Dear Editor,

Please find attached my article, “BIG BLUE KNEECAPS THE FRUIT: IBM’s Calculated PC Play”, a rigorous, strategy-focused retelling of the IBM’s entry into personal computing in the 1980s to take on the Apple II.

I contend that the original battle was between the IBM PC and the Apple II, a battle that Apple lost decisively, with lasting consequences for the technological landscape and Apple itself. This piece explores the strategic thinking behind IBM’s entry into the personal computer market, arguing that the IBM PC was less a technological innovation and more a calculated move to undermine Apple’s position in the business sector.

I believe this perspective offers a fresh take on a well-trodden historical narrative, and I hope the article’s analysis of IBM’s strategic choices and their impact on the industry will be of interest to your readership.

Subtext and timeliness: The article deliberately doesn’t make any attempt to connect that battle to Deepseek’s recent “shock and awe” entry because there are too many unknowns at this point, other than having a Twain-esque “notice” at the beginning. Each reader should develop their own perspective. This article can help.

I’ve embedded an analysis LLM prompt directly at the end of the article’s text. Simply pasting the entire article into any LLM will generate an unbiased analysis of the piece, which I believe will go a long way towards inviting your readers to understand the piece at a deeper level.

I added an explicit “Rebuttals Acknowledged” section. This section addresses some potential counter-arguments, while ensuring that my core message is not obscured by prevaricating language. I left that section untouched by LLMs, to provide you with a clear sense of my unassisted writing style.

Here’s an overview of how I incorporate LLMs into my writing process, as it might be somewhat unconventional. The core premise, and all the key phrases and observations that connect the dots, such as “technological arbitrage,” “kneecapping,” “invented afresh,” “we must not take lightly,” and “no high-end technology reused” were conceived by me without the aid of a large language model. In my view, this is an important way for authors to differentiate themselves in this new era.

The article’s development involved a multi-stage process using Google Gemini 2.0. I began by writing unstructured free-form notes. Then I iterated on guidance to produce text that “sounded like me,” ultimately settling on the instruction: “Adopt the tone of an autodidact software engineer reminiscing about the past. Adopt the fluent, expressive, but precise tone of an expert non-native speaker of English.” I also asked the LLM to generate a chapter for my (fictional) autobiography to capture a pensive tone.

I then manually edited and restructured the initial LLM output, incorporating the best aspects of over a score of drafts. I paid particular attention to concision, as I find LLM-generated text can often be too verbose. After achieving a satisfactory structure and content, I used a fine-tuning prompt to improve the flow of the text, again making over 50 manual read-edit-regenerate iterations. Finally, I prompted the LLM to analyze the validity of my points to ensure the article was not just persuasive but also insightful, and performed smaller fine-tunings based on these analyses.

To speed up review, I provide editors access to my original unstructured notes, LLM prompts etc. See my website https://annoylysis.com/editors/ibmapple/. [no password atm; if locked, use “editors” and “20250128”].

I am confident that this article offers a valuable perspective on a pivotal moment in the history of personal computing, and I would be honored if you would consider it for publication.

Ranga Sankaralingam <ranga@wabisabimicro.com>