Day 1 was a very insightful and thought-provoking experience. Learning about paradigm shifts made me realise how our beliefs and perspectives can influence the way we see ourselves and the world around us. The activity of visualising my perfect life helped me reflect on my goals, the people and circumstances that matter to me, and the barriers that may stop me from reaching my vision. The debate on “Does money buy happiness?” was another highlight. Listening to different perspectives helped me understand that happiness is not defined only by money, but also by relationships, purpose, experiences, and inner peace. Overall, the session encouraged me to question my existing perspectives, be more open-minded, and understand that sometimes changing the way we see things can be the first step towards changing our lives.
We began our session by exploring “The Perfect Life”—what a perfect life looks like to each of us and how we imagine it. We reflected on the challenges, circumstances, and people that may sometimes come in the way of achieving the life we envision.
We also explored the idea of a Paradigm Shift and understood that every individual sees the world differently based on their experiences and point of view. What may seem one way to us can look completely different to someone else.
The session also helped us understand the difference between being Proactive and Reactive—how we respond to situations and how our choices and reactions can shape our lives.
We discussed our Circle of Concern and Circle of Influence, recognising what is within our control and where we can choose to focus our energy.
One of the most meaningful reflections was the Iceberg of the Perfect Life—understanding that what people see on the surface is often only a small part of the story. Beneath the picture of a “perfect life” are struggles, efforts, emotions, and experiences that others may never see.
Most importantly, we reflected on celebrating life, appreciating the journey, embracing challenges, and focusing on what we can influence rather than what we cannot control.
A beautiful reminder that a perfect life may not mean a life without problems, but a life where we learn, grow, choose our responses, and celebrate every moment.
i learned that always be prepared to face any situation in life without any prior ultimatum. You never know when it’s your final good bye. Always take time out to meet your loved ones without any delays
Honestly, I didn’t know what to expect at first, but I’m so glad I came. It was such a wholesome experience so many conversations, laughs, games, stories, and little moments that made us think. I really loved how comfortable and easy everything felt. Thank you for making it such a beautiful experience!
I joined FS around three months ago, and one thing that was completely new for me was the idea of a Life Class. The school is organising these sessions for around 8–9 days. Two days are over so far, and these are some of my experiences and thoughts from Day 1 and Day 2.
Day 1 started with a simple question: What does your perfect life look like? We were also asked to think about the obstacles that stop us from reaching that life. It made me think about the changes I personally want to make and what I can do differently to move closer to the kind of life I want to live.
One of the most important ideas for me was the concept of a paradigm shift. The situation in real life may remain exactly the same, but changing the way we look at that situation can completely change how we experience it. Sometimes the problem is not only the situation itself, but also the way we are thinking about it. This idea has stayed with me even after the session, and I would definitely like to apply it more in my day-to-day life.
We also had a discussion about Money vs Happiness. What I liked about the discussion was that it was not really about choosing one over the other. Both have their own importance in life, and perhaps the real challenge is finding a balance between them.
Day 2 went even deeper.
One of the activities asked us to imagine what our relatives, friends and close ones would remember about us at the end of our life. It sounds like a simple question, but when you actually think about it, it makes you look at your priorities differently.
We were then asked another question: What would you do if you knew you had only 24 hours to live? Would you tell the people close to you?
For me, the answer was quite clear. I would want to spend that time with the people who are closest to me. I would also want to express my gratitude to them and tell them things that we often feel but do not always say.
These two days have made me think about life from perspectives that we normally do not stop and think about in our everyday routine. There are still several days of Life Class left, and I am curious to see what thoughts and questions the upcoming sessions bring.
muniba mazari’s speech – how life is a blessing and even in the worst scenarios we can make the best of it
my last 24 hours on earth – reflecting and choosing what i would i do if i only had 24 hours in my life, made me go back to reflecting what really matters in this life? not one thing of the list was about my work or the deadlines or my dream job. but about relationships, forgiveness, joy, food & dancing. i think i will prioritize these things along with work & finances.
First, you research different AI platforms and compare what each one can do.
Examples include:
ChatGPT — general-purpose AI for reasoning, writing, coding, research, etc.
Claude — strong for long documents, reasoning, coding and structured work.
Gemini — Google’s AI ecosystem, with strong multimodal and Google-service integration.
Microsoft Copilot — AI integrated into Microsoft’s productivity and development ecosystem.
Perplexity — focused strongly on AI-assisted search and research.
Specialized AI platforms — platforms designed for coding, marketing, data analysis, design, customer support, and other specific jobs.
The research shouldn’t just ask “Which AI is best?” Instead, you create criteria such as:
Criteria
What you investigate
Accuracy
Does it give correct answers?
Reasoning
Can it solve complex problems?
Speed
How quickly does it respond?
Cost
Free, subscription, API costs
Context
How much information can it handle?
Multimodal
Text, image, audio, video?
Privacy
How is user/company data handled?
Reliability
Does performance remain consistent?
Explainability
Can you understand why it produced an answer?
Integration
Can it connect to other systems?
This produces a platform comparison report.
2. What is PACE?
There isn’t one universal AI framework called PACE. One current PACE framework defines it as:
P — Plan A — Architect C — Code E — Evaluate
It uses specialized AI agents to divide software-development work into stages rather than asking one AI to do everything. PPACE Framework
Think of it like this:
Plan → Architect → Build → Test/Evaluate → Improve
For example, suppose you want AI to develop a traffic-management application.
P — Plan
Define:
What problem are we solving?
Who will use the system?
What data is required?
What are the success criteria?
A — Architect
Design:
AI model
database
sensors
APIs
user interface
security
data flow
C — Code
Build the actual system.
E — Evaluate
Test:
Accuracy
Safety
Bias
Performance
Reliability
Failure cases
This is useful because AI development becomes a controlled process instead of “ask AI to build everything.”
There is also another current product called Pace that provides AI skills/workflows for different organizational roles such as engineering, sales, finance, legal, data, marketing and design, so you need to identify which PACE your project means.
3. What is CRAFT?
Again, CRAFT is not a single universal AI acronym.
One current CRAFT framework is designed around making AI work repeatable, auditable and disciplined rather than relying on remembered prompts. It uses things such as versioned workflows, confidence gates, backups and multi-persona validation. CCRAFT Framework
The basic idea is very important for AI research:
Don’t just ask an AI a question once. Create a repeatable process that another person can inspect and reproduce.
For example:
Input → AI processing → Validation → Human review → Output → Audit record
That makes AI much more suitable for business, government, research and safety-critical applications.
4. What is a traffic-light audit?
This is probably the easiest concept to understand.
A traffic-light audit evaluates something using:
🟢 Green = acceptable / low risk 🟡 Yellow = needs attention / medium risk 🔴 Red = unacceptable / high risk
For AI, you could audit several categories:
Area
Result
Meaning
Accuracy
🟢
Good performance
Bias
🟡
Some potential concerns
Privacy
🟢
Appropriate controls
Explainability
🟡
More documentation needed
Security
🔴
Serious vulnerability
Human oversight
🟢
Human approval exists
Reliability
🟡
More testing required
There are published AI-audit frameworks that use traffic-light risk assessment alongside multiple technical KPIs, including model performance, discrimination/fairness, transparency and explainability.
So a traffic-light audit is essentially a visual risk-management system.
5. Traffic-light audit for an AI system
Imagine you’re evaluating an AI system used to control traffic lights.
You might investigate:
Technical
Is the AI accurately detecting vehicles?
Can it recognize pedestrians?
Does it work at night?
Does it work during rain?
What happens if a camera fails?
Safety
Can the AI accidentally keep a direction green?
Is there a safe fallback?
Can humans override it?
What happens when the AI makes an uncertain prediction?
Fairness
Does it work equally well in different locations?
Does it disadvantage pedestrians?
Does it behave differently in high-traffic vs low-traffic areas?
Security
Can someone manipulate the sensors?
Can someone interfere with the AI?
Is the system isolated from unauthorized access?
Governance
Who is responsible if the AI makes a bad decision?
Are decisions logged?
Can investigators reconstruct what happened?
Then you could produce:
Overall AI Risk: 🟡 YELLOW
because perhaps the system performs well but still needs stronger security and human override mechanisms.
6. How all of these fit together
You can think of your research project as:
AI Platforms ↓ Compare different AI technologies ↓ PACE ↓ Plan → Architect → Build → Evaluate ↓ CRAFT ↓ Make the AI workflow repeatable, documented and auditable ↓ Traffic-Light Audit ↓ Green / Yellow / Red risk assessment ↓ Final Recommendation
This is a strong structure for an AI research / AI governance / AI evaluation project.
Example final research question
“How can different AI platforms be systematically evaluated using structured frameworks such as PACE, CRAFT, and traffic-light risk auditing?”
Then your research could compare ChatGPT, Claude, Gemini, Copilot, Perplexity and specialized AI systems, evaluate them against common criteria, and finally assign risk ratings.
One particularly important modern research principle is human-in-the-loop evaluation: recent Microsoft Research work found that developers want AI to take on substantial assembly work while maintaining explicit authority boundaries, provenance, uncertainty signals and human control.
During the first 2 days of Life Class – AI Themed, I was introduced to different AI prompt frameworks like PACE and CRAFT. I also got to know about biases that the training models of popular AI tools carry. I also learnt how to create AI workflows for repetitive and time consuming tasks like adding tasks in my to do list from emails and chats, clearing the unimportant emails from the mail box.
What I Learned About Emotional Intelligence and Leadership
This training helped me understand that effective leadership is not only about knowledge or IQ. It is also about understanding and managing our own emotions while being aware of how our emotions affect others.
One of the most important lessons I learned was that when we feel stressed, frustrated, or challenged, we can sometimes react before thinking. By taking a moment to pause, breathe, and reflect, we can respond more thoughtfully and make better decisions.
I also learned the importance of self-awareness. Sometimes, others see behaviors in us that we do not recognize ourselves. Seeking feedback from colleagues and team members can help us identify our strengths and areas for growth.
Another valuable lesson was learning how to give and receive feedback in a respectful and constructive way. Effective feedback should focus on specific situations and behaviors rather than personal criticism. This creates a more positive and productive environment.
Finally, I learned that emotions should not be ignored or suppressed. Instead, they should be acknowledged, understood, and managed in a healthy way. Doing so helps build stronger relationships, improves communication, and creates a more positive team culture.
Personal Reflection
My emotions create an environment around me, whether positive or negative, and they influence the people I work with every day.
I believe my team experiences me as a positive, approachable, and supportive person who brings energy and encouragement to the group.
Rather than completely changing my emotional behaviors, I would like to continue improving how I manage and express my emotions, especially in challenging situations.
As a leader, I want to continue growing by strengthening my active listening skills, showing empathy, encouraging open communication, and supporting the growth and development of others whenever possible.
First two days of life class Acad theme were filled with curious discussions. We discussed points related to our own emotional well-being as well as student well-being.
On the first day we made a timeline of our journey at FS and what were the important highs and lows which made us reflect how far we’ve come in this journey.
The activity on childhood image was also interesting where we reflected about our childhood goals and individual traits
Watching the movie ‘The Intern’ was a good experience. Connecting to the individual characters, especially Ben, to our own life made us reflect how we take care of others and how we are taken care of by other BENs.