The Minhaaj's Podcast

Aytekin is the founder and CEO of JotForm, one of the most widely used no-code automation platforms in the world, serving more than 35 million users across education, healthcare, nonprofits, and small businesses.

He’s also the author of the Wall Street Journal and Publisher’s Weekly bestselling book Automate Your Busy Work,

00:00 – Introduction
Founder mindset, automation philosophy, and the future of work

00:01 – Why Automate Your Busy Work Was Ahead of Its Time
No-code, automation thinking before the AI boom

01:09 – Building JotForm Before the AI Hype Cycle
20 years of bootstrapping, slow growth, and real product-market fit

02:29 – Forms as the Gateway to Automation
How education, nonprofits, healthcare, and SMBs really work

03:49 – From Forms to Workflows, Approvals, PDFs, and E-Signatures
Designing automation for people without developers

04:21 – Solo Founder Reality: Doing HR, Legal, Support, and Product Alone
The hidden cognitive cost of running everything yourself

04:51 – Competing with Google Forms as a Bootstrapped Founder
Why automation and delegation became survival tools

05:58 – Email Automation as Cognitive Relief
How prioritization systems reduce stress and decision fatigue

07:41 – Applying Automation Internally: Teams, CI/CD, and Testing
Why automation makes teams safer, not riskier

08:10 – Designing Products Around How People Actually Work
From tools to systems thinking

09:17 – Writing, Teaching, and Sharing Automation Principles
From Medium and Forbes to a bestselling book

10:48 – Discovering the AI Revolution After Publishing the Book
Automation philosophy vs AI productivity tools

11:16 – “People Aren’t Overworked — They’re Over-Busy”
The psychology of modern work and burnout

12:28 – Embodying Automation Principles Inside the Company
Scaling without chaos

12:48 – Email Prioritization Systems That Actually Work
How to design inboxes for executives and founders

14:20 – Gmail Filters, Labels, and Decision Automation
Simple systems over complex tools

16:59 – Automation as Stress Reduction, Not Speed
Why missing important work causes burnout

19:21 – Continuous Deployment and First-Day Code Commits
How automation builds trust and confidence at scale

21:12 – Why Automation Shouldn’t Be Feared
Risk reduction through systems

22:08 – Internal Automation Lessons from JotForm’s Engineering Culture

23:01 – Future of Work: Policy, Strategy, and AI
WEF, global work, and structural change

24:32 – Does AI Kill Jobs or Create Better Ones?
A real company case study

25:02 – Deploying AI Support Without Laying Off Employees
How JotForm handled AI responsibly

27:09 – Human-in-the-Loop AI Systems
Why oversight matters more than hype

28:19 – Training AI Through Documentation and Feedback
How resolution rates improved from 25% to 75%

31:01 – Improving AI Through Better Knowledge Systems
Documentation as infrastructure

32:36 – New Roles Created by AI Adoption
From support agents to AI evaluators

33:29 – Multilingual AI Support at Global Scale
Why AI enables inclusion, not just efficiency

35:09 – Why JotForm Didn’t Get Acquired
Independence, focus, and long-term thinking

39:29 – Focused Work, Fewer Hours, Higher Leverage
Redefining productivity at scale

41:06 – Evolution of JotForm Into a Full Automation Platform
From forms to AI agents and integrations

42:09 – AI Agents Demo Discussion and Key Takeaways
Real use cases, real ROI

46:18 – User Research at Massive Scale
Learning from 35 million users

48:03 – Omnichannel AI Agents: Web, Instagram, Gmail, Salesforce
Training once, deploying everywhere

49:35 – The Future of AI Agents as Digital Employees
One system, many touchpoints

50:14 – Advice for Young Developers and Founders
How to compete in the AI era

50:49 – Growth Mindset Through Every Tech Revolution
From PCs to the internet to AI

52:10 – Why This Is the Best Time to Be Young
Opportunities created by AI and no-code tools

53:38 – Closing Reflections on Building, Learning, and Purpose
A long-term view of work and life

Aleksa Gordic is an ex-software/ML engineer at Microsoft & DeepMind with a broad background across the "whole stack" - maths, electronics, software engineering, algorithms, ML & deep learning (computer vision, natural language processing (NLP), geometric DL, reinforcement learning (RL)...), web, mobile, etc. He is a Top Linkedin Voice in AI for 2023. He has The AI Epiphany YouTube channel, and occasionally shares his projects on GitHub and blogs on Medium.

# Timestamps

00:00 Intro

00:45 Dropping Out, Self Learning & Chris Olah

03:20 From Android Developer to ML Engineer

06:25 LeetCode and CodeForces, Coding vs Soft Skills

17:30 Input and Output Mode of Learning

21:41 Yugoslavian Education, Cevap Cici, Hate for Schooling

25:46 Maths Teaching, Lack of Incentivizatiion and PISA Scores around the World

29:29 Inspirational Teachers

31:50 Microsoft HoloLens Summer Camp & Apple Vision

39:26 Microsoft Research, Google Ai, OpenAI & ResNet

41:50 Culture at Microsoft vs Google, Teams & Research Areas

50:00 Proprietary vs Open Source Models, Falcon 40B, MosaicML

01:01:02 Microsoft’s Gameplan, Profits vs User Acquisition

01:10:27 Alan Turing’s Paper, Definition of ‘Machines’ & ‘Think’

01:14:05 Neuromoprhic Computing, Neuronal Pathways & Future of Hardware

01:16:18 LLM benchmark Saturation & Research Directions

01:20:37 Disinformation, Adobe Firefly and Social Fabric

01:23:33 Lawsuits against Stability AI & OpenAI, Transition from Non-profit to For-Profit

01:28:30 Politicization of AI, Supercomputing & Technological Real Politik

01:31:14 EU AI Regulation, European Innovation Stifling & Repurcussions

01:38:54 US restrictive Visa Regime, H1B Tech Visa problems & Tech Talent Moving out of the US

01:47:00 Life outside Work, Sports & Calisthenics

Season 2 episode 2 of The Minhaaj Podcast this week brings on the child prodigy and genius co-creator of dataframes.jl package for Julia, Dr Bogumił Kamiński. Bogumil learned C language without owning a computer from library books at the age of 16 in a small Polish town. In post-communist Poland he went on to study applied problems in management and economics and his interest lies in computational models for real-life problems.
He currently serves as the full professor of economics at the Warsaw School of Economics. He also holds the following positions:
- Head of Decision Analysis and Support Unit
- Chairman of the Scientific Council for the Discipline of Economics and Finance
- Member of the Presidium, Statistics and Econometrics Committee, Polish Academy of Sciences
- Adjunct Professor, Toronto Metropolitan University
- Data Science Laboratory Researcher, Fields Institute, Computational Methods in Industrial Mathematics Laboratory
- Affiliated Faculty, Toronto Metropolitan University, Cybersecurity Research Lab
President, INFORMS Polish Section
- Co-editor, Central European Journal of Economic Modelling and Econometrics
- Editorial board member, Multiple Criteria Decision Making journal
Independent Supervisory Board Member, AutoPartner S.A.
Bogumił Kamiński is an expert in the application of mathematical modeling to solve practical problems in business. In the past, he gathered experience as head of business intelligence and data analytics units in one of the largest Polish consulting and IT solution implementation companies.
His field of expertise is the creation of complex decision-support models that use machine learning, optimization, and simulation methods. He is one of the world-leading experts in the Julia language and has numerous contributions to the core of the language and the package ecosystem. He created the famous dataframes.jl package for data science.
He also created SilverDecisions software, which is freely available online for modeling decision trees. He has written five books one of which I have reviewed earlier, Julia for Data Science.
# Timestamps
00:00 Intro
01:08 Learning Programming, Communist Poland & First Computer
07:07 Polish Education System & STEM teaching
11:35 Julia’s Conceptualization & Expectations
28:05 PetaFLOP club language, Data Type-based Operations & Julia’s Performance
38:11 Project Celeste, 800M astronomical objects detection, HPC in Julia
59:50 Julia in Academia vs Industry - Speed & Ease of Learning
01:21:21 Customer-facing Apps, Streamline vs Genie
01:38:56 Julia and LLMs, Falcon 40B, Training & Inferencing in Julia
01:45:05 Relearning Julia, How to get Started
01:51:09 From in-memory to cluster processing and MIT partnership
01:59:09 Family, Productivity, Community & Work - Juggling different Balls

Ryan is an entrepreneur, data scientist, engineer, and former VC. He is the co-founder and CEO of Zenlytic, a SaaS business that makes a next-generation AI-powered BI tool that uses LLMs and Semantic layers. He previously co-founded Ex Quanta AI Studio, a full-service data consultancy.

Dr. Akhtar received his Ph.D. in Neuroscience and M.S. in Electrical & Computer Engineering from the University of Illinois at Urbana-Champaign in 2016. He received a B.S. in Biology in 2007 and M.S. in Computer Science in 2008 at Loyola University Chicago. His research is on motor control and sensory feedback for upper limb prostheses, and he has collaborations with the Bretl Research Group at Illinois, the Center for Bionic Medicine at the Shirley Ryan AbilityLab, the John Rogers Research Group at Northwestern University, and the Range of Motion Project in Guatemala and Ecuador. In 2021, he was named as one of MIT Technology Review’s top 35 Innovators Under 35 and America’s Top 50 Disruptors in Newsweek.

00:00 Intro

01:42 Multiarticulation of Prosthetic Hand, Finger Movements 

03:10 Visiting Pakistan at 7 Years Old, Inspiration for Prosthetics

04:34 $75,000 vs $10,000 Hand, Cost Reduction & Accessibility 

06:13 Sourcing Parts from China, Shenzen, Electronic Part Capital of the World 

08:45 3D Printing of Hand and Distribution of locally vs imported Parts

11:00 Fixing Repair Problems for Imported Components from China, COVID 19  

12:31 USB port, Bluetooth and Spiderman Web 

16:56 Android/iOS App, AI&ML & Sensitivity Controller 

18:50 From Research to Market, Tactile Feedback

24:15 Invasive Technology, Electrode Scarring & Partnerships

27:11 Cortical Implants & Future of BCIs for Humanity 

31:39 Neuroscience Labs as Co-working Spaces

33:20 Guitar, Linkin Park & Mohawk

38:34 OpenAI and Rubic Cube vs Prosthetic Hand 

49:16 Work in Ecuador & Inception of the Idea 

52:39 3D Printing vs Manual Construction of Prosthetics - Robustness 

01:04:31 Multimodel Neuroplasticity & Forced Interchangeability 

01:10:06 Neuroscience of Parenting,  Catch 22

01:14:00 Importance of Recognition & Thanking the Crew as a Leader 

01:17:00 From $200 in account to Funding round and Medicare Approving Psyonic Hand

01:20:29 Going Global and Exploring New Markets 

01:23:31 Infection Mitigation Design 

01:29:06 Low Cost Competitors, KalArm by Makers Hive & Game Plan 

01:36:33 Shoe Dog by Phil Knight and Power of Grit

01:40:40 Impact, Legacy & Fulfillment

Guest Social Media  Aadeel’s Profile: https://www.linkedin.com/in/aadeelakhtar/Perosnal Website: https://www.aadeelakhtar.com/Newsweek Coverage: https://www.newsweek.com/2021/12/24/americas-greatest-disruptors-medical-marvels-1659061.htmlMIT Innovators Coverage: https://www.technologyreview.com/innovator/aadeel-akhtar/

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Who is Minhaaj? 

Minhaaj Rehman is CEO & Chief Data Scientist of Psyda Solutions, an AI-enabled academic and industrial research agency focused on psychographic profiling and value generation through machine learning and deep learning.

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William H. Inmon (born 1945) is an American computer scientist, recognized by many as the father of the data warehouse. Inmon wrote the first book, held the first conference (with Arnie Barnett), wrote the first column in a magazine and was the first to offer classes in data warehousing. Inmon created the accepted definition of what a data warehouse is - a subject-oriented, nonvolatile, integrated, time-variant collection of data in support of management's decisions. Compared with the approach of the other pioneering architect of data warehousing, Ralph Kimball, Inmon's approach is often characterized as a top-down approach.   

00:00 Intro 

01:17 From failed Golf Career to a Computing one  

03:06 Originality, Patterns & Database Design 

04:37 Punch Cards, Magnetic Tapes, Fortran, Cobalt & Bits in IBM 1401s 

11:16 First Book with Arnie Barnett, First Conference & Peer Pressure from Vendors  

14:26 Winning over Marketing & Sales People vs IT Departments 

18:15 Rise & Fall of IBM, Arrogance, Rudeness & Apathetic Company  

20:04 Prism Solutions & Early Days of Data Warehousing, Dormant Data & Textual ETL 

30:20 Corporate Information Factory, DataMarts & ETL 

32:00 Inmon vs Kimball Approach of Data Architecture, Good, Bad & the Worse 

36:15 Data Reliability with Data Marts vs Centralised Data Warehouse  

39:00 Staging Area in Kimball System vs Vetting the Data   

41:00 Metadata, Beethoven & Importance of Metadata, 

45:00 Prolific Writing, Family of Writers & Edgar Allan Poe. Hated Writing in College 

48:51 Writing Course at Stanford, Fiction & Technical Communication  

51:16 Fiction Published Work & Posthumous Publishing 

57:03 ELT vs ETL, Data Needs Work. Computing Power and Data Transformation 

01:01:31 Big Data, Data Creation Speed & Future of Data Warehousing 

01:04:06 Textual ETL, MIT Symposium & Text Data Utilisation Algorithms, Medical Research & COVID 19  

01:13:45 Transformers, NLP, Graph Learning & Unfair Criticism & Animosity 

01:23:56 Dotcom Bubble, Gartner’s Hype Curve, Theranos and Deception 

01:29:45 Venture Capitalists are not Smart People, they are Rich People.  

01:35:31 Cloud Computing vs Local DWHs 

01:38:06 Databricks vs Snowflake 

01:42:03 Not a Book Reader, Carving your Own Path 

01:45:56 Travelling to 59 Countries, Experiencing Culture & Interesting Interactions 

01:50:00 From California to Colorado, Nature in the Rockies & Life  

Follow us:   

Full Episodes Playlist link: https://bit.ly/3p2oWJA 

Clips Playlist link: https://bit.ly/3p0Qmzs 

Apple Podcasts: https://apple.co/3v0YZxV 

Google: https://bit.ly/3s5vDwc 

Spotify:  https://spoti.fi/3H6jqf0   

Who is Minhaaj?   Minhaaj Rehman is CEO & Chief Data Scientist of Psyda Solutions, an AI-enabled academic and industrial research agency focused on psychographic profiling and value generation through machine learning and deep learning.  

CONNECT WITH Minhaaj  

✩ Website - https://bit.ly/3LMvwgT 

✩ Minhaaj Podcast - https://bit.ly/3H8MK4G 

✩ Twitter - https://bit.ly/3v3t1RJ 

✩ Facebook - https://bit.ly/3sV0XgE 

✩ ResearchGate - https://bit.ly/3I6BvLu 

✩ Linkedin - https://bit.ly/3v3FswQ 

✩ Buy Me a Coffee (I love it!) - https://bit.ly/3JCMAnO

Dhaval Patel is a software & data engineer with more than 17 years of experience. He has been working as a data engineer for a Fintech giant Bloomberg LP (New York) as well as NVidia in the past. He teaches programming, machine learning, data science through YouTube channel CodeBasics which has 428K subscribers worldwide. 

00:00 Intro

01:34 Autoimmune disease ‘Ulcerative colitis’, Life & Death Struggle, Back to Life

03:40 Mental Health, Steroids & Immune System 

11:00 Planning Videos, Pedagogy & Smart People Problem

17:15 Working at Bloomberg, Bloomberg Trading Terminal & Exceptional Talent in Bloomberg

21:13  Career Tracks on Data Related Spectrum, Pathways for different Careers

25:16  Data Structure and Algorithms, Politics vs Equations, Eternity 

28:20  ML vs Deterministic Programming, Time & Space complexity of the ML Models

30:37 Kaggle vs Real Life, Soft Skills for Engineers, Transition from Competitions to Industrial Use-cases 

30:02 Litmus Test for Hiring Data Scientists, Continuous Engagement & Adaptability

42:35 Loss of Productivity by Lack of Communication Skills, Education System Deficiencies, How to Win Friends by Dale Carnegie 

46:50 Death by PowerPoint, Simplicity & Walk vs Talk

49:51 Negotiating Salary,  Action vs Motivation, Cellphone is a Distraction 

57:35 Growing Vegetables, Joy of Gardening, Rural Childhood & GMO Food  

01:01:40 Dhando Investor, Motel Business Monopoly by Patels, Software Engineering

01:04:04 Deep learning, C++ Back-propagation Algorithms,  Nvidia Titan RTX GPUs, Amazon Stores Experience

01:08:49 Nvidia Broadcast Noise Cancellation Demonstration, Nvidia Card Filtering, CNNs and Edge Detection 

01:16:06 BlackBox Models, ML-centric vs Data-Centric Models,  

01:19:25 Natural Language Understanding, Yann Lecaun, Low Accuracy is NLP Models

01:21:18 Github AI Pairing, Data Structures & Future of Programming Languages

01:27:01 ETL pipelines & Distributed Computing Structures 

01:30:00 FAST API, Beginner’s Tools, Pytorch vs TensorFlow, Improvements in Tensorflow 2.0

01:35:05 Programmers vs Normal People, Semantics of English vs Programming Languages, pd.read_csv 

01:38:03 Nvidia GPU vs Apple M1 GPU, Hope for non-Nvidia Deep-learning, Google Colab

01:41:30 Google Pixel,  Google Tensor Chips & Chip Shortages

01:44:00 Discord Community for Data Science, Mentorship & Abundance Mindset

01:49:00 Struggles, Battles, Hopelessness & Dysphonia

Harrison Canning is a student at the Rochester Institute of Technology in the School of Individualized Studies, Founder of The BCI Guys & Neurotechnology Exploration Team. He makes videos on his Youtube channel The BCI Guys and has designed his own degree centered around brain-computer interface technology (BA in Neurotechnology).

The BCI Guys is a media company dedicated to removing the barrier to entry and increasing interest in the field of neurotechnology. It produces engaging, sensational, digestible, and informative content via YouTube, podcasts, and blog posts. Its aim is to lead the conversation around neurotechnology through a science-based approach and conveying what is possible, while also conveying the tremendous potential of brain-computer interface and neuromodulation technologies.

00:00 Intro

01:34 Assault, Concussion and Neurotech

06:01 Coping with Memory Loss, Mathematical Ability & Courage 

12:50  Moral Support, SuperMoms & Hope

08:15  Bodysuits, Neuro diseases, Robotics & Boston Dynamics

10:48  Pros and Cons of invasive vs non-invasive Solutions, 1000 Brains Theory, Signal Amplification Issues

13:40  Lucid Dreams, Brain Wave Differences in Human Subjects, RIT Neurotech Research Lab

28:16 Accuracy for Apple Watches & Wearables and Size to Measurement Precision Ration  

30:39  SpO2 Levels, Sleep and Stress levels, False Positives

33:32  Delta Waves, Meditation and Focus Research

37:30  Post-trauma Brain Rewiring, Man with Half a Brain, Machine Learning & Intent Prediction through Connectomes 

43:10  NeoCortex in Humans vs Other Animal Species, Cons of Late Maturation of Cortex, Human Behavioral Biology

47:00 NeuroPharmacology vs NeuroModulation, Addiction & Jordan Peterson

50:00 Deep Brain Stimulation, Jaak Panksepp, Clinical trials on 2000 People, Controllable Neuro Modulation to Alleviate Pain

53:30  Number of Electrodes, Depression & Anxiety, Neuropathic Pain 

56:10 Seizure Detection through AI, Brain Wave Patterns for Seizures, Chip Implants for Preventing them

58:30  Inspiring Mentor & Role Model 

01:02:40 Neuroscience Starter Kit, Cost of  Hypondyne Z vs OpenBCI , $499 EEG Cap

01:06:04 Neurotech Education Around the World. Neurotechx Latam, Nigerian Schools 

01:10:02 Distributed Neurotech, Remote Patient Monitoring, Technology Exchange 

01:14:50 Wernicke & Broca’s Area, Speech Restoration through ML & BrainGate

01:21:25 Motor vs Sensory Homunculus, Sense Substitution & Neuroplasticity 

01:26:18 Predicting Human Activity based on Brain Waves, Jennifer Anniston Neuron & Dedicated Neurons 

01:30:30 AGI, Recreation of Artificial Brain & Limbic System

01:36:00 Stereotypes as Dropout Regularisation, Racism, Xenophobia, Polarity

01:39:20  Icecream, Greasy Food, Music, Happiness, Sex & Rationality

01:42:00 Future of BCI Guys  

01:27:30  Neuroethics, Facebook Whistleblower, Body Image, Culture, Society & Cognitive Enhancements

Matthias Fey is the creator of the Pytorch Geometric library and a postdoctoral researcher in deep learning at TU Dortmund Germany. He is a core contributor to the Open Graph Benchmark dataset initiative in collaboration with Stanford University Professor Jure Leskovec.

00:00 Intro

00:50 Pytorch Geometric Inception  

02:57  Graph NNs vs CNNs, Transformers, RNNs

05:00  Implementation of GNNs as an extension of other ANNs 

08:15  Image Synthesis from Textual Inputs as GNNs 

10:48  Image classification Implementations on augmented Data in GNNs 

13:40  Multimodal Data implementation in GNNs 

16:25  Computational complexity of GNN Models

18:55  GNNAuto Scale Paper, Big Data Scalability

24:39  Open Graph Benchmark Dataset Initiative with Stanford, Jure Leskovec and Large Networks

30:14 PyG in production, Biology, Chemistry and Fraud Detection 

33:10 Solving Cold Start Problem in Recommender Systems using GNNs

38:21 German Football League, Bundesliga & Playing in Best team of Worst League 

41:54  Pytorch Geometric in ICLR and NeurIPS and rise in GNN-based papers 

43:27 Intrusion Detection, Anomaly Detection, and Social Network Monitoring as GNN implementation 

46:10  Raw data conversion to Graph format as Input in PyG

50:00 Boilerplate templates for PyG for Citizen Data Scientists 

53:37 GUI for beginners and Get Started Wizards  

56:43  AutoML for PyG and timeline for Tensorflow Version  

01:02:40 Explainability concerns in PyG and GNNs in general

01:04:40 CSV files in PyG and Structured Data Explainability

01:06:32 Playing Bass, Octoberfest & 99 Red Balloons 

01:09:50 Collaboration with Stanford, OGB & Core Team

01:15:25 Leaderboards on Benchmark Datasets at OGB Website, Arvix Dataset 

01:17:11 Datasets from outside Stanford, Harvard, Facebook etc  

01:19:00  Kaggle vs Self-owned Competition Platform 

01:20:00 Deploying Arvix Model for Recommendation of Papers

01:22:40 Future Directions of Research 

01:26:00 Collaborations, Jurgen Schmidthuber & Combined Research 

01:27:30 Sharing Office with a Dog, 2 Rabbits and How to train Cats