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The article discusses the importance of keeping an engineering notebook, highlighting its benefits for tracking ideas, documenting progress, and building a professional record. It provides practical tips on how to effectively use and maintain an engineering notebook.

The article explores the concept of 'nothing' and its philosophical implications, delving into the nature of emptiness, the history of the void, and the challenges of defining and understanding 'nothing' in the context of physics and metaphysics.

The article discusses the use of the Zstandard compression algorithm for text classification tasks, highlighting its potential benefits over traditional methods like GZIP in terms of compression ratio and speed.

https://fosdem.org/2026/schedule/event/7ZJJWW-fluorite-game-...

ChatZ.ai is a conversational AI assistant that aims to provide helpful and engaging interactions. The platform allows users to chat with the AI on a variety of topics, and it leverages natural language processing to understand and respond to user input.

The article explores the connections between the intricate craft of Kanchipuram sari weaving in India and the development of artificial intelligence (AI), highlighting the complex cognitive processes involved in both traditional textile production and modern machine learning.

The article discusses the history and technical details of the Telnet protocol, which was used for remote access and terminal emulation on early computer networks. It explains how Telnet worked, its role in the development of modern networking, and its continued use in certain specialized applications despite the rise of newer protocols.

Creator here. Hologram compiles Elixir to JavaScript to run in the browser, enabling full-stack development in pure Elixir - and soon, Local-First applications.

This release is a milestone for our porting initiative. 49 contributors ported 150 Erlang functions across 19 modules, pushing client-side Erlang runtime coverage from 34% to 96% and overall Elixir standard library readiness from 74% to 87%.

This means the vast majority of Elixir standard library functions needed for full-stack web and basic local-first apps now work in the browser - string processing, collections, sets, binary operations, Unicode normalization, math, time operations, file path handling, and more.

Beyond porting, the release includes enhancements, bug fixes, and infrastructure groundwork.

Happy to answer any questions!

NetNewsWire, a popular open-source RSS reader, celebrates its 20th anniversary, reflecting on its history and enduring popularity as a go-to tool for staying up-to-date with online content.

The article discusses the potential issues with large language models (LLMs), including their lack of transparency, inability to handle out-of-distribution inputs, and tendency to produce biased or nonsensical outputs. It argues that the current approach to LLM development needs to be reevaluated to address these problems.

Ireland has launched a pioneering basic income scheme for artists, providing them with a monthly payment for three years to support their creative work and address financial challenges faced by the arts community.

This article explores the evolution of backend engineering, discussing how the industry has transformed over the past decades and examining the key trends and technologies shaping the future of backend development.

The article discusses key lessons learned from the Zig programming language, including its focus on simplicity, flexibility, and providing low-level control over system resources. It highlights Zig's design principles and how they can inform the development of programming languages and software in general.

The article discusses concerns that the capabilities of the AI language model Claude are being 'dumbed down' by Anthropic, the company that created it. It suggests that the model's ability to engage in open-ended tasks and conversations is being restricted in order to make it more controlled and predictable.

Hi HN,

I’m Vincent from Aden. We spent 4 years building ERP automation for construction (PO/invoice reconciliation). We had real enterprise customers but hit a technical wall: Chatbots aren't for real work. Accountants don't want to chat; they want the ledger reconciled while they sleep. They want services, not tools.

Existing agent frameworks (LangChain, AutoGPT) failed in production - brittle, looping, and unable to handle messy data. General Computer Use (GCU) frameworks were even worse. My reflections:

1. The "Toy App" Ceiling & GCU Trap Most frameworks assume synchronous sessions. If the tab closes, state is lost. You can't fit 2 weeks of asynchronous business state into an ephemeral chat session.

The GCU hype (agents "looking" at screens) is skeuomorphic. It’s slow (screenshots), expensive (tokens), and fragile (UI changes = crash). It mimics human constraints rather than leveraging machine speed. Real automation should be headless.

2. Inversion of Control: OODA > DAGs Traditional DAGs are deterministic; if a step fails, the program crashes. In the AI era, the Goal is the law, not the Code. We use an OODA loop to manage stochastic behavior:

- Observe: Exceptions are observations (FileNotFound = new state), not crashes.

- Orient: Adjust strategy based on Memory and - Traits.

- Decide: Generate new code at runtime.

- Act: Execute.

The topology shouldn't be hardcoded; it should emerge from the task's entropy.

3. Reliability: The "Synthetic" SLA You can't guarantee one inference ($k=1$) is correct, but you can guarantee a System of Inference ($k=n$) converges on correctness. Reliability is now a function of compute budget. By wrapping an 80% accurate model in a "Best-of-3" verification loop, we mathematically force the error rate down—trading Latency/Tokens for Certainty.

4. Biology & Psychology in Code "Hard Logic" can't solve "Soft Problems." We map cognition to architectural primitives: Homeostasis: Solving "Perseveration" (infinite loops) via a "Stress" metric. If an action fails 3x, "neuroplasticity" drops, forcing a strategy shift. Traits: Personality as a constraint. "High Conscientiousness" increases verification; "High Risk" executes DROP TABLE without asking.

For the industry, we need engineers interested in the intersection of biology, psychology, and distributed systems to help us move beyond brittle scripts. It'd be great to have you roasting my codes and sharing feedback.

Repo: https://github.com/adenhq/hive

Researchers warn that WiFi technology could be repurposed into an invisible mass surveillance system, raising concerns about the potential for misuse and the need for greater security measures to protect individual privacy.

The article discusses the recent announcement that Heroku, a popular cloud platform, will be shutting down its free tier, raising concerns about its future among developers. However, the article argues that Heroku is not dead and remains a viable option for hosting web applications, highlighting its continued evolution and the company's commitment to its customers.

I've been building a tool that changes how LLM coding agents explore codebases, and I wanted to share it along with some early observations.

Typically claude code globs directories, greps for patterns, and reads files with minimal guidance. It works in kind of the same way you'd learn to navigate a city by walking every street. You'll eventually build a mental map, but claude never does - at least not any that persists across different contexts.

The Recursive Language Models paper from Zhang, Kraska, and Khattab at MIT CSAIL introduced a cleaner framing. Instead of cramming everything into context, the model gets a searchable environment. The model can then query just for what it needs and can drill deeper where needed.

coderlm is my implementation of that idea for codebases. A Rust server indexes a project with tree-sitter, builds a symbol table with cross-references, and exposes an API. The agent queries for structure, symbols, implementations, callers, and grep results — getting back exactly the code it needs instead of scanning for it.

The agent workflow looks like:

1. `init` — register the project, get the top-level structure

2. `structure` — drill into specific directories

3. `search` — find symbols by name across the codebase

4. `impl` — retrieve the exact source of a function or class

5. `callers` — find everything that calls a given symbol

6. `grep` — fall back to text search when you need it

This replaces the glob/grep/read cycle with index-backed lookups. The server currently supports Rust, Python, TypeScript, JavaScript, and Go for symbol parsing, though all file types show up in the tree and are searchable via grep.

It ships as a Claude Code plugin with hooks that guide the agent to use indexed lookups instead of native file tools, plus a Python CLI wrapper with zero dependencies.

For anecdotal results, I ran the same prompt against a codebase to "explore and identify opportunities to clarify the existing structure".

Using coderlm, claude was able to generate a plan in about 3 minutes. The coderlm enabled instance found a genuine bug (duplicated code with identical names), orphaned code for cleanup, mismatched naming conventions crossing module boundaries, and overlapping vocabulary. These are all semantic issues which clearly benefit from the tree-sitter centric approach.

Using the native tools, claude was able to identify various file clutter in the root of the project, out of date references, and a migration timestamp collision. These findings are more consistent with methodical walks of the filesystem and took about 8 minutes to produce.

The indexed approach did better at catching semantic issues than native tools and had a key benefit in being faster to resolve.

I've spent some effort to streamline the installation process, but it isn't turnkey yet. You'll need the rust toolchain to build the server which runs as a separate process. Installing the plugin from a claude marketplace is possible, but the skill isn't being added to your .claude yet so there are some manual steps to just getting to a point where claude could use it.

Claude continues to demonstrate significant resistance to using CodeRLM in exploration tasks. Typically to use you will need to explicitly direct claude to use it.

---

Repo: github.com/JaredStewart/coderlm

Paper: Recursive Language Models https://arxiv.org/abs/2512.24601 — Zhang, Kraska, Khattab (MIT CSAIL, 2025)

Inspired by: https://github.com/brainqub3/claude_code_RLM

This article explores a unique Japanese book from the 19th century that features intricate paper snowflake designs. The book showcases the artistic skill and attention to detail of its anonymous creators, providing a glimpse into the rich cultural heritage of traditional Japanese paper cutting techniques.

The article discusses the rising electricity prices across various regions and the potential impact on consumers. It examines the factors contributing to these price increases, such as supply chain disruptions, increased demand, and changes in energy policies, and explores potential solutions to mitigate the burden on households and businesses.

The article describes a microwave oven that spontaneously turned on without any user input, causing a potential fire hazard. It highlights the need for rigorous safety standards and testing for household appliances to prevent such unexpected and dangerous malfunctions.

The article discusses the GLM-OCR (Generalized Language Model for Optical Character Recognition) model, a deep learning-based approach to OCR that leverages large language models to improve accuracy and generalization across a wide range of text and image domains.

The article discusses the backlash surrounding Ring's Super Bowl ad, which appeared to depict a neighborhood search party hunting down an intruder. Critics argued the ad promotes a culture of surveillance and fear, raising concerns about the company's surveillance-focused products.

The article discusses the technical challenges of hacking the last Z80 computer ever made, the Sharp MZ-80K. It explores the process of understanding the hardware and software architecture of this vintage computer system and the innovative techniques used to extend its capabilities.

Latest archive link: https://archive.is/Qdq4x

Apple's internal testing of iOS 26.4, which includes updates to the Siri virtual assistant, has encountered issues, leading the company to focus on releasing iOS 26.5 with potential improvements to address the problems.

The only way to get a trust-less random value is to have it distributed and time-locked three ways, player, server and a future-entropy.

In the demo above, the moment you commit (Roll-Dice) a commit with the hash of a player secret is sent to the server and the server accepts that and sends back the hash of its secret back and the "future" drand round number at which the randomness will resolve. The future used in the demo is 10 secs

When the reveal happens (after drand's particular round) all the secrets are revealed and the random number is generated using "player-seed:server-seed:drand-signature".

All the verification is in Math, so truly trust-less, so:

1. Player-Seed should matches the player-hash committed

2. Server-Seed should matches the server-hash committed

3. Drand-Signature can is publicly not available at the time of commit and is available at the time of reveal. (Time-Locked)

4. Random number generated is deterministic after the event and unknown and unpredictably before the event.

5. No party can influence the final outcome, specially no "last-look" advantange for anyone.

I think this should be used in all games, online lottery/gambling and other systems which want to be fair by design not by trust.