Power Failure: The downfall of General Electric (Score: 151+ in 13 hours)
Link: https://readhacker.news/s/6v9ak
Comments: https://readhacker.news/c/6v9ak
Link: https://readhacker.news/s/6v9ak
Comments: https://readhacker.news/c/6v9ak
Gordon Wintrob
My review of Power Failure: the downfall of America's greatest company
Power Failure by William Cohan chronicles the spectacular collapse of General Electric, once America's most valuable company. From a $600 billion giant to near-bankruptcy, GE's downfall reveals how financialization and imperial CEOs destroyed a 130-year industrial…
Highlights from the Claude 4 system prompt (Score: 152+ in 14 hours)
Link: https://readhacker.news/s/6v96K
Comments: https://readhacker.news/c/6v96K
Link: https://readhacker.news/s/6v96K
Comments: https://readhacker.news/c/6v96K
Simon Willison’s Weblog
Highlights from the Claude 4 system prompt
Anthropic publish most of the system prompts for their chat models as part of their release notes. They recently shared the new prompts for both Claude Opus 4 and Claude …
Yes-rs: A fast, memory-safe rewrite of the classic Unix yes command (Score: 153+ in 11 hours)
Link: https://readhacker.news/s/6v9vE
Comments: https://readhacker.news/c/6v9vE
Link: https://readhacker.news/s/6v9vE
Comments: https://readhacker.news/c/6v9vE
GitHub
GitHub - jedisct1/yes-rs: 🚀 A blazingly fast, memory-safe rewrite of the classic Unix 'yes' command. Written in Rust! 🦀
🚀 A blazingly fast, memory-safe rewrite of the classic Unix 'yes' command. Written in Rust! 🦀 - jedisct1/yes-rs
Show HN: Lazy Tetris (Score: 150+ in 8 hours)
Link: https://readhacker.news/s/6v9Jz
Comments: https://readhacker.news/c/6v9Jz
I made a tetris variant
Aims to remove all stress, and focus the game on what I like the best - stacking.
No timer, no score, no gravity. Move to the next piece when you are ready, and clear lines when you are ready.
Separate mobile + desktop controls
Link: https://readhacker.news/s/6v9Jz
Comments: https://readhacker.news/c/6v9Jz
I made a tetris variant
Aims to remove all stress, and focus the game on what I like the best - stacking.
No timer, no score, no gravity. Move to the next piece when you are ready, and clear lines when you are ready.
Separate mobile + desktop controls
Lazytetris
Lazy Tetris
No stress, memory-optimized 3D Tetris variant.
Clojure MCP (❄️ Score: 152+ in 2 days)
Link: https://readhacker.news/s/6v458
Comments: https://readhacker.news/c/6v458
Link: https://readhacker.news/s/6v458
Comments: https://readhacker.news/c/6v458
GitHub
GitHub - bhauman/clojure-mcp: Clojure MCP
Clojure MCP. Contribute to bhauman/clojure-mcp development by creating an account on GitHub.
The Myth of Developer Obsolescence (Score: 156+ in 4 hours)
Link: https://readhacker.news/s/6vahS
Comments: https://readhacker.news/c/6vahS
Link: https://readhacker.news/s/6vahS
Comments: https://readhacker.news/c/6vahS
Alonso Network
The Recurring Cycle of 'Developer Replacement' Hype
AI isn't replacing developers, it's transforming them. Just as NoCode created specialists and cloud turned sysadmins into DevOps engineers, AI elevates engineers from code writers to system architects. The most valuable skill isn't writing code, it's designing…
The UI future is colourful and dimensional (Score: 150+ in 13 hours)
Link: https://readhacker.news/s/6v9vV
Comments: https://readhacker.news/c/6v9vV
Link: https://readhacker.news/s/6v9vV
Comments: https://readhacker.news/c/6v9vV
www.flarup.email
The Future is Colourful and Dimensional
On the return of texture, depth, and expressiveness in UI.
Get PC BIOS back on UEFI only system (Score: 151+ in 17 hours)
Link: https://readhacker.news/s/6v96E
Comments: https://readhacker.news/c/6v96E
Link: https://readhacker.news/s/6v96E
Comments: https://readhacker.news/c/6v96E
GitHub
GitHub - FlyGoat/csmwrap: Get PC BIOS back on UEFI only system
Get PC BIOS back on UEFI only system. Contribute to FlyGoat/csmwrap development by creating an account on GitHub.
LumoSQL (Score: 151+ in 4 hours)
Link: https://readhacker.news/s/6vaim
Comments: https://readhacker.news/c/6vaim
Link: https://readhacker.news/s/6vaim
Comments: https://readhacker.news/c/6vaim
How a hawk learned to use traffic signals to hunt more successfully (🔥 Score: 152+ in 3 hours)
Link: https://readhacker.news/s/6vaqx
Comments: https://readhacker.news/c/6vaqx
Link: https://readhacker.news/s/6vaqx
Comments: https://readhacker.news/c/6vaqx
Frontiers Science News
Street smarts: how a hawk learned to use traffic signals to hunt more successfully
Dr Vladimir Dinets, a zoologist who studies animal behavior, ecology, and conservation, is the author of a recently published Frontiers in Ethology article that
BGP handling bug causes widespread internet routing instability (Score: 151+ in 5 hours)
Link: https://readhacker.news/s/6vamw
Comments: https://readhacker.news/c/6vamw
Link: https://readhacker.news/s/6vamw
Comments: https://readhacker.news/c/6vamw
blog.benjojo.co.uk
BGP handling bug causes widespread internet routing instability
Square Theory (🔥 Score: 156+ in 2 hours)
Link: https://readhacker.news/s/6vb3Q
Comments: https://readhacker.news/c/6vb3Q
Link: https://readhacker.news/s/6vb3Q
Comments: https://readhacker.news/c/6vb3Q
Adam Aaronson
Square Theory | Adam Aaronson
The story starts in Crosscord, the crossword Discord server. Over 5,000 users strong, the server has emerged as a central hub for the online crossword community, a buzzing, sometimes overwhelming, sometimes delightful town square where total noobs, veteran…
FromSoft's singular mech game Chromehounds is back online (Score: 150+ in 17 hours)
Link: https://readhacker.news/s/6v9tn
Comments: https://readhacker.news/c/6v9tn
Link: https://readhacker.news/s/6v9tn
Comments: https://readhacker.news/c/6v9tn
Read Only Memo
Interview: 15 years after the servers shut down, FromSoft's singular mech game Chromehounds is back online
The PvP mech battler is finally playable online in Xbox 360 emulator Xenia, and I talked to the modder making it happen.
DuckLake is an integrated data lake and catalog format (Score: 152+ in 5 hours)
Link: https://readhacker.news/s/6vaHQ
Comments: https://readhacker.news/c/6vaHQ
Link: https://readhacker.news/s/6vaHQ
Comments: https://readhacker.news/c/6vaHQ
DuckLake
DuckLake is an integrated data lake and catalog format.
DuckLake delivers advanced data lake features without traditional lakehouse complexity by using Parquet files and your SQL database. It's an open, standalone format from the DuckDB team.
Pyrefly vs. Ty: Comparing Python's two new Rust-based type checkers (Score: 153+ in 4 hours)
Link: https://readhacker.news/s/6vaWH
Comments: https://readhacker.news/c/6vaWH
Link: https://readhacker.news/s/6vaWH
Comments: https://readhacker.news/c/6vaWH
Edward Li's Blog
Pyrefly vs. ty: Comparing Python’s Two New Rust-Based Type Checkers
A deep dive into Meta's pyrefly and Astral's ty - two new Rust-based Python type checkers that both promise faster performance and better type inference.
I salvaged $6k of luxury items discarded by Duke students (Score: 150+ in 6 hours)
Link: https://readhacker.news/s/6vb8z
Comments: https://readhacker.news/c/6vb8z
Link: https://readhacker.news/s/6vb8z
Comments: https://readhacker.news/c/6vb8z
INDY Week
I Salvaged $6,000 of Luxury Items Discarded by Duke Students. Why Did It Make Me Feel So Terrible?
At the end of the school year, a lot gets tossed by Duke students at my downtown Durham apartment building. This year I decided to dive in.
Show HN: My LLM CLI tool can run tools now, from Python code or plugins (🔥 Score: 152+ in 3 hours)
Link: https://readhacker.news/s/6vbT2
Comments: https://readhacker.news/c/6vbT2
Link: https://readhacker.news/s/6vbT2
Comments: https://readhacker.news/c/6vbT2
Simon Willison’s Weblog
Large Language Models can run tools in your terminal with LLM 0.26
LLM 0.26 is out with the biggest new feature since I started the project: support for tools. You can now use the LLM CLI tool—and Python library—to grant LLMs from …
Why Cline doesn't index your codebase (Score: 150+ in 15 hours)
Link: https://readhacker.news/s/6vaJ2
Comments: https://readhacker.news/c/6vaJ2
Link: https://readhacker.news/s/6vaJ2
Comments: https://readhacker.news/c/6vaJ2
Cline
Why Cline Doesn't Index Your Codebase (And Why That's a Good Thing) - Cline Blog
Here's a common question we get from prospective Cline users: "How does Cline handle large codebases? Do you use RAG to index everything?"
It's a reasonable question. Retrieval Augmented Generation (RAG) has become the go-to solution for giving AI systems…
It's a reasonable question. Retrieval Augmented Generation (RAG) has become the go-to solution for giving AI systems…
Tariffs in American History (❄️ Score: 150+ in 3 days)
Link: https://readhacker.news/s/6v2d7
Comments: https://readhacker.news/c/6v2d7
Link: https://readhacker.news/s/6v2d7
Comments: https://readhacker.news/c/6v2d7
Imprimis
Tariffs in American History
When Alexander Hamilton became the nation’s first Secretary of the Treasury, he immediately began to prepare a schedule of tariffs, along with excise taxes on such commodities as alcohol and tobacco. The Constitution forbids taxing the exports of any state…
Show HN: AutoThink – Boosts local LLM performance with adaptive reasoning (🔥 Score: 153+ in 3 hours)
Link: https://readhacker.news/c/6vcs8
I built AutoThink, a technique that makes local LLMs reason more efficiently by adaptively allocating computational resources based on query complexity.
The core idea: instead of giving every query the same "thinking time," classify queries as HIGH or LOW complexity and allocate thinking tokens accordingly. Complex reasoning gets 70-90% of tokens, simple queries get 20-40%.
I also implemented steering vectors derived from Pivotal Token Search (originally from Microsoft's Phi-4 paper) that guide the model's reasoning patterns during generation. These vectors encourage behaviors like numerical accuracy, self-correction, and thorough exploration.
Results on DeepSeek-R1-Distill-Qwen-1.5B:
- GPQA-Diamond: 31.06% vs 21.72% baseline (+43% relative improvement)
- MMLU-Pro: 26.38% vs 25.58% baseline
- Uses fewer tokens than baseline approaches
Works with any local reasoning model - DeepSeek, Qwen, custom fine-tuned models. No API dependencies.
The technique builds on two things I developed: an adaptive classification framework that can learn new complexity categories without retraining, and an open source implementation of Pivotal Token Search.
Technical paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253327
Code and examples: https://github.com/codelion/optillm/tree/main/optillm/autoth...
PTS implementation: https://github.com/codelion/pts
I'm curious about your thoughts on adaptive resource allocation for AI reasoning. Have you tried similar approaches with your local models?
Link: https://readhacker.news/c/6vcs8
I built AutoThink, a technique that makes local LLMs reason more efficiently by adaptively allocating computational resources based on query complexity.
The core idea: instead of giving every query the same "thinking time," classify queries as HIGH or LOW complexity and allocate thinking tokens accordingly. Complex reasoning gets 70-90% of tokens, simple queries get 20-40%.
I also implemented steering vectors derived from Pivotal Token Search (originally from Microsoft's Phi-4 paper) that guide the model's reasoning patterns during generation. These vectors encourage behaviors like numerical accuracy, self-correction, and thorough exploration.
Results on DeepSeek-R1-Distill-Qwen-1.5B:
- GPQA-Diamond: 31.06% vs 21.72% baseline (+43% relative improvement)
- MMLU-Pro: 26.38% vs 25.58% baseline
- Uses fewer tokens than baseline approaches
Works with any local reasoning model - DeepSeek, Qwen, custom fine-tuned models. No API dependencies.
The technique builds on two things I developed: an adaptive classification framework that can learn new complexity categories without retraining, and an open source implementation of Pivotal Token Search.
Technical paper: https://papers.ssrn.com/sol3/papers.cfm?abstract_id=5253327
Code and examples: https://github.com/codelion/optillm/tree/main/optillm/autoth...
PTS implementation: https://github.com/codelion/pts
I'm curious about your thoughts on adaptive resource allocation for AI reasoning. Have you tried similar approaches with your local models?