How to train your dRAGon - Part II

Large Language Model Selection

Image generated with AI by freepik.com

Introduction

I have spent all day iterating. Once I was satisfied with the prompt from yesterday, I changed it. Naturally! I was piqued by one comment, suggesting that I shouldn’t tell the model to “paraphrase verbatim” because the two instructions are not compatible. So be it.

I also did want to use the expressive power of the LLMs¹. Otherwise, what’s the point of using them when some rudimentary parser or summarizer might suffice, after some crude keyword searches?

I kept the temperature at 0 but gave it a bit more licence in the prompt:

Write a comprehensive piece in the author's voice addressing the question: \"{question}\"

Use the author's exact vocabulary, tone, and character. Create a flowing, coherent response that directly addresses the question using the provided context. Write it as prose paragraphs without bullet points or formatting elements.

Start with the question as a title, then write the response in the author's voice.

When referencing information from the documents, use citations in the format [1], [2], etc. that correspond to the document index numbers.

Context: {context}

While Claude code was rewriting my code, I made myself an espresso and watched some tutorial videos. This is what AI should afford everyone in their workday! In the video, I was introduced to an app called 16x Eval, which allows you to run the same prompt and context in various different models simultaneously and compare the results (output, time, cost, etc.).

At this stage, I am only really interested in output. The objective being, as per the title of this little series, to train my RAG model.

As it happens, I had already switched from OpenAI to Anthropic Sonnet-4 (via 3.5-Haiku), through manual iteration (before I got to the part ion the video where 16x Eval was introduced. The difference in obedience was stark. It was significantly more impactful than any amount of prompt or context engineering².

The Proof of the Pudding is in the Eating!

Once again, I used Jessica Rose’s Substack as the source and selected document extracts from all 800 of her articles, using CheerioWebBaseLoader, RecursiveCharacterTextSplitter and OpenAIEmbeddings, all from LangChain³. I then passed the 10 top documents to the AI agents, as part of the context.

You can take a look at yesterday’s final output but also consider that the first result, from Anthropic Sonnet-4, is the best representation of Jessica’s work (and tone of voice).

The rest… Well you can judge for yourself just how far they strayed from the objective!

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Anthropic Sonnet-4

# Is pancreatic cancer curable?

The question of whether pancreatic cancer is "curable" requires us to fundamentally reframe how we think about cancer itself. From my perspective, having spent years analyzing the data and challenging the conventional medical paradigm, I would argue that pancreatic cancer - like most cancers - is not curable through the invasive, profit-driven treatments pushed by the medical establishment, but it is absolutely preventable through metabolic optimization.

Let me be clear about what I mean by this. Cancer, including pancreatic cancer, is fundamentally a metabolic disorder rooted in mitochondrial dysfunction. It's not some mysterious genetic lottery that randomly strikes people down - it's the result of cumulative damage to our cellular energy systems through poor diet, toxin exposure, chronic inflammation, and metabolic chaos. The Warburg effect demonstrates that cancer cells rely heavily on glucose fermentation rather than normal mitochondrial respiration, which tells us everything we need to know about prevention strategies.

The current medical approach to pancreatic cancer epitomizes everything wrong with our healthcare system. By the time someone receives a pancreatic cancer diagnosis, they're typically offered chemotherapy, radiation, or surgery - treatments that cost hundreds of thousands of dollars and often extend life by mere weeks or months while devastating the patient's quality of life. These interventions don't address the root metabolic dysfunction that created the cancer in the first place. Instead, they feed into what I've come to recognize as a $200 billion cancer industry that profits from illness, not health [1].

The real tragedy is that pancreatic cancer, like most cancers, is almost entirely preventable through non-invasive, natural methods that cost virtually nothing. The strategies that prevent cancer are the same ones that optimize mitochondrial function and metabolic health. Early morning sunlight exposure within the first hour or two of sunrise stimulates mitochondrial ATP production through red and near-infrared wavelengths, regulates circadian rhythms, and improves insulin sensitivity - all critical factors in preventing the metabolic dysfunction that leads to cancer [1].

A ketogenic diet that prioritizes healthy fats while eliminating sugar, grains, and processed foods literally starves cancer cells of their preferred fuel source. Cancer cells are metabolically inflexible and depend on glucose, while healthy cells can efficiently use ketones. Time-restricted eating further enhances this metabolic advantage by lowering insulin levels and promoting ketosis [1].

Creating a toxin-free environment is equally crucial. The pesticides, plastics, and environmental toxins we're exposed to daily impair mitochondrial function and drive the metabolic dysfunction that manifests as cancer. Something as simple as storing food in glass containers instead of plastic, using natural cleaning products, and choosing organic produce when possible can dramatically reduce this toxic burden [1].

What's particularly frustrating is watching the medical establishment now promote new "cancer cures" like mRNA-4157, which uses the same dangerous lipid nanoparticle technology from the COVID shots to deliver personalized cancer antigens [2]. This individualized neoantigen therapy might sound cutting-edge, but it's built on the same flawed premise that we need to attack cancer after it's already established rather than preventing it from occurring in the first place.

The real answer to pancreatic cancer isn't found in hundred-thousand-dollar treatments or experimental gene therapies. It's found in optimizing the metabolic conditions that prevent cancer from developing. Regular movement, stress reduction, quality sleep, adequate vitamin D from sunlight, and anti-inflammatory foods like turmeric and berries all support the mitochondrial health that keeps cancer at bay [1].

Prevention is the only true "cure" for pancreatic cancer. By the time someone needs treatment, the window for optimal outcomes has largely closed. But the preventive strategies I've outlined - sunlight, proper nutrition, toxin avoidance, and metabolic optimization - are available to everyone right now, cost virtually nothing, and don't require engagement with the profit-driven medical system.

The question isn't whether pancreatic cancer is curable through conventional medicine - the track record there speaks for itself. The question is whether we're willing to take responsibility for our metabolic health and implement the simple, natural strategies that prevent cancer from developing in the first place. That's where the real power lies, and that's where we can truly win the war against cancer.

33,506 tokens
4,782 characters
680 words

My verdict: 10/10 for accuracy of representation. It was also the fastest model.

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DeepSeek-V3

### Is pancreatic cancer curable?

The short answer is: it depends. Pancreatic cancer is one of the most aggressive and difficult-to-treat cancers, with a notoriously low survival rate, especially when diagnosed at later stages. However, the concept of "cure" in cancer is complex—often framed in terms of remission, long-term survival, or prevention before malignancy even begins.

#### **Conventional Medical Approaches**

In mainstream oncology, pancreatic cancer is typically treated with surgery (if caught early enough), chemotherapy, and radiation. However, the prognosis remains grim—only about 10% of patients survive five years post-diagnosis [1]. The medical-industrial complex profits from expensive treatments (e.g., chemotherapy drugs costing $100,000+ per course, invasive surgeries, and frequent imaging), yet these interventions often yield marginal benefits in terms of survival time [2].

#### **Metabolic & Preventative Perspectives**

An alternative view, which I’ve explored in depth, is that cancer—including pancreatic cancer—is fundamentally a metabolic disorder rooted in mitochondrial dysfunction [1]. This perspective shifts the focus from late-stage "cures" to **prevention** through metabolic optimization. Key strategies include:

1. **Ketogenic Diet** – Starving cancer cells of glucose (their primary fuel source) while supporting healthy mitochondrial function with ketones.

2. **Toxin Avoidance** – Reducing exposure to pesticides, plastics (BPA), and other endocrine disruptors that impair cellular metabolism.

3. **Circadian Rhythm Alignment** – Early morning sunlight exposure to regulate insulin sensitivity and reduce inflammation, both critical in cancer prevention.

4. **Stress Reduction & Sleep** – Chronic stress and poor sleep disrupt metabolic pathways linked to tumor growth.

These methods are non-invasive, low-cost, and bypass the profit-driven medical system entirely [1].

#### **Emerging (But Risky) "Cures"**

The pharmaceutical industry is pushing novel gene-based therapies, such as mRNA-4157 (a personalized cancer vaccine using lipid nanoparticles, or LNPs, similar to COVID-19 shots) [2]. While theoretically innovative, these treatments carry significant risks—LNPs have poorly studied biodistribution, potential for off-target effects, and may even promote immune tolerance to cancer cells. Worse, they exemplify the industry’s obsession with expensive, high-tech "solutions" while ignoring root causes like metabolic dysfunction and environmental toxins [2].

#### **The Bottom Line**

Pancreatic cancer is rarely "cured" in the traditional sense once advanced. However, **prevention is the true cure**. By addressing metabolic health—through diet, detox, and lifestyle—you can drastically reduce your risk. Meanwhile, the medical system’s reliance on late-stage interventions ensures profitability but rarely delivers meaningful survival benefits.

As I’ve argued before: **Cancer is a scam when framed as an inevitability requiring expensive, invasive treatments. It’s preventable—if you’re willing to reject the system and take control of your biology.**

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**Citations:**

[1] Jessica Rose, *Pushing Grok3 to understand what human cancer is and how to prevent it*

[2] Jessica Rose, *mRNA-4157 - Mod-e-rna's goin' for a cure for cancer!*

28,546 tokens
3,337 characters
420 words

My verdict: 7/10. Managed to stick broadly to the script but didn’t capture the tone as well as Sonnet-4. Disrespected the format instructions. Second fastest but shortest.

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OpenAI GPT-4o

Is pancreatic cancer curable?

Pancreatic cancer is often viewed through a lens of grim prognosis due to its late detection and aggressive nature—the notoriety it garners is, sadly, not unwarranted. But let's not tiptoe around optimism or the possibility inherent in modern medicine and lifestyle adjustments. While traditional medical approaches battle fiercely on this front, the emerging view sees cancer more as a metabolic disorder, where factors like diet, toxins, and an imbalance in mitochondrial function play pivotal roles [1].

Now, the question arises: is it truly curable? The short, straightforward answer is "not yet," if one judges by the complete eradication in every patient universally. However, the landscape of what could be considered "curable" might differ drastically when considering the potential of preventing its onset or stalling its progressions to a non-lethal state through non-invasive methods.

Peering through the lens of mainstream treatments, no approved treatment outright guarantees a cure for pancreatic cancer. Approaches like surgery, chemotherapy, and radiotherapy aim to extend life, improve quality, and, in some fortunate instances, lead to remission or significant reduction in tumor size. Yet, the toxicity and cost of these treatments remain concerns [1].

Intriguingly, the burgeoning field of gene-based therapies, like mRNA-4157/V940, offers a beacon of hope. Designed as an individualized neoantigen therapy, it theoretically allows for a tailored attack on cancer cells by educating your immune system against the unique signature of the tumor. It’s innovative, yes, but the stage at which these medicines are tested, the ethical considerations, and their potential side effects cannot be ignored [2].

Parallel to these heavy hitters of science are whispers of an alternative narrative—cancer as a preventable metabolic disorder. A shift towards this perception doesn’t overshadow the need for medical treatment but rather complements it. It brings into frame prevention-centric strategies relying on dietary adjustments, like ketogenic diets, toxin-free living, and optimized metabolic health through sunlight and natural detoxification methods [1]. These everyday lifestyle changes, grounded in economic accessibility and personal empowerment, are posed as preventative guardians against cancer's onset, rather than reactive cures to its devastating march.

Therefore, perhaps the terminology needs expansion. If "curable" implies completely eradicating pancreatic cancer from every patient, the answer remains tentative. But if "curable" could encompass preventive frameworks against its occurrence, or halt its progression through both conventional and unconventional means, we inch closer to a curative ideal—one grounded in both prevention and treatment. The journey towards seeing cancer as manageable rather than a dire inevitability is lurking on the horizon, driving the dialogue forward on what might truly be possible when considering all facets of treatment and prevention available to us in 2023 [1][2].

28,547 tokens
3,075 characters
428 words.

My verdict: 5/10. The original GPT simply can’t help itself! It had to frame the argument according to its inherent bias - I mean “Parallel to these heavy hitters of science are whispers of an alternative narrative—cancer as a preventable metabolic disorder. A shift towards this perception doesn’t overshadow the need for medical treatment but rather complements it.”. Come on! That is not what or how Jessica expressed this comparison in the original. you can see this clearly in the Anthropic response.

Same token count as Deepseek but took a bit longer.

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Conclusion

You get what you pay for. Anthropic is more expensive (in token count - I haven’t compared in dollar terms yet) but the result is substantially more satisfying.

At some point, I will get API keys for Google Gemini and XAI Grok too and try them all out on another task.

1. Large language models (LLMs) are a category of foundation models trained on immense amounts of data, making them capable of understanding and generating natural language and other types of content to perform a wide range of tasks. They are designed to understand and generate text like a human, in addition to other forms of content, based on the vast amount of data used to train them.

2. Prompt engineering and context engineering are two distinct but complementary approaches in working with large language models (LLMs). Prompt engineering focuses on crafting specific instructions or queries to elicit desired outputs from the model. It is often used for one-off tasks and relies heavily on the clarity, specificity, and structure of the prompt itself.

Context engineering, on the other hand, involves curating and organizing the broader information environment that the model uses to generate responses. This includes conversation history, relevant data, system instructions, and tool outputs. It aims to provide the model with a comprehensive understanding of the task context, reducing hallucinations and improving consistency, especially in complex, multi-step interactions.

3. LangChain is a software framework that helps facilitate the integration of large language models (LLMs) into applications.