Eugene Asahara, Soft Coded Logic
Putting the "I" Back into BI
This article is a supplement to my new book, Semantic Webs of Meaning: Building Contextual Knowledge Graphs for Deduction and Integration published by Technics Publications (on Amazon) . This is an extension to the topic, Machine Learning Models as Data Products, on page 173. In that topic, iris.py is an example of a Python program … Continue reading Web of Functions (Transformations)
Update August 25, 2026: The supplemental GitHub repo for the Semantic Webs of Meaning is live. The supplemental repo has these main purposes: Post material that is too down into the weeds for the book (ex. install instructions, full appendices, code samples, and tutorials) but is mentioned there. Enable me to expand upon and/or clarify … Continue reading Trailer for My New Book: Semantic Webs of Meaning
This blog describes the Time Molecules process for the analysis of adversarial situations. That includes frauds, competitive games such as Texas Hold'em Poker, and any other situation where imperfect information is the key asset. Beyond sheer skill, good adversaries rely on stealth, sleight-of-hand, misinformation/disinformation, information overload, mimicry (impersonation), etc. Adversaries paint a false picture for … Continue reading Seeing the Hook through the Uncanny Valleys Encountered by an Enterprise
Abstract AI agents are not just about producing answers—they are executing processes. If those processes emit events for each step, they can be studied the same way we study human and enterprise workflows. By capturing and analyzing these event streams, we can reconstruct the context behind agent decisions and understand how AI-driven systems actually operate … Continue reading AI Agents, Context Engineering, and Time Molecules
In the conclusion of my last blog, Chains of Unstable Correlations, I wrote: When you work around experts long enough, you notice that experts sometimes (usually?) forget what isn’t obvious to non-experts. Conversely, people in the field often see things experts overlook because they live inside the operational texture of the system. After a conversation … Continue reading An Interlude Before the Third Act of “The Assemblage of AI”
This is Part 2 of a 3-part series where I make the case that pre-aggregated OLAP is essential in this era of AI. The intent of this post is to describe just enough of how a pre-aggregated OLAP engine works for those who are unfamiliar with this technology: Those who have joined the business intelligence … Continue reading The Ghost of OLAP Aggregations – Part 2 – Aggregation Manager
The phrase “thinking outside the box” traces back to a deceptively simple puzzle: nine dots arranged in a 3×3 grid. The challenge is to draw four straight lines through all the dots without lifting your pencil. Most people fail at first because they instinctively keep their lines inside the square boundary implied by the dots. … Continue reading Outside of the Box AI Reasoning with SVMs
If your entry into the business intelligence (BI) game began after around 2010, it could be difficult to appreciate the value of OLAP cubes (referring mostly to SQL Server Analysis Services MD, ca. 1998-2010), those aggregations, and that MDX query language. In fact, you may have a negative impression of those relics, those "cubes", based … Continue reading The Ghost of OLAP Aggregations – Part 1 – Pre-Aggregation
Enterprise Intelligence and Time Molecules link through the Tuple Correlation Web. Introduction The main takeaway of this blog is an explanation of how my two books, Enterprise Intelligence (June 21, 2024) and the more recently published Time Molecules (June 4, 2025), connect. Time Molecules is a follow-up to my first book, Enterprise Intelligence. It connects … Continue reading BI-Extended Enterprise Knowledge Graphs
Welcome to the Prolog in the LLM Era Summer Vacation Special! Starring … Prolog ... knowledge graphs ... ChatGPT o4-mini ... neuro-symbolic AI ... and our special guest ... Thinking Fast and Slow! In this episode (Part 11 of the series), I wish to address how neuro-symbolic AI relates to this series. After all, the series title, Prolog … Continue reading Thinking Reliably and Creatively – Prolog in the LLM Era – Summer Vacation Special
Eugene Asahara, Soft Coded Logic 