Writing and mumblings¶

Advice to Young People, The Lies I Tell Myself

I'm really not qualified to give advice.

But enough people DM'd me on Twitter, so here it is. I don't have to answer the same question over and over again. After some more editing I realised that I am actually writing this for my younger sister Katherine.

Thoughts on Marketing, Positioning, and Scaling my Consulting

I've enjoyed writing about my indie consulting process. Today, I want to share some insights on marketing, positioning, and scaling my consulting business. This post builds on my previous discussions about referrals and the tools I use, focusing on how I've grown my practice through strategic marketing efforts.

As a former MLE, I had always relied on my hands-on coding skills to excel in my career. However, a hand injury forced me to adapt and pivot towards consulting. In this essay, I share my journey of becoming a successful AI consultant and the lessons I've learned about marketing, positioning, and scaling my business.

• Transitioning to consulting and building a marketing plan
• Generating leads and creating valuable content
• Closing leads using situational assessments

Losing My Hands Pt. 2: The Two Jasons

This is part of a series about my experience with a repetitive strain injury (RSI) during the COVID-19 pandemic. It talks about how this injury changed my life and what I think about now. If you want to know more about what happened, you can read part one here. I'm not going to give a lot of medical details. Instead, I want to look at how this injury changed what's important to me and how I live my life.

A comment on Twitter made me want to write this part of the series. I'm not trying to tell anyone how to live. I just want to think about the values that shape me and other men like me. This connects to some ideas I wrote about in my article on data literacy, where I talk about how we understand and use information in our lives.

Losing my Hands, Advice and Tips for RSI

This is the final entry (for now) of a series I wrote about my experience with tendonitis in both my wrists and thumbs during COVID-19. The injury occurred in 2020 due to overworking at my previous job, where I would put in excessive hours for weeks on end with minimal breaks. The debilitating pain prevented me from eating, dressing myself properly, and programming, leading to a significant disruption in my work and personal life. Ultimately, this experience led me to make three major changes:

1. Consulting full-time: Sometimes, you need to take a leap of faith; other times, you need a swift, firm shove in the back to overcome your limitations. The RSI was the latter that lead me down the path of higher leverage.

2. Revaluating my values: This doesn't necessarily mean discarding the traits that led to me getting an RSI, but it certainly made me rethink what is actually valuable and what I am trying to do with my life. Sorry to disappoint, but there has been no 'epiphany'. I am not discarding worldly possessions and pursuing a spirit quest to find 'my true self'. My hands are now a limited commodity, and I fear reinjuring myself. This means if I'm going to use my hands, it must be purposeful and deliberate.

3. Writing: Thankfully, we live in an era where you no longer need hands to express yourself through text. Writing helped me realize that I have spent my first three decades learning and absorbing knowledge and information. Now, in my thirties, my goal will be to share the thoughts and stories I've collected.

You can read the previous two entries here: Losing My Hands, Losing My Hands Pt. 2: The Two Jasons.

What is prompt optimization?

Prompt optimization is the process of improving the quality of prompts used to generate content. Often by using few shots of context to generate a few examples of the desired output, then refining the prompt to generate more examples of the desired output.

Systematically Improving Your RAG

This article explains how to make Retrieval-Augmented Generation (RAG) systems better. It's based on a talk I had with Hamel and builds on other articles I've written about RAG.

In RAG is More Than Just Embeddings, I talk about how RAG is more than just vector embeddings. This helps you understand RAG better. I also wrote How to Build a Terrible RAG System, where I show what not to do, which can help you learn good practices.

If you want to learn about how complex RAG systems can be, check out Levels of RAG Complexity. This article breaks down RAG into smaller parts, making it easier to understand. For quick tips on making your RAG system better, read Low Hanging Fruit in RAG.

I also wrote about what I think will happen with RAG in the future in Predictions for the Future of RAG. This article talks about how RAG might be used to create reports in the future.

All these articles work together to give you a full guide on how to make RAG systems better. They offer useful tips for developers and companies who want to improve their systems. If you're interested in AI engineering in general, you might enjoy my talk at the AI Engineer Summit. In this talk, I explain how tools like Pydantic can help with prompt engineering, which is useful for building RAG systems.

Through all these articles, I try to give you a complete view of RAG systems. I cover everything from basic ideas to advanced uses and future predictions. This should help you understand and do well in this fast-changing field.

By the end of this post, you'll understand my step-by-step approach to making RAG applications better for the companies I work with. We'll look at important areas like:

• Making fake questions and answers to quickly test how well your system works
• Using both full-text search and vector search together for the best results
• Setting up the right ways to get feedback from users about what you want to study
• Using grouping to find sets of questions that have problems, sorted by topics and abilities
• Building specific systems to improve abilities
• Constantly checking and testing as you get more real-world data

Through this step-by-step runbook, you'll gain practical knowledge on how to incrementally enhance the performance and utility of your RAG applications, unlocking their full potential to deliver exceptional user experiences and drive business value. Let's dive in and explore how to systematically improve your RAG systems together!

Low-Hanging Fruit for RAG Search

RAG (Retrieval-Augmented Generation), is a powerful technique that combines information retrieval with LLMs to provide relevant and accurate responses to user queries. By searching through a large corpus of text and retrieving the most relevant chunks, RAG systems can generate answers that are grounded in factual information.

In this post, we'll explore six key areas where you can focus your efforts to improve your RAG search system. These include using synthetic data for baseline metrics, adding date filters, improving user feedback copy, tracking average cosine distance and Cohere reranking score, incorporating full-text search, and efficiently generating synthetic data for testing.

Losing My Hands

The world was ending, and I couldn't even put my pants on. My hands had cramped up so badly that I couldn't grip a water bottle or type and could barely dress myself. A few weeks earlier, I had been riding the greatest decade-high anyone could have dreamed of. I was moving to New York, making 500k, working for an amazing company, and was engaged in what might be the most lucrative field on the planet. I was doing what I loved, getting paid well, and feeling like I was making a difference. Life was good. Well, as good as it could get during a once-in-a-lifetime pandemic. My name is Jason. I'm a machine learning engineer. And this is how I almost lost my hands.

When COVID-19 hit, I was a Machine Learning Engineer at Stitch Fix. Being remote meant avoiding the worst of the pandemic, which made life easier for me than most. However, as with many others, COVID-19 brought with it less-than-ideal coping mechanisms. While the world was falling apart outside, I was in a cocoon. I felt like I was just locked in and taking my job seriously because I enjoyed the work so much. What I didn't realize was that I was seriously harming myself. The idea that value was a measurement of the function of hard work, length of work, and economic activity became a madonna that consumed me. This experience would later shape my advice to young people and my reflections on self-worth, as well as influence my journey into consulting and open-source projects.

There would be ~6-week periods where I would wake up and start work around 7 am every morning, then code with few breaks until around 2 am, followed by long rest periods. Even to hardened engineers, keeping up this work rate and style of work is unsustainable, but what else are you going to do during a pandemic? When you’ve been conditioned to believe rightly or wrongly that your value as a human being is derived from the economic value you provide to those around you and all barriers to producing work have been removed by an unprecedented upheaval to social norms, it felt like there was only one path forward and that was working as hard as possible every day. This rat-brained mentality, combined with my binge work style is ultimately what I think led to the severity of my injury.

Another aspect that led to this insane cycle of overwork was that the team I was a part of was going through a lot of upheaval. Teammates were leaving, and I felt like I was left to pick up the slack. I’d like to think I was in control of my work, but consistently logging 12-15 hour days for weeks on end took its toll. At one point, my manager saw my commit history and took me aside, asking me what the fuck I was doing working this much. Imagine that. Your boss telling you that you’re working too hard. Ultimately, it came down to outside of pottery, BJJ and programming; there just wasn’t much else to do. My lifestyle had become a bubble, and when it burst, I came tumbling back to earth.

The loss of my hands came on suddenly and without much warning. One day, I woke up and realized I couldn’t hold my phone properly. I tried to get a glass of water but had the same issue. My hands were stiff and had a restricted range of motion; it was difficult to perform basic tasks. At first, it didn’t seem like a big deal; I just took a few hours off and rested. Maybe I had slept poorly or in an awkward position; maybe I had played too many video games that day. It’s not as if I was the first engineer ever to get pain in their hands, right? But things didn’t get better. Not that day or the next or even the next week. A sort of dread started to creep in as I realized most of the tasks I performed daily were becoming increasingly impossible for me to complete. This dread eventually transformed into an existential one.

The first fear was whether I could ever code again. If I can’t hold my phone, I can’t type. If I can’t type, I can’t work. Which quickly collapsed into If I can’t work hard, where do I derive my value from?

I slipped into a kind of depression because it was a listless kind of existence. I wasn’t sad per se, but I felt like my course had been rerouted, and I wasn’t sure where I’d end up. I would kind of just wander around New York, coping by going on dates or surrounding myself with non-tech-related people as I tried to get back into a normal routine. This was interspersed by periods of what is, in hindsight, less than optimal behaviours. I would do really stupid shit like go alone to Michelin-star restaurants for lunch or waste my day smoking a bunch of weed. It wasn’t quite a spiral as my life balanced itself out by diving into non-tech hobbies like spending 6-7 hours in Bryant Park playing ping pong, training BJJ, swimming a mile every morning and ultimately learning how to free dive, which helped me for a while to keep my mind off of not being able to work.

I went through acupuncture physiotherapy, tried anything that might work and threw as many resources at my hands as I tried to work through not being able to use them. I even considered peptides, PRP, and stem cells, telling myself even if it was a small fortune, it would be worth it if I could make a living again. All of these therapeutics and treatments helped to some degree, but I still deal with pain and stiffness even three years later. To this day, it affects my ability to cook, eat, get dressed, and say nothing about my hobbies. Even swimming would aggravate my wrists without treating them immediately afterwards. The whole experience of being this helpless is just insane to think about. Since being injured, I’ve hesitated to take on a lot of work despite enjoying it. Which has been the major push for me to shift roles slightly. I’ve turned down basically every offer to join a startup because I’m worried about reinjuring myself. And to be honest, I’m still trying to figure out what it all means. I don’t know if there is some moral or epiphany for me and how I approach work other than trying to be more purposeful with my work. Every time I code now, I have to weigh if what I’m doing is a valuable use of my time and resources. If coding adversely affects my health, it would be better for me not to do it.

I took roughly two years off of work. I wasn’t making much money or doing much programming. What helped was reminding myself that the skills that took me to ‘the dance’ are not the skills that will keep me happy for the rest of my life. You must keep moving and learning new things; otherwise, you will get left behind. In this current wave of AI optimism, I found myself enjoying things again and adapting. Again, I’m still trying to figure out what my injury means, but at any rate, I’m much more resilient now than where I was 3 years ago.

This idea that you have control over yourself and your actions and choices and can in some way shape your outcomes through nothing but your own decisions may sound haughty and full of myself, but I really do think it’s important to try and frame things in terms of what you’re able to do. Stop worrying about everyone else and things that are out of your control.

I think the first time something really good happens to you—I mean really good—like when you can take a step back from life and breathe and look at it and go, ”Hey, I have it pretty good,” you tell yourself you got lucky. You met the right person, went to the right school, and landed an internship at the right startup; whatever it is, there's a feeling that it's out of your control. But, when you don’t understand nature or luck, you feel it’s impossible to reproduce it again. This was part of how I felt initially, but having gone through everything I’ve gone through over the last ten years or so, I don’t just mean a struggle, but all of my experiences have placed me in a position where I’m much more confident even though my hands still hurt and bother me to this day.

Despite my injury, I still try to maintain a bulletproof growth mindset. I constantly ask myself why I shouldn't make more money every month. The worst part is I truly do not know whether this is a ‘good’ mindset to have. Should I abstract to something like ‘focusing on the process’ and results will come? Should I be working with new clients to solve new problems? Maybe this is part of what caused my injury in the first place and the poison I was leaning into. I truly believe all I need to succeed is my hands, brain, and laptop. As long as I have these three things, I’ll be fine.

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I write about a mix of consulting, open source, personal work, and applying llms. I won't email you more than twice a month, not every post I write is worth sharing but I'll do my best to share the most interesting stuff including my own writing, thoughts, and experiences.

Picking Metrics and Setting Goals

I think people suck at picking metrics and setting goals. Why? Because they tend to pick metrics they can't actually impact and set goals that leave them feeling empty once they've achieved them. So, let's define some key terms and explore how we can do better.

Hiring MLEs at early stage companies

Build fast, hire slow! I hate seeing companies make dumb mistakes, especially regarding hiring, and I’m not against full-time employment. Still, as a consultant, part-time engagements are often more beneficial to me, influencing my perspective on hiring. That said, I've observed two notable patterns in startup hiring practices: hiring too early and not hiring for dedicated research. Unfortunately, these patterns lead to startups hiring machine learning engineers to bolster their generative AI strengths, only to have them perform janitorial work for the first six months of joining. It makes me wonder if startups are making easy-to-correct mistakes based on a sense of insecurity in trying to capture this current wave of AI optimism. Companies hire Machine learning engineers too early in their life cycle.¶

Many startups must stop hiring machine learning engineers too early in the development process, especially when the primary focus should have been on app development and integration work. A full-stack AI engineer can provide much greater value at this stage since they're likely to function as a full-stack developer rather than a specialized machine learning engineer. Consequently, these misplaced machine learning engineers often assist with app development or DevOps tasks instead of focusing on their core competencies of training models and building ML solutions.

After all, my background is in mathematics and physics, not engineering. I would rather spend my days looking at data than trying to spend two or three hours debugging TypeScript build errors.