I've been busy embedding myself in the intersection of biotech and climate tech for the past few months by reading, writing, and talking with as many people as I can. I've been itching to get back to my coding roots though, and so decided to hack together a quick project over the course of a few days. I wanted to work on something that would allow me to brush up on my front end development skills while also being biology related. Thus, I developed a simple protein visualization app. The app:

I’ve been exploring the synthetic biology space due to its potential to improve human health and mitigate climate change. My initial foray was into “traditional” synthetic biology companies that used genetically modified microbes to produce a specific target of interest. Cell free industrial biomanufacturing was a space I frequently heard about, but didn’t explicitly dig into until hearing about Cascade Biocatalysts via the Grow Everything podcast. I actively dislike using clickbait phrases like “revolutionize the space” or “breakthrough technology”, but I think this company and cell free biomanufacturing as a space are definitely worth keeping an eye on.

As mentioned in my last blog post, I’ve been exploring the synthetic biology space from the perspective of “how do I make technology that can act as a lever to move this ecosystem forward?”. My hunch is that a space projected to go from 13.09 billion in 2022 to 55.37 billion dollars by 2030 will surely need picks and shovels companies to support that kind of growth.

In my last blog post I wrote about the four pillars of alternative protein technology: cultivated meat, precision fermentation, plant based protein, and molecular farming.

As I researched more about precision fermentation, I stumbled into its overarching domain of synthetic biology, “a field of science that involves redesigning organisms for useful purposes by engineering them to have new abilities.”

Ever since I read this fantastic article on cultured meat half a year ago, I’ve been absolutely hooked on the alternative protein space. The industry is relatively nascent and very complex, with few clear beginner friendly resources to guide newcomers into the space. As someone with no biology/food science background, I have the unique opportunity to write about my learnings from a layman’s perspective. This article will give the reader an overview of the alternative protein space, its incredible potential, and some of its problems. I ultimately hope this article increases the number of people working in this space, or at minimum increases readers’ willingness to buy alternative protein products.

I’ve long believed that the majority of the crypto ecosystem is a scam, and truth be told I still believe that. However, in the Work on Climate slack there are similarly crypto-skeptic folks that are sold on the regenerative finance movement (frequently referred to as ReFi), with many of them referring to Regen Network as a prime example of a fantastic project. That piqued my curiosity enough to listen to the Regen Network’s founder, Gregory Landua, interview with the ReFi Podcast. Greg’s genuine desire to improve the world, his clear track record of having done so, and his conviction in ReFi convinced me to revisit the ReFi movement without any prejudices and analyze the movement from first principles.

If we spend 1/3rd of our waking life working, then why not work on something that matters? This simple question drove me to reevaluate my career and long term vision, convincing me to leave my job at Robinhood and dedicate my career to fighting climate change. Finding my next role was harder than expected, so I wanted to write down some lessons I learned along the way in case they could be helpful for others.

What we work on matters, and incremental improvements, no matter how small, have compounding effects. I’ve decided to put my efforts towards fighting climate change, and to anyone who reads this, I hope you will too. The problem is intimidatingly massive, but with that size comes incredible opportunities for impact and innovation. In this article I hope to summarize what I’ve learned so far about the energy industry and the current landscape of companies tackling these issues, so anybody like me, a traditional software engineer with no background in energy or climate change, can get caught up to speed a bit quicker.

*Blog post written at work for Robinhood

The past two years have been an exciting time for Robinhood engineering as we’ve launched new products to millions of customers and scaled our operations to meet the enormous demand. During this rapid growth period, we spun up the Load and Fault team to increase product safety and reliability for our customers. In this blog post, we’ll be looking at how this team tackles daily load testing and the core principles that inform our decision making process.

I still remember the exact moment in August of 2020. I, a "tech lead" just one year out of college, had just received a meeting invite to the biweekly software platform tech lead/engineering manager meeting. The meeting was filled with Senior and Staff engineers that were revolutionizing the computer industry when I was still crawling in my diapers.

I want to make a difference. One way I tried doing so was by making a reddit bot, called Lookoutt, that regularly scanned secondhand websites and notified users on reddit when a listing matching their keywords was discovered. As a regular hunter of secondhand goods, I realized that manually scrolling through various secondhand websites every few hours was tedious and simply not feasible for your average user. The effort to find a specific item you wanted on a secondhand market was just not worth it when you could instantly find the item new on a normal retailer's website.

*or maybe just non-AWS deployment...

As a student in college, I never really understood the value of containers and Docker, technology that seemed to pervade every single company that I interned at. It's like when everyone tells you: don't eat that, it taste like crap. You take their word for it, but you never really understand until you try it and realize - oh it DOES take like crap.

I had successfully managed to store Grailed's history of sold listings (here if you missed it), but I still had a daunting task in front of me. How could I use the historical data to determine what was a good deal or not? There were so many factors to consider, such as clothing condition, style, brand, item type, and even purchase time: an item that is currently hot might not have necessarily been hot a few weeks ago.

I've always heard the common adage: "one man's trash is another man's treasure". However, anyone that has gone online secondhand shopping knows that the usual reality is people think their trash is another man's treasure, and are sure to price it as such...