Posts

There’s nothing quite like the clarity of losing your job on a friday that forces you to contend with the bigger question; who and what kind of future do you want to build for? For the last year, I’ve been deep in the local-first ecosystem, learning alongside peers and building the infrastructure to power local-first software. Amidst the hype of AI and agent-driven code, I’ve witnessed a quiet hum of folks demanding to take back control, of their data, of their tools and of the role software has in their everyday lives. Local-first is not just a software methodology, it is a philosophical movement. It’s about building software for people in the context of where they’re at. ...

As the saying goes there is no cloud, just someone else’s computer. Simplistic as it is, the saying captures a universally accepted reality: app data is better off hosted elsewhere living on someone else’s hardware (I’m looking at you GCP and AWS). The issue with this cloud-first sentiment is that it relegates the cloud as a panacea. Sure, giving control to the cloud frees us from the burden of bootstrapping infrastructure and managing complex ops, but it comes with its own set of tradeoffs. Chief among them? The total loss of control over our own data. Not to mention the added reliance on third-party uptime (looking right at you us-east-1). ...

The rise of the local-first movement was no anomaly. For years, browsers were no match for native environments that offered superior performance and offline capabilities. The gap was painfully obvious, native apps could store gigabytes of data and had access to a whole file system while browsers barely scraped by with megabytes. Modern browsers have since caught up over the last few years and the divide between browser and native environments has significantly blurred. There were many developments that gave rise to this, chief among which are: larger browser storage capacity, and new storage APIs. Let’s examine these. ...

In my last post, I mentioned that what makes an app local-first is its ability to keep running even when a connection falters. At first glance, this might look a lot like the offline-first movement that arose alongside the progressive enhancement wave of the mid to late 2010s. But there’s a subtle distinction. Offline-first apps focused primarily on staying functional during network interruptions but the server remained the primary data source. Data in this context is stored locally until a connection is restored, after which the locally stored data is deleted in favor of the remote store. A restored network connection progressively enhanced the experience and syncing only happened when there was new data created during the interim offline period to upload. ...

I’m frequently amused by how often local-first software gets mistaken for community initiated software. The ethos is spot on, but the confusion is revealing: cloud first has become the de facto standard for building apps. Local-first challenges this notion and subverts the dynamic between cloud and device. It puts the device at the center of operations. In this way, local-first apps remain operational despite an unstable connection unlike cloud-first ones. This of course doesn’t disregard the cloud completely. In a local-first model, the cloud shifts to the role of facilitator, ensuring data is synchronized across devices and sessions. ...

I’ve been pretty quiet about my work life lately. But spoiler alert, I have a job (and have been at it for the last 3 months)! If you spoke to me earlier this year or read a previous post about my job search, you’d have heard that the journey to a job post layoff for me was an emotional rollercoaster. Interviewing was not a strength of mine. I spent months getting wooed by companies impressed by my resume only to get rejected after yet another failed technical. It was horrifyingly depressing. But just as I was starting to lose steam, I got my break and landed a dream role, in the most unexpected (but unsurprising) of ways—in person, at a conference. ...

A few years ago, I received news of a professor’s passing in the most bizarrely impersonal way we tend to receive news these days: via a twitter mention from a college ex I hadn’t spoken to in years. The memorial service was set for that weekend in Central Massachusetts where he and his family lived. At the time, I was living in Cambridge, which was just a short train ride away. But I never made it past Back Bay. ...

I got laid off for the first time back in September (surprise!) and it took a giant toll on me emotionally. For the last 10 or so years I’d managed to muscle my way through engineering jobs despite not having a formal degree in CS. I’ve had the immense privilege of working at some really cool companies, working my way from the front of the frontend through the bowels of the stack and (for a brief moment) into the cold heart of bare metal. I’ve worked on product, systems, support tooling, growth/sales pipelines, billing, and miscellaneous developer workflows. In that time, I’ve written code in Ruby, JavaScript, TypeScript, Golang, Elixir and (some) Rust and worked with some crazy intelligent people. I’ve given talks internationally and written blog posts about various deeply technical pursuits. While I’m by no means an expert at all or many of things, I share this to say that I have a chunk of experience under my belt. ...

2024 was the year when I finally transitioned from surviving to thriving. With everything that transpired over the last few years, I got lost in the chaos of my reality and it’s taken me a second to “get back”. I’m not quite who I used to be, but I’ve become a version of myself that I’m quite pleased with, same same but different. The year came and went, for the most part, without incident. And (for once) I have no one to blame but myself for any and all shenanigans I found myself in. I grew, I learnt, and successfully averted any major crisis. In no specific order, here’s everything that happened this year in a nutshell: ...

Change is inevitable, especially so in applications that ebb and flow with system changes and user requirements. Generally, changes are codified in the form of an event; an event like a ddos attack for instance triggers a reaction or a response from one or more nodes, which ultimately mutates the overall state of the universe in a system. Undoubtedly, events rarely happen as one offs. At any given time, a sequence of events flows through the system. Whether it be a cascade of related events or multiple isolated events, the system is consistently responding and adapting. ...