Uploaded December 2021 | Updated September 2026, 2 weeks ago
A Statistician by the name of Abraham Wald saved the US government millions with this one simple observation. Where else do you think we can apply survivorship bias?
#DataScience #KenJee #short
β Subscribe: youtube.com/c/kenjee1?sub_confirmation=1
π Listen to My Podcast: youtube.com/c/KensNearestNeighborsPodcast
πΈ Check out My Website - kennethjee.com
βοΈSign up for My Newsletter - kennethjee.com/newsletter
π Books and Products I use - amazon.com/shop/kenjee (affiliate link)
Partners & Affiliates
π 365 Data Science - Courses ( 57% Annual Discount): 365datascience.pxf.io/P0jbBY
π Interview Query - interviewquery.com/?ref=kenjee
MORE DATA SCIENCE CONTENT HERE:
π€My Twitter - twitter.com/KenJee_DS
π LinkedIn - linkedin.com/in/kenjee
π Kaggle - kaggle.com/kenjee
π Medium Articles - medium.com/@kenneth.b.jee
π» Github - github.com/PlayingNumbers
π My Sports Blog -playingnumbers.com
Check These Videos Out Next!
My Leaderboard Project: youtube.com/watch?v=myhoWUrSP7o&ab_channel=KenJee
66 Days of Data: youtube.com/watch?v=qV_AlRwhI3I&ab_channel=KenJee
How I Would Learn Data Science in 2021: youtube.com/watch?v=41Clrh6nv1s&ab_channel=KenJee
My Playlists
Data Science Beginners: youtube.com/playlist?list=PL2zq7klxX5ATMsmyRazei7ZXkP1GHt-vs
Project From Scratch: youtube.com/watch?v=MpF9HENQjDo&list=PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1t&ab_channel=KenJee
Kaggle Projects: youtube.com/playlist?list=PL2zq7klxX5AQXzNSLtc_LEKFPh2mAvHIO
A Statistician by the name of Abraham Wald saved the US government millions with this one simple observation. Where else do you think we can apply survivorship bias?
#DataScience #KenJee #short
β Subscribe: youtube.com/c/kenjee1?sub_confirmation=1
π Listen to My Podcast: youtube.com/c/KensNearestNeighborsPodcast
πΈ Check out My Website - kennethjee.com
βοΈSign up for My Newsletter - kennethjee.com/newsletter
π Books and Products I use - amazon.com/shop/kenjee (affiliate link)
Partners & Affiliates
π 365 Data Science - Courses ( 57% Annual Discount): 365datascience.pxf.io/P0jbBY
π Interview Query - interviewquery.com/?ref=kenjee
MORE DATA SCIENCE CONTENT HERE:
π€My Twitter - twitter.com/KenJee_DS
π LinkedIn - linkedin.com/in/kenjee
π Kaggle - kaggle.com/kenjee
π Medium Articles - medium.com/@kenneth.b.jee
π» Github - github.com/PlayingNumbers
π My Sports Blog -playingnumbers.com
Check These Videos Out Next!
My Leaderboard Project: youtube.com/watch?v=myhoWUrSP7o&ab_channel=KenJee
66 Days of Data: youtube.com/watch?v=qV_AlRwhI3I&ab_channel=KenJee
How I Would Learn Data Science in 2021: youtube.com/watch?v=41Clrh6nv1s&ab_channel=KenJee
My Playlists
Data Science Beginners: youtube.com/playlist?list=PL2zq7klxX5ATMsmyRazei7ZXkP1GHt-vs
Project From Scratch: youtube.com/watch?v=MpF9HENQjDo&list=PL2zq7klxX5ASFejJj80ob9ZAnBHdz5O1t&ab_channel=KenJee
Kaggle Projects: youtube.com/playlist?list=PL2zq7klxX5AQXzNSLtc_LEKFPh2mAvHIO








![How I Built a Profitable AI Product in 43 Days
I built my SaaS Newsletter Hero in 43 days in order to prepare for the massive AI disruption I see coming. This was my process, the lows and the highs.
Check it out here: https://www.newsletterhero.ai/
Code: BETA45 ($99 for the full year - more than 50% off the monthly rate)
00:45 Days 1-10: Foundation & Planning - Team organization took unexpected energy and time - Multiple decisions required before writing any code - Key lesson: Working with a human team forced accountability
02:15 Days 11-24: Market Research & MVP - Newsletter market chosen after extensive analysis - Three core pain points identified through creator interviews: - Writing faster in personal voice - Stronger subject lines - Easier multi-platform distribution - [03:45] MVP features: custom templates, subject line generation, user profiles, credits, payments
05:30 Days 25-35: Launch Reality Check - Major assumption proven wrong: Users wanted control, not one-click solutions - Marketing became unexpectedly difficult despite existing audience - Multiple integrations added: Kit, Mailchimp, podcast uploads - Key insight: Building a product and getting people to care about a product are two completely different games
07:45 Day 35: First Paying Customer - Customer acquired through Reddit comment on micro-SaaS celebration post - Validation moment: Stranger paid for the product - Customer feedback immediately integrated, especially onboarding improvements
09:15 Days 36-43: Growth & Learning - Additional paying customers from existing network - Product responsibility realization as users depend on it for income - Honest admission: I am currently just ass at marketing How I Built a Profitable AI Product in 43 Days](https://i.ytimg.com/vi/uokE-FiDUVw/mqdefault.jpg)

