How I Built a 10-Year Life Analytics Platform in 5 Days (with Antigravity)

From 87,000 rows of raw spreadsheet data to a React/ML dashboard, powered by Antigravity and Gemini. Personametry.com

The Data Hoarder’s Dilemma

For the last 10 years, I’ve been obsessed with tracking my time. Every hour of work, every night of sleep, every family interaction—logged diligently in Harvest. By 2026, I had amassed 35,442 unique time entries covering 87,100 hours of my life.

I had the data. But I didn't have the truth.

Spreadsheets were too slow. Standard dashboards were too generic. I needed a custom "Life Operating System" that understood my specific contexts—Personas, "Deep Work" streaks, and Sleep hygiene.

In the past, building this would have been a 3-month side project to an outsourced developer since I've stopped coding back in 2010! This time, I decided to do it differently. I paired up with Antigravity (powered by Gemini/Opus and separately using Codex 5.2 to validate) to see if we could build it in a week.

Here is the story of Personametry. The worklog journal separately shared here.

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The Co-Pilot Experience: "Senior Engineer" on Demand

Working with Antigravity wasn't like using a glorified autocomplete. It feels like pairing with a Senior Principal Engineer, Business Analyst, Data Engineer, UX Designer & Systems Engineer - all in-one-person who never sleeps.

We established a Coding Contract early on: "No stubbing. Plan first. Self-validate." This set the tone. The AI didn't just throw code at me; it wrote Implementation Plans, created "Artifacts" to visual progress, I explicitly instructed it to maintain its own worklog.md.

Day 1: The Foundation (Dec 31)

We first reviewed options for a suitable tech stack geared towards Business Intelligence Dashboards. The choices were: 1) Google's Material UI, 2) AWS Cloudscape and 3) Ali Baba's Ant Pro suite. I chose Ant Pro because I wanted to learn something new and also it apparently enjoys the highest stars on GitHub compare to the others. We defined a clean architecture. Instead of hacking together a script, we set up a scalable ETL pipeline in Python. The AI understood the concept of "Personas" immediately— and used by Quicksight transformation code to map out my Harvest tags into clean P1 (Muslim), P3 (Professional), and P0 (Sleep) buckets.

Day 2: Visualization & The "Wheel of Life"

We moved to the frontend (React 19 + Ant Design Pro). The goal: A "Wheel of Life" radar chart.

• Challenge: Visualizing 10 years of balance without clutter.
• Solution: The AI implemented interactive year-switching and diverging bar charts to show year-over-year trends.

Day 3: The "Data Nerds" Playground

I wanted to slice the data myself. We built a SQL-like Query Builder UI.

• Me: "I want to filter by 'Deep Work' and see the trend."
• AI: "Here’s a dynamic QueryFilter component backed by an in-memory aggregation engine."

Day 4: Machine Learning & "The Optimiser"

This was the turning point. I asked it to research best practice ML techniques for leveraging my dataset and build a forecasting and optimization engine. I didn't settle for its original design. I fed its design into Gemini Pro, deep research, and fed that into the AI for review. It then settled on a revised design plan ml-recommendation-design.md. The AI didn't just give me averages. It built an Optimization Service using Goal Programming. It took my "hard constraints" (work contracts) and "soft goals" (increase family time by 10%) and solved for the perfect daily schedule.

It also added Anomaly Detection (STL Decomposition) to scientifically prove when I was burning out.

Day 5: Sleep & V1.0.0 (Jan 4)

Final polish. We added Sleep Health Heatmaps (Red/Amber/Green based on hours) and analyzed my circadian rhythm to find my average bedtime (10:17 PM).

By 2:00 PM, we tagged Version 1.0.0.

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The Result: Personametry V1

In 5 days, we built what would have taken me months alone:

• Tech Stack: React 19, TypeScript, Python, Ant Design Charts.
• Features: ETL Pipeline, ML Anomaly Detection, Goal Optimization, Interactive Dashboards.
• LOC: Thousands of lines of clean, strictly typed, documented code.

The biggest lesson? The future of coding isn't about writing syntax. It's about orchestrating logic. With the right AI partner, the barrier between "Idea" and "Shipped Product" has never been thinner.

Links:

• See the Code: github.com/khanmjk/personametry
• Play with the App (Not mobile friendly): Personametry.com

By 2:00 PM, we tagged Version 1.0.0.

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NotebookLM - Slides

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NotebookLM - Audio Overview

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NotebookLM - Video Overview

Personametry V1.0 Worklog with Antigravity

Personametry - a decade's journey of time tracking now enhanced with AI

A summary of 2025 performance and intro to personametry.com

It is the time when I share my Performance metrics for the previous year, this card pretty much sums it up, logging 8700 hours, with 3006 time entries, tracking close to 24 hours per day:

Background

For the last ten years I've been running an experiment in logging my time spent activities like: Work, Family, Me Time, Sleep, Spirituality, etc. In 2015 I developed a model for personal development, called RAGE (Reality, Aspiration, Goals, Expectations). In 2016, I got more serious by inspecting my time across all areas of my life against my RAGE model, which triggered deeper reflection on my aspirations versus reality. For the first three years, I maintained a rhythm of personal monthly performance reviews (PMPRs) and then transitioned to quarterly, mid-year and final year reviews. At the start of each new year, I would dive deep into the previous year's data - build analytics and dashboards, which I shared on this blog.

Context about my workflow - the early days

In the early days, my process for insights was quite manual. Logging my time was easy, using Harvest App, which I'd been introduced to by a good friend, Farid - around the time I switched to professional consulting, servicing some contracts with Crossbolt that expected Harvest timesheets for billing. Incidentally, Farid was the source of inspiration for me to critically think about Reality V Aspirations that led to me creating my RAGE model. 

Generating reports initially started with exporting from Harvest, and importing to Excel and running pivot tables and charts, using content for my blog posts. I needed a way to transform the Harvest data to higher level constructs - so I transitioned to Amazon Quicksight (now Quick Suite), using an AWS Free Tier account. Quicksight was useful in acting as a yearly dataset, creating analysis that I would have done in Excel (so replaced excel) and created the dashboards, which I'd then copy and share in this blog. A downside of Quicksight is it's a closed system, had no way of publishing dashboards for public sites (like Google docs embedded pages mechanism). The free tier also prevented me from using its built-in insights features, and more recently Quicksight's AI analysis. I added Google slides to my workflow, sharing my deep dives as in this post. As AI tooling emerged, I transitioned to AI analysis as described here.

Introducing my latest workflow - finally, the Personametry Dashboard is born - ZERO Workflows

I spent just under 5 days building my Personametry app with Google's Antigravity as my coding partner. What a journey (look out for a future post). Since November 2025, I've been learning how to build apps with Antigravity, at first building my SMT app, then building tools for work - and I had enough insights to get Personametry app built.  What's my new workflow then? Everything is now automated, apart from my manual time logging. I've built a dashboard that syncs daily with Harvest data, through an automated GitHub actions workflow that pulls time entries via the Harvest API. Harvest is so cool that they allow even free users full access to their APIs. An automated data transformation job runs that cleans up the data and transforms it just the way I used to do the meta level transforms using Quicksight. So no more Quicksight. All the dashboards refresh automatically. I no longer need to create Google slides anymore. At the start of each year, I'd usually spend about a week's time analysing, reflecting and creating dashboards. Now my analysis can be anytime, with zero manual work. Giving a week's time back! Yes, anyone has access to my data and dashboard, I don't mind sharing because I believe other folks could benefit from my experiment, decide to start their own tracking journey or build an app for themselves. The codebase is on GitHub.

Personametry.com is more than just a dashboard - introducing Machine Learning

With my rich dataset, there's opportunities for applying machine learning forecasting techniques and instrumenting goals. Check out the Machine Learning page. I can now tune my personas and in real time see the effects, example: If I reduce my sleep hours, where would the gains go? If I reduce my work hours, subject to constraints, what can I do? If I invest in health and fitness, what's the impact on Family time, etc. For me, this is a game changer. The app will evolve and learn as the dataset is updated, without having to change code or do manual imports! I might have to tweak the code just a little to cater for special years like sabbatical breaks though.

What's next - where am I going with this?

Version 1.0.0 is now live! Depending on how much time I have in 2026, I will look at embedded AI data driven analysis into Personametry.com, leverage conversational analysis. Ultimately I'm still striving to build the perfect personal assistant that just "knows" me. I will look at bringing in additional data sources like Strava, Netflix, Youtube, even integrating Islamic and Gregorian calendars. And finally I'll hook in a RAGE scorecard to match my time against the RAGE model! I could also turn this into a paid platform service, creating a platform for anyone to sign up and build their own RAGE model personas and track with Personametry.com!

Where did my time go in 2024? Sharing my 2024 Personametry results.

It's that time of year again to share my time tracking analysis for 2024. The visuals should be self explanatory and nothing surprising. 2024 was the year my professional work stream dominated, but not completely. I did also index on spending more time with family (at the expense of 1:1 time as a husband), and also spent much time on my own "me time" primarily focused on experimenting with AI tools. I maintained previous levels of spiritual hours, back to 2022 norms since 2023 was an outlier (pilgrimage to Makkah was the highlight of 2023). My health and fitness took a severe knock and is on a downwards trend since 2021. 2021 was the year I made big changes impacting personal and professional streams: Relocated to a new city (Cape Town) leaving friends and family behind in Johannesburg, starting a new job in a new company in a new domain -- I'm now four years into this transition, and I'm not pleased with the downwards trends in my personal streams. 2025 will need to be a year of intentional change in managing my work time, setting firmer boundaries, and finding a solution to working late nights, weekends, and limiting the streaks of long work hours. 2024 reached the peak in my work hours since starting time tracking in 2016, that's almost 10 years of time tracking! In the last four years, since starting my new job in 2021, the work hours are trending upwards (in 2022 I made adjustments to reduce work hours with some success), only to rebound higher in 2023, and much higher in 2024. In a future post, I will share the challenges of working for  a global high-tech giant like Amazon AWS from South Africa and the impact on personal time - it has been, and continues to be, the biggest challenge in maintaining my professional "happiness", especially when it comes to maintaining a regular "start day" and "end day" routines and rituals.

Overview since 2018

Here's the summary dashboard of my time spent in my personas since 2018:

What's my workflow for tracking all this data?

Nothing much has changed since I started my experiment back in 2016. I use Harvest for tracking my personal and professional streams. I use a free account, with one major project called "RAGE Time tracking". Tasks are related to my personas. I track my time from the minute I wake up till I go to sleep. Throughout the day, I switch between tasks, making sure I don't track my personal time as work time, including lunch breaks. The hours logged do track closely to 24 hours/day, for the whole year, with a negligible margin of error that's within reasonable tolerance (I'm still human!). The idea is to regularly inspect where my time is being spent, and make adjustments according to my prioritized streams. 2024 unfortunately wasn't my best year in reaching a harmony-state, something I'm not pleased about. The data helps me make sense of how my life is transforming, triggering moments of reflection for adapting or at times, just general acceptance of my current reality, it is what it is -- forcing me to make sense of my aspirations to perhaps re-calibrate (for areas where I have full agency to control and influence).

How has my workflow for insights generation changed over time - are genAI tools of any help?

In the early years, I used Excel as my main source of data insights. Later I moved over to Amazon QuickSight. I still use QuickSight to generate my analysis and dashboards, as I have a few transformations with calculated fields. I then export the Quicksight data tables as Excel file as the source data set for AI tools. Quicksight too, is a little quirky with ingesting new data, maintaining the integrity of calculated fields and sometimes data gets corrupted when updating its splice models. I spent a good few hours debugging failures in data alignment, missing rows due to errors in calculated fields (that should have "just worked").  I use a free account, so I'm unable to use any of the AI "Amazon Q" features - ideally, I'm expecting an interactive analysis/dashboard AI assistant that I can have a conversation with. Alas, there is no way to share or embed QuickSight dashboards openly, embedding QuickSight dashboards in blog posts would be cool.

Anyway, with the advent of ChatGPT, in the last two years, I started integrating AI data analysis. I spent the last few days with ChatGPT - suffice it to say, I'm not that impressed by ChatGPT's Data Analyst capability. Nothing much has improved since the last year. At least it can understand large datasets in Excel or CSV format which is cool, something that Claude, Gemini or NotebookLM don't currently support. 

ChatGPT's "Data Analyst" does a decent job performing exploratory data analysis, was able to infer what my dataset was largely about without me providing clues or guiding info. The biggest problem I encountered was loss of context, loss of memory, and complete loss of the data's runtime environment. I had to repeatedly reload the dataset because ChatGPT "lost the data", then re-coax it to understand the data fields. It also hallucinated and made simple mistakes calculating aggregated results. It got simple math wrong. At times, I had to specify in detail how to use the data fields to generate the insights I asked for. This was surprising as I had a much better experience on the model from a year ago. I'm using the latest 4o model, being a ChatGPT Plus subscriber. I feel that OpenAI team should just kill the Data Analyst as a separate feature and promote the Canvas Projects capability going forward.

On ditching the built-in "Data Analyst", I switched to the latest Projects capability in ChatGPT. I shared my dataset as project files, included all my blog posts on Personametry and RAGE as context data, and provided fine tuned instructions for the project as data scientist responsible for producing business intelligence reporting. I had a much much better experience using ChatGPT projects than Data Analyst - however - I still ran into issues with hallucination, over confidence in the AI's interpretation of data and calculated results. AI is still far from being a trusted source of business intelligence as far as I'm concerned. You need to take time to manually build your own reports and analysis, like the way I use Quicksight -- and then test the AI generates the same results. I've spent hours on this over the last few days - yes, it was a little frustrating - but nevertheless insightful. The more time I spend playing around with these tools, the more I am amazed at the potential power and future disruption in this space - and at the same time, the more I gain some comfort that there is still a long journey ahead. For my simple data set of hours logged by task, the AI doesn't perform 100% on first shot -- so for big businesses out there, don't go firing your business analysts, BI engineers anytime soon, thinking GenAI will replace these roles... IMHO, we are at least another 2 years away from maturing, if not, more. A key input is validation - you would need to generate reference test cases to validate all the metrics compute correctly to gain trust in AI-generated insights.

In 2023 I had some fun with Noteable's ChatGPT plug-in. I was really looking forward to Noteable's progress in the area of AI-assisted data intelligence, but alas, the company and product is no more. I'm now experimenting with something similar from deepnote, but it's early days - and also quite expensive for a general hobbyist as myself. I believe this is the future though.

Where do I see this experiment going?

Personal AI assistants are all the rage these days, some say 2025 is the year of AI agents. I'd like to build a truly personalized agent that is not just about rudimentary calendar integration, answering texts and emails - but an assistant that truly understands me as a person - across my personal and professional streams. Integrating my time tracking data, health, fitness and well-being data from smart trackers, integrated with my todo lists, etc. Coming back to personametry, I would like daily, weekly insights from my personal assistant. Imagine if we could have an assistant that says "Mo, I noticed you haven't exercised in awhile, and you're finishing work quite late. You've not had quality time with your wife and kids - and your recent trip to the ER is not boding well. I've booked dinner for you and the family at your favorite restaurant, and for the upcoming long weekend, I've made a booking at mountain lodge you will enjoy. I scanned your calendar, there's no major work deliverables or travel planned - so take some time to rest and recharge, or else you will burnout soon!"

So, what's the 2024 insights then?

Until I can get my personal agent implemented, manual Google slides will have to do. Check it out below!

'24 Personametry First Quadrimester (Jan-April) Work/Life Balance

So we're already in the month of May(!), I've missed my first quarter personal business review - hence I had to do a quadrimester review :-) A 4-month period is commonly referred to as a "quadrimester" link. The term "quadrimester" is derived from the Latin word "quadrimestris," which literally means "four months". However, it's important to note that the term "quadrimester" is not as widely used or recognized as "quarter" for a 3-month period.

2024 vs 2023 Insights and Comparisons

If this is the first time you're seeing my personal metrics, you might want to catch up on how I got here. I invented a term "Personametry" and have been tracking my time in some detail since 2016. Catch up on the history of personametry posts here.

<chatGPT>

• Family Time (P5 Family) has increased from 408.64 hours in 2023 to 488.14 hours in 2024, indicating more time spent with family.
• Professional Work (P3 Professional) saw a significant increase from 549.06 hours in 2023 to 825.54 hours in 2024, highlighting a heavier focus on professional activities.
• Individual Activities (P2 Individual) decreased from 339.81 hours in 2023 to 207.58 hours in 2024, suggesting less time spent on personal activities and hobbies.
• Sleep (P0 Life Constraints) saw a slight decrease, from 903.63 hours in 2023 to 857.69 hours in 2024, possibly due to the increased professional workload.
• Muslim Practices (P1 Muslim) also saw a decrease from 501.00 hours in 2023 to 418.30 hours in 2024.
• Time spent with friends (P6 Friend Social) and as a husband (P4 Husband) has also decreased.

These shifts suggest a trend towards more work and family engagement at the expense of personal leisure, sleep, and other social activities. This might reflect a shift in priorities or changes in personal or professional commitments.

This report delivers a comprehensive analysis of personal time allocation for the first four months of 2024, benchmarked against the corresponding period in 2023. The findings are crucial for optimizing time management strategies and ensuring alignment with broader personal and professional goals.

*Key Highlights*

1. Workload Increase: There has been a significant surge in professional engagement, with work hours increasing by 50.3% from 549.06 hours in 2023 to 825.54 hours in 2024. This increase indicates a robust uptake in professional activities, potentially reflecting expanded responsibilities or new projects.
2. Health and Fitness: A concerning decline in health and fitness activities was noted, with a 70% reduction in time allocated to these crucial activities. The decrease from 64 hours in 2023 to 19 hours in 2024 signals a need for immediate realignment of priorities to safeguard physical well-being.
3. Self-Learning and Development: Time invested in self-learning through books and other media saw a dramatic drop of 75%, decreasing from 69 hours in 2023 to 17 hours in 2024. This reduction could hinder ongoing personal development and professional competitiveness.
4. Sleep and Rest: Sleep-life balance saw a modest decrease of 5.1%, with total hours reducing from 903.63 to 857.69. While not as stark as other categories, this reduction will continue to be monitored to prevent potential impacts on health and productivity.
5. Personal Life Engagement: Time spent on broader personal life activities decreased by 14.7%, indicating potential overreach of professional commitments into personal time.
6. Husband Time: Notably, time spent in the role of a husband decreased by 40%, from 134 hours in 2023 to 80 hours in 2024. As every wise person knows, a happy wife is indeed a key to a happy life, suggesting that revisiting this balance could be crucial, lest we find ourselves investing significantly in couch time!

*Strategic Implications and Forward-Looking Statements*

The data from early 2024 underscores a pivot towards intensified professional commitments, which, while beneficial for career progression, has led to significant sacrifices in health, fitness, and personal development. To address this, strategic initiatives will focus on reinstating a balanced allocation of time across all domains to support sustained health, continuous learning, and overall life satisfaction.

Moving forward, we will implement routine evaluations and adjustments to our time management strategy. This will ensure that our commitments and daily activities are optimally aligned with our stated goals of maintaining a healthy work-life balance, fostering continuous personal growth, and ensuring physical well-being.

*Conclusion*

As we continue through 2024, our objective remains clear: to effectively manage our time to enhance our quality of life and fulfill our professional ambitions without compromising our health and personal development. This report serves as a foundation for making informed decisions that will drive improvements in our daily routines and long-term strategies.

</chatGPT>

My Reflections, what happened? I had a good thing going in 2023!

Personametry 2023 - Wheel of life streams, hours logged

It's that time of the year when I sit down and review my time tracking data for the year. This time round, playing around with ChatGPT (whilst still maintaining my AWS Quicksight dashboards). I was quite looking forward to continuing to use Noteable's AI/Data tools, sadly the service shut down :-(

I've shared my dataset openly and also you can look at the ChatGPT transcript of the conversation and prompts here.

ChatGPT's overall summary:

• Rest and Sleep (Individual): A substantial 2,856.11 hours, akin to the restorative power of a long, rejuvenating sleep every night.

• Professional Work: Impressively, 2,051.20 hours were dedicated to your professional life, showing a solid commitment to career growth and achievements.

• Family Time (Family-Man): A heartwarming 1,398.79 hours spent with family, which is like embarking on a year-long road trip with your loved ones, filled with bonding and cherished memories.

• Spirituality (Individual): A profound 1,106.44 hours in spiritual pursuits, reflecting a journey akin to a spiritual retreat, deepening your inner peace and understanding.

• Personal Time (Individual): 467.55 hours of 'Me Time', ensuring a healthy balance of personal space and activities, like taking a short, refreshing break each day.

• Marital/Wife (Husband): 451.91 hours dedicated to marital life, resonating with the quality time spent in building a strong, supportive partnership.

• Knowledge and Learning (Individual): 202.88 hours of enriching your mind, like attending a series of insightful lectures throughout the year.

• Health and Fitness (Individual): 145.07 hours, a commitment to staying active and healthy, similar to a consistent routine of short, daily workouts.

• Social (Friend): 117.06 hours, akin to enjoying meaningful social gatherings, reinforcing bonds and making memories.

Looking back, my time tracking is reaching steady state. Not sure I'm going to keep reporting these stats going forward, but I'll probably keep fine-tuning. For 2023 Scorecard, I'm glad to have focused and met largely my spiritual goals, work/professional goals was maintained year-on-year, despite the spike in work hours in the last quarter (I got "promoted", with extra responsibilities which means more work hours). Health and Fitness hours took a dive compared to 2022, but it seems that my Strava/Garmin activity tracking shows better performance in 2023 compared to 2022 (so more time logged doesn't necessarily equate to being for fit, or achieving more). Social time decreased because we lost some friends to emigration, and generally our year was focused on the kids as my son approached his final high school matric exams, we prioritised staying at home.

If you've read all my previous posts on Personametry, you would've learnt that as part of this experiment, even way back when I started in 2016, I wanted a personal-assistant AI to help me with my RAGE / Personametry framework. I wanted to engage in meaningful conversations with an AI-assistant, coach me, act as my council, gatekeeper, motivator, etc. I believe there is still a need for this and the current state-of-the-art still has some catching up to do. Nevertheless, I am quite enjoying my interactions with ChatGPT. It was able to understand my personametry data, derive some insights, create the views I would generally take a couple hours doing myself. It's just a matter of time until we get truly personalized agents, like a personametry-gpt agent. Here's what ChatGPT offered I should look into for 2024:

Here's my Personametry slides as usual:

Personametry + ChatGPT = personametry.ai (a truly personalised AI)

Around this time of year with 6 months already past us, I spend some time reflecting on my Personametry and RAGE model - keeping in check how I'm performing against my own personal and professional goals -- just like we do in business with mid-year performance reviews. 

If this is the first time you've come across my work on Personametry, here's a view of my time spent in 2022 compared to 2021, click here. 

My workflow until then was:

1) Export data from Harvest

2) Update Amazon Quicksight dataset by importing the Harvest export, creating transforms

3) Create a new analysis

4) Modify all the charts and views to include the latest data, publish a new dashboard

5) Create a Google slide deck 

NO MORE!! ENTER CHATGPT and the NOTEABLE plugin!

My new workflow is now much more simplified:

1) Export data from Harvest

2) Import to Quicksight, creating transforms

3) Export CSV from Quicksight

4) Prompt ChatGPT to produce the insights in Noteable I would normally have manually created

Okay, so I spent my Sunday locked up in my office playing around with ChatGPT geeking out on data analysis & visualisations. So not much gain in time productivity there - but the learning was fun and immensely rewarding. Yes, a good investment of time, spent learning and preparing to adapt for the new world of AI disruption!

I've been on my data capturing journey since 2015. My end goal to end up with an AI personal assistant that truly understands me. I suspect realising my aspiration isn't that far off and neither far fetched for that matter. My entire workflow would be a fully integrated AI assistant that has the ability to track all my activities, by the minute (imagine "personametry.ai"). To get there, the next simpler step would be to automate the data ingestion piece, leaving me with the only manual entry of starting and ending tasks. My next experiment would be to use the raw data export from Harvest, without doing any data transforms and let the AI do that for me. If that works, I can build in automation that does monthly data imports and produces insights for me automatically. Ideally, I would build personametry.ai as a task into my personal assistant. Imagine a time when we're all wearing a device that "just knows" what we're doing, who we're interacting with, and what we're spending our time on? This device, i.e. "my AI" or "personametry" will act as a guide, coaching us along the way to improve - and hold us accountable - calling us out on what we're paying attention to (i.e. deviating from our goals.)

Lessons Learnt - Still early days but very hopeful

• The tools are still early days, but still nevertheless very powerful and will definitely improve my productivity in future.
• It takes a few attempts to load data files with the plugin, CSV seems to cope much better than XLS files.
• ChatGPT/Noteable uses different methods each time for approaching the data analysis - some coaxing on the nature of the dataset produces better insights.
• I didn't need to edit any code myself so there's an immediate empowerment driver right there.
• Don't trust every output though, as the AI can get things wrong
• Double check calculations, ChatGPT still doesn't seem to get some simple math right the first time round
• It is amazing what one can accomplish with simple, clear prompting
• I am definitely going to learn more
• I had so much fun learning, I was in a state of flow for 10 hours and couldn't stop thinking about the world of possibilities of this technology!

Here's a video of ChatGPT prompts - Play at fastest speed (sorry, no time to edit)

Here's the conversation history with ChatGPT

Round 4

Round 3

Round 2

Round 1

Here's the Noteable project that I've released publicly

Here's a screen grab of the visuals in a nice slide view

Here's all the questions ChatGPT answered in various sessions

2022 Personametry Tracking - Work/Life Balance & Harmony Update

Courtesy

It is time for my yearly ritual of analysing my time spent the previous year. This ritual is one of analysis and reflection, setting up the stage for planning & making new intentions for the upcoming year, 2023! 

I've been doing this exercise consistently over the last eight years! Am I crazy? Maybe?! I've become quite the data junkie, and I'm loving it! 

I know that tracking every activity and accounting for every minute of one's life might seem like overkill to most people. I on the other hand, actually quite enjoy doing so! :-) Primarily because having insights into how I spend my time has really helped me be more conscious and intentional about my aspirations, goals and expectations covering all dimensions of my life, seeking balance and harmony in my personal and professional streams. My methods allow me to focus and maintain discipline with my time...

This is my value system that describes my streams:

Muslim | Individual | Professional (Work) | Husband | Family-Man | Social/Friend

When someone asks me the following: Mo, how's life? Mo, how are you doing work-wise? Mo, how's things? Are you happy? Are you meeting your aspirations? Mo, what consumes most of your time these days? I can have a sincere and authentic conversation about it.

Yes, as some of my friends have argued that you "just know" instinctively where your time is being spent, on what and you just know the areas you need to improve on. Sure, I get that and agree. I find it much more useful to validate my instincts, verify anecdotes with quantifiable data & metrics to help me answer such questions: Where am I spending my time? Am I spending time in the right areas according to my priorities? Am I heading in the right direction? How am I growing? Where am I in my stages of growth across all my personas? How do I measure success? Am I growing holistically as a person?

In 2015, I researched productivity and personal development methods extensively, culminating to me creating my own frameworks:

1. RAGE (Reality Aspirations Goals Expectations). Knowing yourself, i.e. what you stand for, your value system, by identifying Personas. For each Persona, define Aspirations/Goals that becomes your long term personal roadmap. What emerges from this is a scorecard that you can track your progress, see example from 2020.
2. PERSONAMETRY is another concept I created that essentially captures key metrics about yourself, TIME being our most valuable resource. If time is our most valuable resource, do we not owe it to ourselves to account for it? For each Persona you identify with, Personametry is your personal telemetry. It can be extended to a variety of use cases, including overall happiness/stress sentiment analysis. If you're keen to learn more, check out this product specification document I created years ago, but alas, haven't developed the app for it as yet (alas, no time, wasn't a priority!)

Personametry complements RAGE by providing data insights, that I use to analyse if I'm trending in the right direction or not. Keeping a personal RAGE scorecard helps me keep track of how I'm progressing against my personal roadmap. In the last eight years alone, these frameworks have helped me reach my highest potential in climbing up the career ladder (making CTO, executive role), becoming debt free and remaining debt-free for 7 years and-running, improve my marriage enhancing the foundations (insha Allah), and rekindled relationship with family members, including long lost friendships, develop a more consciously confident identity as a Muslim in the workplace, make big bold decisions of starting over in my career (like walking away from CTO and big financial incentives rewards, take a pay-cut and step down in role) or start my own consulting, also make time to focus on paying it forward by offering my time to coach/mentor for free, etc. RAGE/Personametry has also helped me in being critically selective of where/what/whom I spend time with, I've learnt to say "NO" more often guarding my personas and setting boundaries, even with my own family and dearest loved ones.

Emerging from this experience so far are some interesting learning experiences, such as how one's goals and aspirations can change with time, depending on one's stage of life. For instance, where I'm at right now in 2023, is my profession is no longer what drives me (I'm consciously not seeking out the next promotion or level up because I've been there already and experienced the life of an executive), as I'm now seeking new experiences centred on creating more purpose, meaning and fulfilment...Having said this, I remain a pragmatist and so am open to new job opportunities that more closely align with my value system (example: NGOs/NPOs looking for CTO/CIO expertise, Africa-friendly timezone working hours is also being considered). If you know of any opportunities in this area, do get in touch!

Analysing 2022 v 2021 - Data Analysis & Insights

Since 2016 I've tracked 24,983 (±25K) activities as data points, tracking my life streams as: Muslim | Individual | Professional (Work) | Husband | Family-Man | Social/Friend - thus logging 60,572 (±60K) hours with an error tolerance of ±0.5% (99.5% capturing accuracy). In 2022 alone, I logged 8,715 hours, of which: Professional Work consumed 23%,  Personal Life 43% with the physical constraint of Sleeping accounting for 34%. Yep, we sleep for a third of our lives, and I have the data to back that up!

Suffice to say, I've made some good gains in 2022 that I hope to carry through into 2023. Check the slide show for the rest...

P.S. If you'd like to have a coffee/virtual chat about my RAGE/Personametry concepts, or you're curious to learn more, or seeking a mentor/coaching/networking opportunity or you simply want to learn about my workflows, then please get in touch!

GROW Model - Coaching questions to consider

I recently came across the GROW model which I think complements my own RAGE model quite nicely when it comes to inspecting aspirations and goals. It's all about seeking clarity through questions:

Goal - What do you want? What's your desired outcomes (Aspirations)?

• What would you notice if you were performing in this area more proficiently?
• What would others notice if you were performing in this area more proficiently?
• What would be the benefits to your team / family / business / friends of you gaining proficiency in this area?
• What is the short- and long-term impact of you not enhancing in this area?

Reality - What's your current situation? Be brutally honest about current reality.

• What is the current state of your proficiency in this area?
• What have you done till date to develop proficiency in this area?
• What has helped your progress?
• What has held you back?
• How long have you been working on enhancing yourself in this area?
• Where do you feel stuck?
• What perceptions about yourself might be getting in your way?
• Are these perceptions accurate? How do you know?

Options - Exploring possibilities / Expectations. What could you do?

• What do you feel you need to gain proficiency in this area?
• What are the possible actions you can take to enhance yourself in this area?
• What else can you do? Probe deeper
• Now that you are aware of the possibilities, which one would you try first?
• What would you like to have happen?
• If you do nothing, what will be the impact?
• What does the wiser part of you tell you?
• If you were coaching someone on enhancing themselves in this area, what might you say to them?
• If there were no limitations/restrictions, what might you do?
• What options are within your control?

Will - What will you do? Commitment / Next Steps? 

• What support do you need to be successful in your next steps?
• What obstacles do you anticipate? How will you navigate them?
• How might you motivate yourself when things get tough?
• Who might be able to help you in achieving your next steps?
  

My 2022 mid-year review of Life/Work streams

Tis the period of mid-year performance reviews in the workplace, so I decided to inspect my own personal performance with my time tracking metrics covering the dimensions that make up my life and work streams. 

I've been tracking these metrics for a number of years already and at least once a year, share the analytics and insights from this lifelong experiment. I created the term Personametry which basically is about telemetry (metrics) about the self (personal). Feeding Personametry is a framework I've created for myself for personal and professional development, my RAGE model.

At the start of 2022 I shared insights from my past six years of tracking and also followed up another post zooming in on the 2021 year, highlighting the main time sinks and the impact on other related streams. I set a goal of turning things around in 2022 to get to a state of balance I enjoyed prior to 2021.

With half the year over, 2022 is fairing much better than 2021 - as I've been very intentional about the changes. 

Here are the headlines (comparing 2022 with 2021 for the first 7 months, January to July):

• Work hours is down 28%
• Spirituality is up 53%
• Family time is up 27%
• Social time is up 75%
• Overall "Me Time" is up 16%

Holistically then, my process of re-calibrating in 2022 is having the desired effect. I'm spending time in the areas I've prioritized without significantly compromising on a major stream like my work (work obviously provides for the lifestyle I'm grateful for).

For more insights, check out the embedded slideshow :-)

In terms of my overall happiness sentiment and tracking my aspirations and goals as governed by my RAGE model, I'll share in a separate post in September '22. I've started to warm up more and more to Mo Gawdats' happiness formula which has helped me in coming to terms with the turbulence I've experienced with my job/career decision to disrupt and reinvent myself...stay tuned for the next write up!