Pinned Posts

Deep Dive into Claude Code Harness - Chapter 1: Memory Management

What makes the Claude Code harness best-in-class? Let's dive into its leaked source code to learn about the rigorous engineering within. Turns out, its memory management is remarkably similar to the wiki system described in my previous post.

Introducting Wiki-Skills: Agent Skill for Managing Markdown Vaults

Kaparthy shared a viral note about a building an LLM-managed 'personal wiki' - which I interpret as a specific instance of a locally stored markdown vault. Here, I present Wiki Skills - a set of agentic Skills that captures the process of creating, querying, and updating this knowledge vault.

Autoresearch: Autonomous Hill-Climbing for Any Optimizable System

Run optimization experiments while you sleep

Coffee Water Composition

TL;DR: Boston’s tap water is terrible for making high quality coffee (wrt aroma and taste). No need to start at zero with deionized water – spike your water to get better results. In these notes, I aim to derive a recipe for optimizing my flat whites using Boston’s (filtered) tap water.

A Review on Agentic Memory

Managing context for long-running agents, across sessions, or swarms of agents, remains an active area of research and development. This is a survey of the current landscaspe in the world of Agentic memory.

Python Tooling

An index of relevant Python tooling references in this blog

Tower Defense

A Javascript version of the original Flash-based Tower Defense, circa 2008

Pytest Markers & Parametrization

Pytest markers are like tags. Tag your tests to keep them organized. Use markers to indicate test priority, or group them by performance, integration, or acceptance. Use them to skip tests under certain conditions, or mark them as expected failures. Use parametrization to run your test under different parameters.

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Pyproject.toml Template

If you don’t already have a pyproject.toml file for your existing project, you should. It is required to use with pip install . and with poetry. Let’s take a look at what a pyproject file looks like.

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Intro to Python Imports and Modules for Matlab users

When you write a function in MATLAB, each function typically is a single .m file. So let’s say you’ve written my_function() and saved that function as my_function.m. To gain access to this function, you would use the addpath function to add that script to your MATLAB’s search path. After calling addpath(/path/to/myfolder/), which contains myfunction.m, then you can call my_function(). How do these function imports work in Python?

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