Alternatives
Products that do what Recursive COW Pages in Userspace does
- 1IW
https://www.manning.com/books/data-oriented-programming-in-j... This book is a distillation of everything I’ve learned about what effective development looks like in Java (so far!). It's about how to organize programs around data "as plain data" and the surprisingly benefits that emerge when we do. Programs that are built around the data they manage tend to be simpler, smaller, and significantly easier understand. Java has changed radically over the last several years. It has picked up all kinds of new language features which support data oriented programming (records,…
2024
- 2
- 3MM
Hi HN! Erik here from Pig.dev, and today I'd like to share a new project we've just open sourced: Muscle Mem is an SDK that records your agent's tool-calling patterns as it solves tasks, and will deterministically replay those learned trajectories whenever the task is encountered again, falling back to agent mode if edge cases are detected. Like a JIT compiler, for behaviors. At Pig, we built computer-use agents for automating legacy Windows applications (healthcare, lending, manufacturing, etc). A recurring theme we ran into was that businesses already had RPA (pure-software scripts), and…
2025 · github.com
- 4PP
2019 · publisheet.com
- 5IR
Hey HN! I built a proof-of-concept for AI memory using Git instead of vector databases. The insight: Git already solved versioned document management. Why are we building complex vector stores when we could just use markdown files with Git's built-in diff/blame/history? How it works: Memories stored as markdown files in a Git repo Each conversation = one commit git diff shows how understanding evolves over time BM25 for search (no embeddings needed) LLMs generate search queries from conversation context Example: Ask "how has my project evolved?" and it uses git diff to show actual…
2025 · github.com
- 6AF
2016 · github.com
- 7DB
2018 · dpage.io
- 8
- 9PA
2018 · github.com
- 10
- 11BA
Hi HN, Erik here. Today we launch Butter, an OpenAI-compatible API proxy that caches LLM generations and serves them deterministically on revisit. Since April, we’ve been working on this concept of “muscle memory,” or deterministic replay, for agent systems performing automations. You may recall our first post in May, launching a python package called Muscle Mem: https://news.ycombinator.com/item?id=43988381 Since then, the product has evolved entirely, now taking the form of an LLM Proxy. For a deep dive into this process, check out:…
Oct 2025 · docs.butter.dev
- 12RS
2021 · github.com
- 13SY
2020 · sheethub.io
- 14
- 15NM
2018 · github.com
- 16PA
2019 · abhin4v.github.io
- 17GP
2016 · github.com
- 18LW
2017 · github.com
- 19SS
I'm developing a storage system for versioning data at the subfile level, especially well suited for SSDs due to its log-structured COW nature. It implements a novel versioning algorithm called sliding snapshot, a diff-algorithm which makes use of our stable record-identifiers and optionally hashes, another diff algorithm for importing similar XML-documents as a versioned resource as well as novel XPath axis to navigate not only in space, but also in time. Recently, I've implemented a higher level, asynchronous REST-API with Kotlin (Coroutines) and Vert.x in a seperate module. The system is…
2018
- 20AL
Raymond here from Butter.dev, an LLM response cache built as a chat-completions proxy. Today we're launching a key feature for the platform: the ability to generalize on dynamic, templated inputs. Caching at the HTTP request level has the obvious problem of generalizability. Nearly no request is identical, due to templated variables (like names) and metadata (like timestamps), so exact-match cache lookups rarely hit. We solve this at Butter by using LLMs to detect dynamic content in requests and derive their inter-relationships, allowing the cache entry to be stored as a template + variables…
Jan 2026 · blog.butter.dev
- 21SO
2015 · github.com
- 22MT
2024 · github.com
- 23OA
Owl is built a spaced repetition app. We built it for ourselves mostly because we were unhappy with Anki from a UX perspective, and are now releasing it to everybody else. It is super tiny, but - we think - also pretty good. You can add your own decks manually, or generate them from a PDF (think academic papers, which is how I use that feature) or a prompt. There are no emails except study reminders (when there are cards to study). You can also use our "AI tutor" to review cards conversationally. Looking forward to your feedback!
2025 · owl.cards
- 24ST
Hi HN! I'm Alex, a tech enthusiast who likes to build stuff from scratch. Often my programs have data to store or a configuration file to read and/or edit. Therefore, I design relational databases [1] and write SQL queries to manage complex data with relationships, and for other needs, I used to do unmaintainable hacks (custom file formats) with plain old files. But that was before I discovered Pickle [2], the Python data serialization module. A simple way to store a representation of memory-living data collections on local disk. Therefore, Pickle became my favorite way to store data,…
2022 · github.com
Ranked by how close each launch is in meaning, then by votes. Refine with a description →