How I Wrote a Technical Book on Coin Authentication: From a $10k 1933-S Half Dollar Scandal to O’Reilly Publication

Ever stared at a rare coin and wondered: *Is this real? Or is it a clever fake?* I did—back in 2021, when a 1933-S half dollar sold for $10,000 in a Czech auction. The forums exploded. Was it genuine? Hand-engraved? A die mismatch? No one had clear answers. Just theories, speculation, and frustration. That moment lit a fire in me. I didn’t just want to debate authenticity. I wanted to *solve* it. That’s how my technical book on coin authentication using forensic analysis was born—and how I landed a deal with O’Reilly.

Why Technical Books Matter (And Why They’re Not Just About Teaching)

Most people think of books as tutorials. I see them as ownership. When you write a technical book, you’re not just sharing info. You’re saying: *This is my territory. I’ve studied it, tested it, broken it down, and built it back up.*

When I saw the 1933-S controversy, I didn’t see a coin. I saw a technical challenge—one with no definitive guide. Collectors, CTOs, forensic analysts, and even fintech folks were all arguing online. But no one had a repeatable, code-backed method to prove authenticity. That’s the gap I filled. My book isn’t about “collecting coins.” It’s about authenticating rare U.S. coins with digital forensics, image analysis, and die research.

And it’s written like a lab manual—every claim, every step, backed by code, data, and real images. That’s what makes it peer-reviewable, court-admissible, and collector-trusted.

How I Found the Right Topic (And Why It Started With a Scandal)

Find a Niche That’s Hot, Not Just Rare

The 1933-S wasn’t just rare. It was controversial, valuable, and technically complex. That’s the sweet spot. A good technical book needs:

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• High stakes—like a $10k coin under suspicion

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• Unresolved debates—“Is it a real die? Was it hand-modified?”

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• Technical meat—die alignment, strike quality, luster anomalies

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• Global reach—U.S. collectors, Czech auction houses, online forums

I didn’t write a hobbyist’s guide. I wrote a forensic toolbox—using that coin as the first case.

Build a Framework, Not a Timeline

Instead of a history lesson, I built a diagnostic system:

1. Die Diagnostics: Spotting die markers, spacing, symmetry
2. Strike Analysis: Reading depth, luster, relief—like a fingerprint
3. Image Forensics: Pixel-level comparisons, lighting traps, resampling clues
4. Provenance Tracking: Auction trails, digital footprints, metadata

Each chapter? A real example. That misaligned “IN” in “IN GOD WE TRUST”? We proved it with image overlays. The suspicious rim-field junction? Code detected the mismatch.

How I Pitched Publishers (And Why O’Reilly Said Yes)

Tailor Your Pitch to Each Publisher

I didn’t send the same proposal to O’Reilly, Manning, and Apress. I spoke their language:

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• O’Reilly: “This is about tools—Python, OpenCV, databases. It’s a lab notebook for coin forensics.”
• Manning: “Here’s a 5-step workflow to authenticate any coin.”
• Apress: “It’s peer-reviewed methodology. Think of it as applied numismatics.”

For O’Reilly, I attached a working prototype: a Python script to compare auction images with PCGS CoinFacts scans. That code? It’s still in the book today.

Sample Code: The First Tool in the Book

This snippet—from Chapter 1—showed publishers I wasn’t just theorizing. I was building:

import cv2
import numpy as np

def align_and_overlay(image1_path, image2_path, alpha=0.5):
    img1 = cv2.imread(image1_path, cv2.IMREAD_GRAYSCALE)
    img2 = cv2.imread(image2_path, cv2.IMREAD_GRAYSCALE)
    # Match sizes
    img2 = cv2.resize(img2, (img1.shape[1], img1.shape[0]))
    # Blend images
    overlay = cv2.addWeighted(img1, 1 - alpha, img2, alpha, 0)
    return overlay

# Compare the suspect 1933-S with a known MS65
auction_overlay = align_and_overlay('auction.jpg', 'coinfacts_ms65.jpg')
cv2.imwrite('diagnostic_overlay.jpg', auction_overlay)

Takeaway: Publishers want proof, not promises. A working script shows depth.

The Proposal That Got the Deal

My proposal had:

• A technical chapter outline (e.g., “Chapter 4: Fourier Analysis for Die Translation”)
• A full sample chapter (“Strike Quality vs. Lighting Artifacts”)
• Clear audience—collectors, appraisers, fintech, forensics
• My niche platform (10k followers on numismatic forensics)
• Market gap (“No book uses image forensics for coin authentication”)

O’Reilly signed me in two weeks. They saw the code, the case study, the real-world need.

Audience Before the Book (Why I Built a Following First)

You’re Not Just Writing—You’re Launching

I didn’t wait for publication. I started building:

• Weekly LinkedIn posts analyzing coins (“Why the ‘IN’ in that 1933-S is 3 pixels off”)
• GitHub repo with code, stamped “Coming Soon: Book”
• Webinars with PCGS experts on digital authentication
• Guest posts for numismatic tech blogs

This wasn’t marketing. It was trust-building. When the book launched, I had 500 beta readers, 200 reviewers, and a waiting list.

Authority Is Built in Public

By launch, I wasn’t “an author.” I was *the* guy who could prove a coin was fake with code. CTOs asked for tools. Auction houses wanted training. Law firms consulted me. I spoke at CoinFacts Live and Numismatic Society Tech Summits. That’s the power of positioning.

Writing the Book: My Tech Stack and Tricks

Tools That Make Tech Writing Scalable

I used:

• Markdown + Jupyter Notebooks for code-heavy chapters
• Git + GitHub for versioning (my co-author and I collaborated live)
• Overleaf (LaTeX) for final formatting (O’Reilly loved it)

Every chapter had:

• Code blocks (Python, shell scripts)
• Data sets (auction images, PCGS scans)
• Annotated comparisons (overlay maps, die markers)
• “Technical Takeaway” boxes—for busy CTOs and appraisers

Example: Technical Takeaway

Technical Takeaway: Use cv2.matchTemplate() to detect die shifts. A 3-pixel gap in “IN”? Likely die manipulation or counterfeit.

Working With Publishers: What I’d Do Differently

O’Reilly was great—but not flawless. My lessons:

• Fight for rights: I kept digital rights to sell PDFs on my site.

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• Guard technical accuracy: I pushed back when editors wanted to simplify code. “This *is* the point.”
• Leverage your audience: I shared draft chapters with my blog readers. Their feedback shaped the final book.

Manning and Apress offered advances. But O’Reilly? Their tech credibility was worth more. Their audience gets tools. They want to *use* what you write.

Why This Path Works—For Anyone With Expertise

Writing a technical book isn’t about writing. It’s about **positioning**. Do this:

• Pick a high-stakes niche (like coin authentication)
• Build a framework, not a history lesson
• Embed code, data, real cases—not just theory

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• Start building audience *now*—before you write Chapter 1
• Pitch with precision—to O’Reilly, Manning, Apress, with tailored messaging

You’re not just publishing a book. You’re launching a **brand**. The 1933-S was the spark. The real value? The method. Now, when someone asks “Is this coin real?” I don’t guess. I run the code. I show the overlay. I prove it. That’s what a technical book gives you: **the power to know—and show—the truth**.

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