2024¶

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.

If you want to know who I am, check out blog/whoami or my Twitter.

Losing My Hands Pt. 2: The Two Jasons

This is part of an ongoing series that discusses my experience of suffering an RSI during the COVID-19 Pandemic and the ongoing struggles and disruptions it still causes. You can read part one here. My goal here is to interrogate how the injury affected my values and my approach to life. You'll probably be disappointed if you're looking for a detailed medical report.

This comment partly inspired this installation of the series. This article isn't meant to be preachy but rather introspective of the value systems that shape me and many other men.

The Future of RAG: Generating Reports to Accelerate Decision Making

Motivation

Instead of just using Retrieval Augmented Generation (RAG) for question answering, which has limited value, the real impact lies in leveraging RAG to automatically generate reports that can accelerate decision making and align teams. People are willing to pay for high-quality reports that provide valuable insights and save time.

Positioning

This capability should be marketed as a way to "make decisions faster" and "get aligned", rather than merely saving time on simple question answering. The focus should be on the substantial value provided by the generated reports in terms of improved decision making and team coordination.

Examples

1. Financial Research Reports
2. Take financial documents for a company over time and automatically generate reports in the format of Morning Star or other equity research firms
3. Replace time-consuming manual research work
4. Interview Debriefs
5. Automatically generate a single comprehensive interview report from multiple interview transcripts
6. Capture key points, strengths, weaknesses, and areas for follow-up
7. Save time and improve alignment in hiring decisions
8. User Research Synthesis
9. Distill insights from large volumes of user research interviews into standardized reports
10. Include pros, cons, NPS scores, and other key metrics
11. Quickly identify trends and actionable insights
12. Personal Data-Driven Form Filling for Applications
13. Use AI to process an individual's personal data (e.g., emails, documents, social media) and automatically fill out complex forms and applications
14. Similar to how Indexify can generate reports from disparate data sources, AI could analyze personal data to populate fields like work history, skills, interests, etc.
15. Streamline tedious form filling processes and ensure consistency across applications

Mechanics

1. Define standard report templates (e.g., as YAML files) with the desired sections and descriptions
2. Indexify queries the indexed documents to populate the reports
3. Use techniques like automatically extracting question-answer pairs from interview transcripts to improve results

By focusing on the value of generating comprehensive reports and automating complex data extraction tasks, Indexify can differentiate itself from simple RAG question answering. It can deliver substantial benefits to businesses in terms of improved decision making, time savings, and team alignment, while also showcasing the potential for AI to streamline personal data-driven processes like form filling.

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.

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.

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.

Data Flywheel Go Brrr: Using Your Users to Build Better Products

You need to be taking advantage of your users wherever possible. It’s become a bit of a cliche that customers are your most important stakeholders. In the past, this meant that customers bought the product that the company sold and thus kept it solvent. However, as AI seemingly conquers everything, businesses must find replicable processes to create products that meet their users’ needs and are flexible enough to be continually improved and updated over time. This means your users are your most important asset in improving your product. Take advantage of that and use your users to build a better product!

Unraveling the History of Technological Skepticism

Technological advancements have always been met with a mix of skepticism and fear. From the telephone disrupting face-to-face communication to calculators diminishing mental arithmetic skills, each new technology has faced resistance. Even the written word was once believed to weaken human memory.

Technology	Perceived Threat
Telephone	Disrupting face-to-face communication
Calculators	Diminishing mental arithmetic skills
Typewriter	Degrading writing quality
Printing Press	Threatening manual script work
Written Word	Weakening human memory

Levels of Complexity: RAG Applications

This post comprehensive guide to understanding and implementing RAG applications across different levels of complexity. Whether you're a beginner eager to learn the basics or an experienced developer looking to deepen your expertise, you'll find valuable insights and practical knowledge to help you on your journey. Let's embark on this exciting exploration together and unlock the full potential of RAG applications.

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