Sunday, December 31, 2023

2023-12-31 Sunday - 2023 Reflections

[image credit: Markéta Klimešová (MAKY_OREL) on



  • [376] commits to my personal knowledge management GitHub repositories

  • [2] long-term client engagements completed 
    • Client #1: ~$100B AUM, financial services sector
      • Enterprise Architecture consulting services
    • Client #2: ~$7B annual revenue, financial services sector
      • Enterprise Architecture consulting services
  • [1] Pro Bono consulting engagement, advising a SaaS startup  
  • [19] detailed resume reviews conducted
  • [30+] career coaching/mentoring sessions
  • [44] technology blog posts written 
  • [6,000+] miles traveled 
    • [13] cities visited
  • [5,844] LinkedIn connections (143 pending invitations to connect to review) 
  • [32,659] lines recorded in my 2023 Technology Reading List notes

The highlight of 2023, was this feedback from a startup founder:

"Following your code audit we started asking a ton of questions and ended up firing our tech team.  Thank goodness!  We would never have known if it weren't for you!"
(Key Findings: Hard-coded unauthorized user id and password, as well as unauthorized data exfiltration embedded in the business application source code, and highly sensitive data encryption keys committed into the source code repository. Significant software design and solution architecture concerns identified - related to reliability, performance, scalability, maintenance, cloud infrastructure costs, etc.)

Noteworthy 2023 LinkedIn Engagement


Saturday, December 23, 2023

2023-12-23 Saturday - 10 suggested books for your 2024 personal/professional development goals


[image credit: Mohamed_hassan on]

If you are still working on your 2024 personal/professional development goals, here are some suggested books to consider adding to your reading stack:

Ten books that greatly influenced my professional development:


Customers for Life: How to Turn That One-Time Buyer Into a Lifetime Customer


Secrets of Closing the Sale


Father, Son & Co.: My Life at IBM and Beyond


As a Man Thinketh


Make It Happen Before Lunch: 50 Cut-to-the-Chase Strategies for Getting the Business Results You Want


How to Win Friends & Influence People


How to Stop Worrying and Start Living


Several of Gerald M. Weinberg's books:

  • An Introduction to General Systems Thinking
  • Becoming a Technical Leader
  • Secrets of Consulting
  • More Secrets of Consulting
  • Exploring Requirements 1: Quality Before Design
  • Exploring Requirements 2: First Steps into Design
  • Are Your Lights On?: How to Figure Out What the Problem Really Is
  • The Psychology of Computer Programming


Letters from a Stoic



Thursday, December 07, 2023

2023-12-07 Thursday - Quantum Computing Conference Talks


IBM Quantum Summit 2023


2023 Mathematical Aspects of Quantum Learning Workshop (UCLA, IPAM)

Institute for Pure & Applied Mathematics  (IPAM)

(22 videos, playlist)

"Recent results have hinted at the role quantum computing and technology may play in the future of machine learning, but much remains to be understood.  For example, it has been shown that quantum computers can offer exponential improvements in learning from quantum data that comes from the physical world, and that compact quantum models can allow us to sample from probability distributions that seem inaccessible to traditional computing devices.  In addition, general purpose quantum algorithms exist to dramatically speed up a number of subroutines that are pivotal in existing machine learning systems, but come with challenging caveats or have led to novel classical algorithm counterparts that challenge the advantage provided by quantum systems.  However, fully grasping these results and connecting them to problems of interest today remains challenging for many reasons."

"In this workshop, we hope to bring together experts from mathematics, quantum algorithms, and machine learning to better understand this intersection and reach the full potential of quantum computing and machine learning.   This includes, but is not limited to, the ways in which quantum computers can accelerate existing machine learning algorithms, how we process inherently quantum data with either classical or quantum computers, and ways in which machine learning can change how we operate quantum devices.  We hope to identify a number of open questions of interest in each area, and draw strong connections to the mathematical foundations of both quantum computing and machine learning."



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