I played around with the Nemotron Lightning 30b model this week. It is one of the most affordable models on the market, at approximately 25% of the price of OpenAI’s ChatGPT Luna model. At the time of this article, Nemotron Lightning costs just $0.05 per million input tokens and $0.20 per million output tokens.

I tested it for my usecase of proofreading my writings. And, well, it did terribly. I had a coding agent evaluate it against DeepSeek v4p1 Flash (also ~4x the price) as a baseline, and what my AI said about Nemotron

I spent much of yesterday pouring my mental energy into designing a better AI-assisted code review process. Then I threw it away.

What I learned is that you shouldn’t build every idea you have. I thought I had found a great way to improve the code review process. When I tried to say exactly what the system would improve, the answer was: not much. It was too complicated for the improvement it offered over an agent skill. I didn’t notice this when I was designing it. I had to step away and stop thinking about it before I could see the full cost of building it.

I started using AI coding agents in March of 2025. I’ve always had personal projects before. But adopting AI agents completely changed the scale of my codebase. I am writing tools, web apps, and automations that I never would’ve had the time or energy to write myself. Today, I have more AI generated code in my codebase than code I wrote myself.

This is what Claude says about the growth of my private repos.

Generative AI 2024 Retrospective

2024 witnessed a parade of increasingly more powerful AI model releases, culminating in OpenAI’s groundbreaking “o3”. While I’m certain these advancements really are significant, I don’t think they have translated to noticeable improvements for the average user.

What people are paying attention to, though, are the really amazing product features that are coming out of Anthropic and Google. I’ve heard a lot about people building software Claude’s Artifacts. And Google’s Deep Research product, released a few days ago, has just completely changed search.

This is a review of Open WebUI, an extensible and user-friendly self-hosted WebUI for LLMs.

I recently decided to run my own UI layer for LLMs, as I have some exciting ideas. For those who are not familiar with chatbots, their architecture basically looks like this:

While I’m pretty good at customizing the middleware, I’m not as skilled at customizing the UI layer.

I tried writing my own UI at first, but I quickly gave up when I realized it was beyond my skills as a frontend developer. The next thing I did was look into open-source solutions. There were a lot of choices, but I narrowed them down to these three:

I had two weeks off at the end of 2022. Telesign closed its operations on the last week of 2022 to give employees well-deserved time off for a year of hardwork and I took another week off in addition to that. Like many technologists, I became captivated by OpenAI’s release of ChatGPT in 2022, and I spent a lot of the last two weeks exploring what OpenAI has to offer.

ChatGPT is a chatbot developed by OpenAI. It has been widely recognized for its impressive capabilities, such as imitating human writing, transforming plain English into code, and making glaringly stupid mistakes. The underlying technology of ChatGPT is a machine learning model known as GPT-3. This model is designed to predict how a human might continue a previous piece of text. For example, given what I’ve written so far, GPT-3 predicted what the rest of this blog post will look like: