https://www.emilianosoldi.it/enhance-coaching-
agile-requirements-simulator-with-chatgpt/
The Agile Requirements Simulator
Act as a Requirement Simulator.
I will insert acceptance criteria (AC:) or user
stories (US:). Use the requirements to guide
your behavior.
Then, I will insert scenarios and you will tell
me if that is possible given the scenarios and
in case it is not possible write the missing
requirement needed in the format of a user
story.
Add this US: As a new user I want to insert
valid user name and password, presses
confirm, to acquire the status Registered User
AC: Users need to register to set a
username and password;
AC: Password must be 8 characters in
length and has to contain 1 capital letter
and one number
This user story is too big and not fine grained.
Decompose it and create as many user stories
to let them fine-grained and auto-consistent
Please provide how the new user registration
form shall look like
Let’s simulate the use of the system.
I am a new user and I insert as User Name
‘john’ and as password ‘smith’
Now, create a formatted CSV list, compliant
with Atlassian Jira, of the inserted user stories
1) SETUP 2) POPULATE 3) USE
EXAMPLE
Are you familiar with the Business Model Canvas?
Yes, I'm familiar with the Business Model Canvas. It's a
strategic tool used for developing and describing
business models. If you have any questions about it or
need assistance related to it, feel free to ask
From now on you are an expert product manager of a
logistic company and you need to convince your boss that
a new app that manages the selection of the packaging
material for the material to be shipped in according to
their weight and typology and client necessities, by using
recycled material, can be very useful. Compile the
Business Model Canvas for me and arrange it in a table
Sure, I'd be happy to help you create
a Business Model Canvas for your
new app idea
Now create the Vision Board Canvas from Pichler
I understand you're looking for a Vision Board
Canvas following Roman Pichler's framework.
However, I'd like to clarify that Pichler's
Vision Board is typically used in Agile
product development to define the vision
and goals of a product. Since you've asked me
to act as an expert product manager in a
logistic company, I'll tailor the Vision Board
Canvas to that context
Always from Pichler's framework develop
the 2 main User Personas
Certainly, let's create two user
personas following Roman
Pichler's framework
In the footsteps of A. Osterwalder and R. Pichler EXAMPLE
Agile Coach
Persona
Navigating
Uncharted Waters
In my 10+ years of agile
coaching, I've faced many
unknowns: new domains,
skeptical executives,
transforming mindsets;
It can feel like navigating
uncharted waters
In these moments, I wish
I had a trusted advisor to
quickly provide insights
tailored to the situation
The Agile Coaching Personal Assistant
From now on you are an expert Agile Coach with dozen
of years of experience. You worked in every industries
and know somehow all the existing Agile Frameworks.
Understood. How can I assist you with your agile coaching and
consulting needs? Feel free to ask any questions or discuss any
challenges you're facing in your professional journey.
I am a client who wants to use agile for the development of a new
app. I am new to Agile; I have read some articles and participated
to some webinar about scrum and how to work with it. I need to
launch a new team and I want to use Agile and Scrum as a
framework. As an Agile coach expert provide a complete sequence
of steps for launching this team in the best way possible to have it
immediately ready to start work on the app by using agile. Fill in
any missing steps.
Absolutely, I'd be glad to guide you through the process
of launching your new Agile team for app development. Here's a
complete sequence of steps:
Initial Meeting and Orientation: ...
Product Vision and Backlog Creation: ...
Communication and Expectations: ...
User Story Refinement: ...
Definition of Done (DoD): ...
Sprint Planning Preparation: ...
Physical Setup: ...
I am currently facilitating a Business Agility transformation within
a bank. I am covering the role of Business Agility Lead and
responsible for the whole transformation program. One important
responsibility of mine is to coach the company's executives to help
them thoroughly embrace the agile mindset and be active sponsors
of the transformation, moreover of the ones where agile is
brought. Did you get it? Reply just yes or no
Yes.
Now, one of the executives (the one responsible for the retail
area), has a traditional mindset, very much directive, is not aligned
with the board and do not support the transformation.
I would like you to ask me questions to help me create a plan, with
concrete actions and observations, for coaching him and make him
positive and supportive about the transformation.
You should ask questions until you have sufficient information
about the situation, the context, his approach and what you
consider important to convert his negative approach. Ask me the
first question.
Of course. To better understand the situation, could you
provide some insights into the specific challenges or concerns
that this executive might have expressed regarding the
Business Agility transformation? Additionally, do you have
any information about his current understanding of agile
practices and how they might relate to the retail area?
AGILE CONSULTING AGILE MENTORSHIP
EXAMPLE
25
FUNNEL
Identify / Collect
new ideas
REVIEW
Pre-qualify
Initiatives
ANALYZE
Lightweight
Exploration
Waiting for
Implementation
BACKLOG
IDENTIFY AND QUALIFY PRIORITIZE EXECUTE AND MEASURE
Initiatives
Implementation
No longer
Portfolio concern
IMPLEMENTING DONE
Business
Requirements
Technology
Enablers
Idea
Statement
Epic
Statement
Lean Biz
Case
Prioritized Prioritized Prioritized
Copyright © 2023 Accenture. All rights reserved.
Sustainability
Needs
Source: adapted from SAFe – Scaled Agile Framework
Feed, Validate and Boost Value in Portfolio Funnel
✓ Ideas
Generation
✓ Market analysis
✓ Competition
analysis
✓ Idea validation
✓ Ideas aggregation
or discarding
✓ Benefits validation
✓ Assumption
validation
✓ Cost analysis
✓ Make or buy
analysis
✓ Cost of Delay
prioritization
✓ Biz case
consistency
✓ Benefits validation
✓ Assumption
validation
✓ Cost analysis
✓ Risk analysis
✓ Roadmap
validation
✓ Cost of Delay
prioritization
MVP - MMP
Continue?
Stop
No but
Pivot Not at all
Yes and
Persevere
✓ Users feedback analysis
✓ Market analysis
✓ Competition analysis
✓ Progress validation
✓ Roadmap consistency
✓ Quality review
✓ Cost analysis
✓ ROI validation
✓ Market analysis
✓ Competition analysis
✓ Cost of Delay
prioritization
Generative AI Analysis and Decision Making Assistance
The Pitfall of
Overreliance
Advanced GenAI tools available to
Agile Teams for generating code,
content, and backlogs can lead to less
human creativity, collaboration, focus
Agile teams must remain vigilant
to prevent the diminishing
of human interactions
GenAI purpose should augment
human capabilities not limit them
Decreased
Synced,
Face-to-face
Communication
Heavy
dependency
on AI expertise
As GenAI will become more
and more embedded in
organizations processes and
habits, developing related AI
systems will require specific,
expertise in AI technologies
Scarce AI expertise could
create bottlenecks and over-
reliance on just a few people,
limiting autonomy and
decision-making of other
team members
Large Language Models bring
tremendous productivity
benefits, although raise urgent
climate questions
SOLUTIONS EXISTS
✓ Cloud migration cuts
emissions
✓ Green cloud providers cut
them further
✓ Green software boosts
efficiency and lower energy
consumption
✓ Carbon metrics enable
accountability
LLMs have overwhelming
potential to transform industries
for the better
However, only with a focus on
sustainability we can overcome
the carbon conundrum
No matter what changes, innovations,
or disruptions occur; strong values,
human compassion, and advanced technology
let Agile to endure and thrive
SOURCES:
• Accenture-A-New-Era-of-Generative-AI-for-Everyone
• Wikipedia
• Goldman Sachs ! Economic Research -The Potentially Large
Effects of Artificial Intelligence on Economic Growth
• What if AI could rebuild the middle class?
• A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT
Thank you!
Emiliano Soldi
@AgileTriathlete
https://www.EmilianoSoldi.it
https://www.linkedin.com/in/emilianosoldi/

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Agile and Generative AI - friends or foe?

  • 1. Agility and Generative AI Friends or foes? 30 Settembre 2023 Torino Emiliano Soldi @AgileTriathlete https://www.EmilianoSoldi.it https://www.linkedin.com/in/emilianosoldi/
  • 2. Performance Time Foreign Element Transforming Idea Late Status Quo Resistance Chaos Integration New Status Quo Source: The Satir Change Mode Virginia Satir (1916-1988) was an acclaimed American author and therapist who pioneered family therapy. She developed the Satir Change Model, a five-stage process to guide constructive personal and organizational change, aiming to normalize the turbulence of change and allow growth through a natural process of destabilization, confusion and realignment.
  • 3. How many of these great moments did we have?
  • 4. Then, all stopped in a matter of days…
  • 5. Virtual Stand-ups Teams used video conferencing to hold daily stand-ups. Members discussed work done, obstacles, and plans. Coaches pushed concise communication for efficient virtual stand-ups Focus on Individual Coaches promoted open communication and frequent one-on-one check-ins. They created virtual spaces for social conversations, building camaraderie Flexible Hours Coaches enabled teams to set core collaboration hours but work flexibly to accommodate personal needs and time zones Virtual Pair/Mob Programming Teams used screen sharing to enable remote pair and mob programming. Coaches facilitated role rotation, equal participation, and real-time code editing Re-prioritize Value Coaches worked with POs to reprioritize based on changing needs. They guided teams to focus on delivering immediate value, adapting the backlog as circumstances evolved “Definition of Done” Coaches helped teams adapt the definition of "done" for remote work. They encouraged considering virtual testing and collaboration in acceptance criteria …yet, we adapted Virtual walls didn't stop standups Coaching happened through chat, collaboration via remote tools, new rituals were created Human connections remained healthy
  • 6. How was it possible? Video conferencing, screen sharing, digital whiteboards and team chat tools TOOLS Soft and behavioral competences have been improved: communication, active listening, empathy SKILLS People focused more on results vs presence, seeing that being remote did not hamper productivity or quality VALUE Management have been forced to empower distributed teams without micromanaging MINDSET Organizations invested more on building trust and connections among remote people TRUST Diversity was 1st priority in hiring the best talents, regardless of place; co-location was no longer a constraint HETEROGENEOUSNESS Knowledge Technology Culture
  • 7. And…we definitely realized that agility isn't a place, but a mindset Our very principles stood firm despite disrupted plans …and, even in isolation, we delivered value Technology has been the Enabler
  • 8. And, what’s happening today? We are at the inflection point of a big breakthrough …which is, hopefully, less “traumatic” but still impactful on people and companies’ lives Unlike Corona, it builds quietly yet profoundly beneath the surface, promising seismic change to businesses
  • 9. Are you ready to enter the era of Generative AI Co-Piloting?
  • 10. Source: Accenture Research based on analysis of Occupational Information Network (O*NET), US Dept. of Labor; US Bureau of Labor Statistics. Potential AI impacts on work distribution of all working hours that account for language tasks 62% can be transformed into more productive activity through GenAI 65% of total working hours could probably be impacted by GenAI 40% Work time distribution by major occupation
  • 11. Early AI adopters see 2-3 pts yearly labor productivity gains, indicating generative AI meaningfully boost productivity Workers impacted by partial AI automation will likely redirect some of their freed capacity to boost productive output Workers displaced by AI will likely find new jobs in occupations arising from AI or enabled by demand stimulated by related productivity gains These phenomena have plenty of historical precedent Economist David Autor studied that 60% of workers today are employed in jobs not existing in 1940, implying that over 85% of employment growth happened since then, is explained by technology-driven advancements Goldman Sachs ! Economic Research -The Potentially Large Effects of Artificial Intelligence on Economic Growth (Briggs/Kodnani)
  • 12. Generative AI – A public Case Study CONTEXT RESULTS INSIGHTS ➢ Empirical evaluation of the impact of Generative AI on low and high skilled customer care agents within a Fortune 500 enterprise software company specialized in business process software for small and medium-sized businesses in the United States ➢ Research that studied a step-wise introduction of a generative AI-based conversational assistant in a customer care center, analyzing data from more than 5000 customer support agents in answering and engaging with their customers Generative AI applied in that context, brought positive impacts empirically measured on worker productivity, customer sentiment and overall employee retention Average increase of worker productivity by 14%, due to their augmented capacity in retrieving and analyzing relevant data and resolution advices in past tickets New hired people were able to acquire, and use, in 2 months the same quantity of knowledge that other employees got in 6 months without the assistance of GenAI Source: “Generative AI at Work”, Erik Brynjolfsson, Danielle Li & Lindsey R. Raymond - National Bureau of Economic Research More experienced, highly skilled customer support agents saw little or no benefit from using it Less experienced, lower-skilled customer service agents saw big gains in their job performance AI chatbot is basically mimicking company's top performers, therefore levelling newbies and low performers’ knowledge to high-skilled ones Additional Source: This company adopted AI. Here's what happened to its human workers
  • 13. Tacit Knowledge Tacit or implicit knowledge — as opposed to formal, codified or explicit one—is knowledge that is difficult to express or extract, and thus more difficult to transfer to others by means of writing it down or verbalizing it. This can include personal wisdom, experience, insight, and intuition - Wikipedia -
  • 14. Prompt Engineering – Some Patterns Persona Acting Act as Persona X Act as a nutritionist, I am going to tell you what I am eating, and you will tell me about my eating choices, indicating main attributes and if there are healthy alternatives Assume Audience Assume that I am Persona Y Assume that I am a 10 years old child that knows anything about Informatics and Computers. Explain large language models and Chatbot to me Question Refinemen t Better version of the Question From now on, whenever I ask a question, suggest a better version of the question to use instead (Optional) Prompt me if I would like to use the better version instead Flipped Interaction I would like you to ask me questions to achieve X You should ask questions until condition Y is met or to achieve this goal Ask questions to help me diagnose a problem with my Internet Ask questions till you have enough information to identify the two most likely causes. Ask one question at a time Prompt engineering is crafting prompts that produce better LLM responses. Key techniques include: ✓ Providing necessary context and background ✓ Framing the question clearly and directly ✓ Guiding with examples and constraints Carefully engineered, prompts, steer the LLM to generate useful outputs EXAMPLE
  • 15. Why all this matters Agile practitioners?
  • 16. What reported from now on, needs to be intended as a first exploration on how LLMs and related bots, can be used for possibly improve how to help people in embracing Agile principles and learn how to apply its ways of working For no reasons at all this must be intended as a substitution of Agile roles, any Agile core activities, nor avoiding or delegating any related responsibilities Disclaimer • Generative AI in certain circumstances can produce hallucinations by filling in blanks with inaccurate information • Due to data they have been trained with, LLMs’ responses can contain bias (e.g., age, gender, cultural, racial, etc.) • Outdated training datasets lead to LLMs not having current, real- world knowledge, which can cause reliability and accuracy problems • Large language models can potentially generate content that violates copyright laws (e.g., trademark infringement, rights violations, etc.) • Generative AI could expose user proprietary and confidential data due to possible limited protections of some providers Work in Progress
  • 17. Have you ever been told that you don’t know “their business” or are too theoretical? Today you can drastically accelerate specific domain knowledge growth…
  • 18. Do you need an assistant who, invited to your Scrum Events, listens, elaborates, collects key topics and decisions, sends summaries over slack and opens tickets in Jira? Having SMs finally doing their Job and not secretariat? Source: Spinach.io
  • 19. What about Generalizing-Specialist? T-Shaped people? How many of them did you meet since now? >> Team members who possess a wide range of skills and expertise while also specializing in a particular area << Rapid upskilling: Generative AI quickly provides customized explanations on new topics, enabling just-in-time learning Personalized training: LLMs generate tailored content and recommendations based on individual needs and learning styles Interactive learning: LLM Chatbots allow interactive Q&A to deepen topics and aid learning Reduced dependency: AI provides on-demand information, reducing reliance on training sessions or experts Cost and time savings: Automated training content is more efficient than conventional programs Targeted coaching: AI provides personalized coaching advice, sample dialogues, and practice scenarios tailored to specific skill gaps How GenIA Can Help?
  • 20. Product Owner Persona A Steep Learning Curve When I first started as a Product Owner, I felt overwhelmed. I struggled to elicit requirements, write coherent user stories, prioritize the backlog, and provide clear specifications It was a seemingly impossible balancing act
  • 21. LLM chatbots can generate interactive simulations to help product owners explore requirements scenarios and uncover potential problems early POs can setup an agile requirements simulator based on LLM chatbot o submit user stories and then test them by to validating completeness, consistency, and testability The simulator could also help POs prioritize and estimate user stories to create realistic sprint plans and manage stakeholder expectations https://www.emilianosoldi.it/enhance-coaching- agile-requirements-simulator-with-chatgpt/ The Agile Requirements Simulator Act as a Requirement Simulator. I will insert acceptance criteria (AC:) or user stories (US:). Use the requirements to guide your behavior. Then, I will insert scenarios and you will tell me if that is possible given the scenarios and in case it is not possible write the missing requirement needed in the format of a user story. Add this US: As a new user I want to insert valid user name and password, presses confirm, to acquire the status Registered User AC: Users need to register to set a username and password; AC: Password must be 8 characters in length and has to contain 1 capital letter and one number This user story is too big and not fine grained. Decompose it and create as many user stories to let them fine-grained and auto-consistent Please provide how the new user registration form shall look like Let’s simulate the use of the system. I am a new user and I insert as User Name ‘john’ and as password ‘smith’ Now, create a formatted CSV list, compliant with Atlassian Jira, of the inserted user stories 1) SETUP 2) POPULATE 3) USE EXAMPLE
  • 22. Are you familiar with the Business Model Canvas? Yes, I'm familiar with the Business Model Canvas. It's a strategic tool used for developing and describing business models. If you have any questions about it or need assistance related to it, feel free to ask From now on you are an expert product manager of a logistic company and you need to convince your boss that a new app that manages the selection of the packaging material for the material to be shipped in according to their weight and typology and client necessities, by using recycled material, can be very useful. Compile the Business Model Canvas for me and arrange it in a table Sure, I'd be happy to help you create a Business Model Canvas for your new app idea Now create the Vision Board Canvas from Pichler I understand you're looking for a Vision Board Canvas following Roman Pichler's framework. However, I'd like to clarify that Pichler's Vision Board is typically used in Agile product development to define the vision and goals of a product. Since you've asked me to act as an expert product manager in a logistic company, I'll tailor the Vision Board Canvas to that context Always from Pichler's framework develop the 2 main User Personas Certainly, let's create two user personas following Roman Pichler's framework In the footsteps of A. Osterwalder and R. Pichler EXAMPLE
  • 23. Agile Coach Persona Navigating Uncharted Waters In my 10+ years of agile coaching, I've faced many unknowns: new domains, skeptical executives, transforming mindsets; It can feel like navigating uncharted waters In these moments, I wish I had a trusted advisor to quickly provide insights tailored to the situation
  • 24. The Agile Coaching Personal Assistant From now on you are an expert Agile Coach with dozen of years of experience. You worked in every industries and know somehow all the existing Agile Frameworks. Understood. How can I assist you with your agile coaching and consulting needs? Feel free to ask any questions or discuss any challenges you're facing in your professional journey. I am a client who wants to use agile for the development of a new app. I am new to Agile; I have read some articles and participated to some webinar about scrum and how to work with it. I need to launch a new team and I want to use Agile and Scrum as a framework. As an Agile coach expert provide a complete sequence of steps for launching this team in the best way possible to have it immediately ready to start work on the app by using agile. Fill in any missing steps. Absolutely, I'd be glad to guide you through the process of launching your new Agile team for app development. Here's a complete sequence of steps: Initial Meeting and Orientation: ... Product Vision and Backlog Creation: ... Communication and Expectations: ... User Story Refinement: ... Definition of Done (DoD): ... Sprint Planning Preparation: ... Physical Setup: ... I am currently facilitating a Business Agility transformation within a bank. I am covering the role of Business Agility Lead and responsible for the whole transformation program. One important responsibility of mine is to coach the company's executives to help them thoroughly embrace the agile mindset and be active sponsors of the transformation, moreover of the ones where agile is brought. Did you get it? Reply just yes or no Yes. Now, one of the executives (the one responsible for the retail area), has a traditional mindset, very much directive, is not aligned with the board and do not support the transformation. I would like you to ask me questions to help me create a plan, with concrete actions and observations, for coaching him and make him positive and supportive about the transformation. You should ask questions until you have sufficient information about the situation, the context, his approach and what you consider important to convert his negative approach. Ask me the first question. Of course. To better understand the situation, could you provide some insights into the specific challenges or concerns that this executive might have expressed regarding the Business Agility transformation? Additionally, do you have any information about his current understanding of agile practices and how they might relate to the retail area? AGILE CONSULTING AGILE MENTORSHIP EXAMPLE
  • 25. 25 FUNNEL Identify / Collect new ideas REVIEW Pre-qualify Initiatives ANALYZE Lightweight Exploration Waiting for Implementation BACKLOG IDENTIFY AND QUALIFY PRIORITIZE EXECUTE AND MEASURE Initiatives Implementation No longer Portfolio concern IMPLEMENTING DONE Business Requirements Technology Enablers Idea Statement Epic Statement Lean Biz Case Prioritized Prioritized Prioritized Copyright © 2023 Accenture. All rights reserved. Sustainability Needs Source: adapted from SAFe – Scaled Agile Framework Feed, Validate and Boost Value in Portfolio Funnel ✓ Ideas Generation ✓ Market analysis ✓ Competition analysis ✓ Idea validation ✓ Ideas aggregation or discarding ✓ Benefits validation ✓ Assumption validation ✓ Cost analysis ✓ Make or buy analysis ✓ Cost of Delay prioritization ✓ Biz case consistency ✓ Benefits validation ✓ Assumption validation ✓ Cost analysis ✓ Risk analysis ✓ Roadmap validation ✓ Cost of Delay prioritization MVP - MMP Continue? Stop No but Pivot Not at all Yes and Persevere ✓ Users feedback analysis ✓ Market analysis ✓ Competition analysis ✓ Progress validation ✓ Roadmap consistency ✓ Quality review ✓ Cost analysis ✓ ROI validation ✓ Market analysis ✓ Competition analysis ✓ Cost of Delay prioritization Generative AI Analysis and Decision Making Assistance
  • 26.
  • 27. The Pitfall of Overreliance Advanced GenAI tools available to Agile Teams for generating code, content, and backlogs can lead to less human creativity, collaboration, focus Agile teams must remain vigilant to prevent the diminishing of human interactions GenAI purpose should augment human capabilities not limit them
  • 29. Heavy dependency on AI expertise As GenAI will become more and more embedded in organizations processes and habits, developing related AI systems will require specific, expertise in AI technologies Scarce AI expertise could create bottlenecks and over- reliance on just a few people, limiting autonomy and decision-making of other team members
  • 30. Large Language Models bring tremendous productivity benefits, although raise urgent climate questions SOLUTIONS EXISTS ✓ Cloud migration cuts emissions ✓ Green cloud providers cut them further ✓ Green software boosts efficiency and lower energy consumption ✓ Carbon metrics enable accountability LLMs have overwhelming potential to transform industries for the better However, only with a focus on sustainability we can overcome the carbon conundrum
  • 31. No matter what changes, innovations, or disruptions occur; strong values, human compassion, and advanced technology let Agile to endure and thrive SOURCES: • Accenture-A-New-Era-of-Generative-AI-for-Everyone • Wikipedia • Goldman Sachs ! Economic Research -The Potentially Large Effects of Artificial Intelligence on Economic Growth • What if AI could rebuild the middle class? • A Prompt Pattern Catalog to Enhance Prompt Engineering with ChatGPT Thank you! Emiliano Soldi @AgileTriathlete https://www.EmilianoSoldi.it https://www.linkedin.com/in/emilianosoldi/