A developer's blog featuring thoughts ideas and all things engineering.
I've spent the last 2 years building and interviewing candidates for AI Engineering roles. So I've been fortunate enough to watch the career track evolve from being a fringe amorphous role fueled by hype to a growing discipline in and of itself. AI Engineering as a
AI Assisted/Agentic programming are pretty common place at this point. The growing sentiment seems to be that if you can't find some sort of benefit in your workflow, it's more of a skill issue than a problem with the tools. Whether you believe this to
Over the weekend, I had some interesting discussions about the impacts AI on developer growth and skill atrophy. Much of that discussion was inspired by Mo Bitar's video on the subject. Within my small group, we couldn't come to a consensus on its impacts. We all
I recently got my hands on a GMKTec Evo X2 for local model inference. Here's my hardware details nish@gmktec-evo-x2:~$ sudo lshw -short H/W path Device Class Description ========================================================= system NucBox_EVO-X2 (EVO-X2-001) /0 bus GMKtec /0/0 memory 64KiB BIOS /0/b
The DORA State of AI Assisted Software Development report came out recently. It's a massive 142 page report that details analysis done by the DORA team. It captures trends and observations covering a 5000 participant study that focuses on AI Adoption and tool use in the Software industry.
OpenAI's dev day was today. While I wrote up a short summary of what was announced on bluesky , one of the major announcements was the AppSDK for ChatGPT. It looks like OpenAI plans to position ChatGPT as a platform for the future not unlike the Google Play and
A Norm of a vector \(\vec{v}\) describes the magnitude or size of a vector. It is usually denoted as \(||\vec{v}||\). There are a few common norms worth discussing. Eucledian Norm (L2 Norm) Let's consider a vector v = [3, 4] we can calculate the Eucledean norm as,
A fantastic deep dive into the seahorse emoji phenomena [1] was recently published by Theia [2] . It's engaging, well presented and worth reading. The post presents a case using meta-llama/Llama-3.3-70B-Instruct . However I wanted to verify this behavior with smaller models which unsurprisingly
Last week I happened to be in a discussion that involved getting an LLM to generate JSON reliably. A major frustration expressed was that no matter how much they tried the model would often fail to follow instructions during generation. I pointed out that most major vendors support some variant
Phi-4 Reasoning Microsoft recently released the phi-4 reasoning model as well as its technical report. They explore using supervised finetuning as well as synthetic dataset curation to train phi-4 a 14B parameter model to compete with and often outperform significanly larger models such as DeepSeek-R1-Distill-
While performing some routine maintenance of my Ubuntu server, $ docker compose pull $ docker compose up -d I ran into an interesting situation where nginx-proxy-manager failed to serve my blog properly, I wasn't sure what the issue was but these types of issues are usually solved with
Gaussian noise is data that is added to a signal in order to introduce a distortion. The data follows a Gaussian/Normal distribution. It's a well understood distribution often used to introduce noise to training data as an augmentation technique. Generating noise to add to a signal is
I recently put together a new PC build. It's primarily aimed at machine learning so I wanted to get a case that had really great airflow. I asked around and was directed to a list put together by GamersNexus [1] highlighting their top cases of the year. The
DuckDB recently shipped with a new local UI package [1] . It allows users to visualize DuckDB databases as well as run SQL queries through embedded notebooks. You can start the UI by running duckdb -ui in the terminal which starts an http server on port 4213 by default. $ duckdb -ui
Vector projection is the process of projecting one vector onto another. In simple terms, it is the adjacent side of a right triangle with the original vector as the hypotenuse.