Wil - Interjected Future

Wil

Lab note #054 Visualizing Execution

Lab note #054 Visualizing Execution

One of my main goals is to make non-CRUD backend pipelines more visible. I didn't think nodes and wires programming was the way to go, but unconsciously, I envisioned just showing the results of a cell next to the cell, like regular computational notebooks. But my underlying assumption was that

A simple way to understand CRDTs

A simple way to understand CRDTs

🔰If CRDTs (Conflict-free Replicated Data Types) are new to you, check out this previous post. There's a simple way to understand CRDTs: It leverages algebra to unmix the inevitable mixing of data when syncing over an unreliable network. Why are networks unreliable? For one, it'd be really expensive to build

Lab note #053 Breaking from structured programming

Lab note #053 Breaking from structured programming

I've been a bit anxious about the pace of progress these last three weeks. I wanted to strike a balance between making practical progress and having a sound basis. This last week, I struggled with breaking from structured programming. * What do algebraic effects buy you? * What is the return value

The moats are in the GPT-wrappers

The moats are in the GPT-wrappers

Despite the disdain for "GPT-wrappers," it's currently where the value is accruing in the supply chain of value to the end-user with LLM-driven apps. Unless something changes with the foundational model companies approach the market, the GPT-wrapper application layer is where the value accrues, hence where the money will be

Lab note #052 Epx for everything

Lab note #052 Epx for everything

This past week, I worked through more confusion on my part. * Consolidated the representation of an algebraic effect with the React-like components (Fibers) * Worked out a solution for resuming fibers after getting a result back from from the algebraic effect. (Then block) * Use a data description of all cells (Epx)

TIL Poor man's quoting in Python

Today I Learned

TIL Poor man's quoting in Python

In Lisp, you can quote an expression to delay its evaluation while passing it around as a value. In Python, this means in practice, I want a function that looks like it's executing, but reality, I'm delaying its actual execution. I can use decorators to achieve this. # A thunk-based Efx

Lab note #051 Cell composition and lazy evaluation

Lab note #051 Cell composition and lazy evaluation

Last week, I merged the runtime worker into the kernel worker. Originally, I wanted that to run multiple kernels at once, so users can run languages in a mix of cells, or they can run more than one cell in parallel. It was too hard to trace execution over a

Lab note #050 Prior art of a React-like runtime

Lab note #050 Prior art of a React-like runtime

I fell short this week in that I didn't do what I said I was going to do. Instead, of writing code, I went down the incremental rabbit hole. It was innocuous at first, but ended up being a full deep dive, mostly into the work of Steven Wittens (aka

Lab note #049 Survey of Reactive and Incremental Programming

Lab note #049 Survey of Reactive and Incremental Programming

For a while now, I've been circling the drain on the Tools for Thought space and all the topics related to it. One large topic is reactivity, and not too far behind is incremental computation. They're two sides to a coin, so it's hard to disentangle them from each other.

Lab note #048 Basic Effects Done, Reactivity Next

Lab note #048 Basic Effects Done, Reactivity Next

I spent most of the week getting a basic algebraic effects runtime working. The initial version is single-threaded, synchronous, no typing, with a single yield from handlers. For now, it's good enough for building the proverbial skateboard. Only during implementation did I run into design questions I wouldn't have had

Lab note #047 Progress on Notebook

Lab note #047 Progress on Notebook

My progress on Crafting Interpreters halted when I was researching how Algebraic Effects were implemented, once I realized that I might not need all the gory details. The part I wanted to get to was understanding how closures were implemented, especially if they were relevant to getting Algebraic Effects to

A mental model for `yield from`

A mental model for `yield from`

❓Prompt: teach me the difference between yield and yield from in python. I understand yield from can replace the iterative nature of reading from a generator to get all the results. But as I understand it, it also covers a lot of other edges too, when you send stuff into

Lab note #046 Algebraic Effects for Notebook Cells

Lab note #046 Algebraic Effects for Notebook Cells

The notebook that I want to build and use has pure functional cells. Functional cells are where the output only depends on the input. * No need to figure out the correct execution order for the notebook cells to get it in a working state. * For any change, only dependent cells

Lab note #045 From Database to Notebook

Lab note #045 From Database to Notebook

I spent the last month doing some contract work, both to pay the bills and get some perspective on how web devs are working nowadays. I've been away for about two years and some things have changed. I worked on a Next.js stack, and I'm honestly a little horrified

Launching a Digital Zine

Launching a Digital Zine

While I've been working on systems programming and local-first software, I've resisted diving into building with LLMs for the better part of 8 months. But I think it's too much of a fundamental shift to ignore. I won't be ignoring the groundwork that I've been doing on CRDTs and Prolly

Empowering End Users with Local Models

Empowering End Users with Local Models

I pulled down Llama 3.1 7B for a long flight recently. It seemed magical in the same way downloading all of Wikipedia seems--like taking an entire universe with you. The missing piece is the context to steer the LLM. We need a Microsoft Access of RAG and LLM system

Lab note #044 Sailing by cache-oblivious data structures

Lab note #044 Sailing by cache-oblivious data structures

As part of biasing towards action, I thought it was time to reimplement the Prolly Tree in Zig. I wanted to focus on being cache-friendly this time, now that I have lower-level control. But that resulted in a deep dive into data-oriented programming. The question is how to represent a

Where is the sandbox in your code base?

Where is the sandbox in your code base?

I was watching Casey Muratori and the Primeagen the other day, and they were talking about the high-level architectural design of the core data inside of Primeagen's game. What Casey says sounds counter-intuitive for anyone from a traditional OOP software background. He suggests not committing to an organization of data

Lab note #043 Merkle CRDT protocol

Lab note #043 Merkle CRDT protocol

My adherence to immutability has put me on the hard path for everything so far. Not just for the unicit Prolly tree, but also for the CRDT. Most practical CRDT libraries use an op-based CRDT or a delta-based CRDT, but many do not keep the entire history around. I think

Visual Programming Should Start in the Debugger

Visual Programming Should Start in the Debugger

Just like CAD didn't make everyone an industrial designer, visual programming isn't going to make everyone a programmer. Whether textual or visual, there'd still be a lot of underlying concepts (and how they are composed) to learn. But still, I think it's underexplored. Most visual programming paradigms focus on coding--the

Lab note #042 LLM Zine

Lab note #042 LLM Zine

I started working on making an LLM Zine. Not to worry, the work on the database is still in the works, but this has been a burgeoning interest and opportunity. LLMs are a fundamental technological breakthrough, and the effects of this technology will take at least a decade to work

Recurse Center Return Statement

Recurse Center Return Statement

💡The Recurse Center encourages recent graduates to write about their experience in the form of a Return Statement. Below is mine. The 12-week experience at RC did remind me of the story of the tall, strong, and unbendable Oak that towers over the short, thin, and flexible Reeds. On an

Lab note #041 Two flavors of Op-based CRDTs as a baseline

Lab note #041 Two flavors of Op-based CRDTs as a baseline

I've now implemented an Op-based and a Pure op-based CRDT. I couldn't quite make the leap before to merkle-based CRDTs. While vectors clocks are mechanically simple, I wasn't quite sure how they mapped to a merkle-DAG node if replica IDs weren't available. After seeing them in action, I'm fairly certain

Lab note #040 Hitting a wall and going back to basics with CRDTs

Lab note #040 Hitting a wall and going back to basics with CRDTs

This continues my exploration into CRDTs, beyond the typical tutorials. The more I looked, the more threads there were to pull on. I currently have a couple of lines of questioning to answer: * How do we compose CRDTs so they both converge to a single state without coordination but with

Lab note #039 Semantics of Composed CRDTs

Lab note #039 Semantics of Composed CRDTs

After the implementation of the Prolly Tree, I set about writing an immutable map. It was pretty straightforward as most of the heavy lifting is done by the Prolly Tree implementation. The immutable map just keeps a simple list of roots after every change. There are a bunch of improvements