Ranking algorithms. LLMs. Recommendation engines. The systems that shape what people see—explained by someone who's built them and marketed with them.
All 100% Free.
From Ben Wills
Writing HTML since 1994
Writing Software since 1998
SEO, PPC, & Online Marketing since 2001
Weekly Episodes
New episodes every weekday. One technical topic per week, five episodes each.
Curriculum
Structured modules that connect engineering concepts directly to marketing applications. Each topic builds on the last.
Modules 1–4
Build your technical foundation with the core concepts that underpin all modern marketing systems.
Modules 5–8
Understand the major systems that power marketing platforms—from databases to machine learning.
Modules 9–11
Explore cutting-edge systems and distributed architectures that shape modern digital marketing.
Throughout all modules
Every concept connects back to practical marketing applications with concrete examples.
What You'll Learn
Each module connects technical engineering concepts directly to marketing applications. You'll understand not just what these systems do, but how they work under the hood.
Marketing Concept Engineering Concept ───────────────────────────────────────── Keyword indexing ← Hash tables Query performance ← B-Trees Domain authority ← PageRank algorithm Ad optimization ← Gradient descent Content systems ← Transformer models Scale & speed ← Distributed systems Ranking signals ← Feature engineering
Learning Outcomes
Technical literacy translates into strategic advantage.
Understand API docs, system architecture, and engineering specifications without translation.
Communicate with engineering teams using the right vocabulary and concepts.
See through marketing claims to understand what tools actually do under the hood.
Connect disparate platforms and understand how changes in one affect others.
Anticipate algorithm updates by understanding the engineering constraints behind them.
Move from tactical execution to strategic thinking with a systems-level view.
Who This Is For
This content is designed for professionals who want to move beyond surface-level understanding.
Primary audience
You work with search every day. Now understand how search engines actually index, rank, and retrieve content at scale.
Primary audience
You optimize campaigns daily. Learn how ad auctions, bidding algorithms, and ML-powered optimization actually work.
Primary audience
You're making decisions based on data. Understand the systems that generate, store, and process that data.
Secondary audience
You bridge marketing and technology. Deepen your engineering knowledge to become even more valuable.
Most marketers don't understand systems. Most engineers don't understand marketing. I've spent my career in both.
I've built search engines and I've optimized for them. I've written ranking algorithms and I've tried to beat them. I've architected data infrastructure and I've analyzed the data that flows through it.
That dual perspective is rare. It's also exactly what's needed to explain engineering concepts in ways that actually make sense to marketers—without dumbing it down or losing the important details.
Technical content is either too engineering-focused (assumes you already know the context) or too marketing-focused (treats everything as a black box). Nothing speaks to the growing number of people who need to understand both.
This site fills that gap. Engineering fundamentals, explained with the intuition and context that marketers need. No tutorials. No fluff. Just how these systems actually work.
What Makes This Different
Engineering blogs assume you're an engineer. Marketing content treats systems as black boxes. This does neither.
Example Content
See how engineering concepts connect to marketing applications.
# How search engines index keywords # This is simplified, but shows the concept keyword_index = {} def index_page(url, keywords): for keyword in keywords: if keyword not in keyword_index: keyword_index[keyword] = [] keyword_index[keyword].append(url) # Query: O(1) lookup time def search(query): return keyword_index.get(query, [])
# Simplified PageRank calculation # Shows how link structure creates authority def calculate_pagerank(pages, links, damping=0.85): n = len(pages) pr = {page: 1.0/n for page in pages} for _ in range(100): # iterations new_pr = {} for page in pages: rank = (1 - damping) / n for linker in links[page]: rank += damping * pr[linker] / len(links[linker]) new_pr[page] = rank pr = new_pr return pr
FAQ
No. The content is designed for marketing professionals without engineering experience. Concepts are explained from first principles with marketing context throughout.
Daily videos, typically 5–15 minutes. Clear, focused topics with high-density explanations. Visual technical diagrams to illustrate concepts.
Primary content is distributed on LinkedIn with native video. Additional content may be available on YouTube and as podcast audio.
The core educational content is freely available. The goal is knowledge sharing and community building, not immediate monetization.
Most marketing education focuses on tactics and tools. This focuses on the underlying systems—databases, algorithms, distributed systems—that power those tools.
Technical literacy differentiates you from other marketers. Understanding systems makes you more strategic, harder to replace, and better at communicating with engineering teams.
Resources
Daily videos explaining technical concepts with marketing applications.
Watch on LinkedIn →Full outline of all 11 modules and the topics covered in each.
View Curriculum →Curated collection of papers, books, and respected creators in this space.
Coming Soon →Not a technical blog. Not a marketing channel. The engineering behind the platforms you use—explained the way marketers need to understand it.
This isn't about writing code or following APIs. It's about understanding how these systems work so you can think clearly about what they do.
Ranking systems, classifiers, recommendation engines, LLMs—understand what's actually happening inside the black boxes that shape your results.
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