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
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!
