Changes since congestion pricing started in New York (Score: 151+ in 1 day)
Link: https://readhacker.news/s/6upxD
Comments: https://readhacker.news/c/6upxD
Link: https://readhacker.news/s/6upxD
Comments: https://readhacker.news/c/6upxD
Nytimes
Here Is Everything That Has Changed Since Congestion Pricing Started in New York
Fewer cars. Faster travel. Less honking. And some questions we still can’t answer.
The cryptography behind passkeys (Score: 151+ in 12 hours)
Link: https://readhacker.news/s/6utfz
Comments: https://readhacker.news/c/6utfz
Link: https://readhacker.news/s/6utfz
Comments: https://readhacker.news/c/6utfz
The Trail of Bits Blog
The cryptography behind passkeys
This post will examine the cryptography behind passkeys, the guarantees they do or do not give, and interesting cryptographic things you can do with them, such as generating cryptographic keys and storing certificates.
Git Bug: Distributed, Offline-First Bug Tracker Embedded in Git, with Bridges (Score: 150+ in 1 day)
Link: https://readhacker.news/s/6upzw
Comments: https://readhacker.news/c/6upzw
Link: https://readhacker.news/s/6upzw
Comments: https://readhacker.news/c/6upzw
GitHub
GitHub - git-bug/git-bug: Distributed, offline-first bug tracker embedded in git
Distributed, offline-first bug tracker embedded in git - git-bug/git-bug
Writing N-body gravity simulations code in Python (❄️ Score: 150+ in 4 days)
Link: https://readhacker.news/s/6ueLr
Comments: https://readhacker.news/c/6ueLr
Link: https://readhacker.news/s/6ueLr
Comments: https://readhacker.news/c/6ueLr
Perverse incentives of vibe coding (Score: 150+ in 6 hours)
Link: https://readhacker.news/s/6uuTD
Comments: https://readhacker.news/c/6uuTD
Link: https://readhacker.news/s/6uuTD
Comments: https://readhacker.news/c/6uuTD
Medium
The Perverse Incentives of Vibe Coding
I’ve been using AI coding assistants like Claude Code for a while now, and I’m here to say (with all due respect to people who have…
Show HN: Muscle-Mem, a behavior cache for AI agents (Score: 150+ in 7 hours)
Link: https://readhacker.news/s/6uuUP
Comments: https://readhacker.news/c/6uuUP
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 it worked for them in most cases. The pull to agents as an RPA alternative was not to have an infinitely flexible "AI Employees" as tech Twitter/X may want you to think, but simply because their RPA breaks under occasional edge-cases and agents can gracefully handle those cases.
Using a pure-agent approach proved to be highly wasteful. Window's accessibility APIs are poor, so you're generally stuck using pure-vision agents, which can run around $40/hr in token costs and take 5x longer than a human to perform a workflow. At this point, you're better off hiring a human.
The goal of Muscle-Mem is to get LLMs out of the hot path of repetitive automations, intelligently swapping between script-based execution for repeat cases, and agent-based automations for discovery and self-healing.
While inspired by computer-use environments, Muscle Mem is designed to generalize to any automation performing discrete tasks in dynamic environments. It took a great deal of thought to figure out an API that generalizes, which I cover more deeply in this blog:
https://erikdunteman.com/blog/muscle-mem/
Check out the repo, consider giving it a star, or dive deeper into the above blog. I look forward to your feedback!
Link: https://readhacker.news/s/6uuUP
Comments: https://readhacker.news/c/6uuUP
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 it worked for them in most cases. The pull to agents as an RPA alternative was not to have an infinitely flexible "AI Employees" as tech Twitter/X may want you to think, but simply because their RPA breaks under occasional edge-cases and agents can gracefully handle those cases.
Using a pure-agent approach proved to be highly wasteful. Window's accessibility APIs are poor, so you're generally stuck using pure-vision agents, which can run around $40/hr in token costs and take 5x longer than a human to perform a workflow. At this point, you're better off hiring a human.
The goal of Muscle-Mem is to get LLMs out of the hot path of repetitive automations, intelligently swapping between script-based execution for repeat cases, and agent-based automations for discovery and self-healing.
While inspired by computer-use environments, Muscle Mem is designed to generalize to any automation performing discrete tasks in dynamic environments. It took a great deal of thought to figure out an API that generalizes, which I cover more deeply in this blog:
https://erikdunteman.com/blog/muscle-mem/
Check out the repo, consider giving it a star, or dive deeper into the above blog. I look forward to your feedback!
GitHub
GitHub - pig-dot-dev/muscle-mem: A cache for AI agents to learn and replay complex behaviors.
A cache for AI agents to learn and replay complex behaviors. - pig-dot-dev/muscle-mem
Copaganda: How Police and the Media Manipulate Our News (Score: 151+ in 4 hours)
Link: https://readhacker.news/s/6uvxF
Comments: https://readhacker.news/c/6uvxF
Link: https://readhacker.news/s/6uvxF
Comments: https://readhacker.news/c/6uvxF
Teen Vogue
How to Sniff Out ‘Copaganda’: When the Police and the Media Manipulate Our News
"By cherry-picking anecdotes, news reports can distort our interpretation of the world."
How the economics of multitenancy work (Score: 150+ in 15 hours)
Link: https://readhacker.news/s/6utyj
Comments: https://readhacker.news/c/6utyj
Link: https://readhacker.news/s/6utyj
Comments: https://readhacker.news/c/6utyj
www.blacksmith.sh
How The Economics of Multitenancy Work
With millions of jobs running monthly on our bare-metal fleet, we've seen the economics of multitenancy hold up — here's a peek behind the curtain of how the math works.
Uber to introduce fixed-route shuttles in major US cities (Score: 150+ in 13 hours)
Link: https://readhacker.news/s/6uu7P
Comments: https://readhacker.news/c/6uu7P
Link: https://readhacker.news/s/6uu7P
Comments: https://readhacker.news/c/6uu7P
TechCrunch
Uber to introduce fixed-route shuttles in major US cities designed for commuters | TechCrunch
Ride-hail and delivery giant Uber is introducing cheap, fixed-route rides along busy corridors during weekday commute hours in major U.S. cities -- one
Migrating to Postgres (Score: 150+ in 8 hours)
Link: https://readhacker.news/s/6uvgK
Comments: https://readhacker.news/c/6uvgK
Link: https://readhacker.news/s/6uvgK
Comments: https://readhacker.news/c/6uvgK
Medium
Migrating to Postgres
Since early 2022, Motion was on CockroachDB. Cockroach has many qualities going for it: effortless horizontal scaling, especially when…
LLMs get lost in multi-turn conversation (Score: 152+ in 4 hours)
Link: https://readhacker.news/s/6uvQa
Comments: https://readhacker.news/c/6uvQa
Link: https://readhacker.news/s/6uvQa
Comments: https://readhacker.news/c/6uvQa
arXiv.org
LLMs Get Lost In Multi-Turn Conversation
Large Language Models (LLMs) are conversational interfaces. As such, LLMs have the potential to assist their users not only when they can fully specify the task at hand, but also to help them...
Human (Score: 154+ in 4 hours)
Link: https://readhacker.news/s/6uvSE
Comments: https://readhacker.news/c/6uvSE
Link: https://readhacker.news/s/6uvSE
Comments: https://readhacker.news/c/6uvSE
Quarter--Mile
Human — Quarter Mile
Human Written by a human [0] Imagine, for a moment, a world with no humans. Just machines, bolts and screws, zeros and ones. There is no emotion. There is...
Internet Artifacts (Score: 154+ in 1 day)
Link: https://readhacker.news/s/6upDF
Comments: https://readhacker.news/c/6upDF
Link: https://readhacker.news/s/6upDF
Comments: https://readhacker.news/c/6upDF
neal.fun
Internet Artifacts
Browse through the old internet
Our narrative prison (Score: 151+ in 17 hours)
Link: https://readhacker.news/s/6uuhS
Comments: https://readhacker.news/c/6uuhS
Link: https://readhacker.news/s/6uuhS
Comments: https://readhacker.news/c/6uuhS
Aeon
Our narrative prison
The three-act ‘hero’s journey’ has long been the most prominent kind of story. What other tales are there to tell?
EU ruling: tracking-based advertising [...] across Europe has no legal basis (🔥 Score: 150+ in 2 hours)
Link: https://readhacker.news/s/6uwdn
Comments: https://readhacker.news/c/6uwdn
Link: https://readhacker.news/s/6uwdn
Comments: https://readhacker.news/c/6uwdn
Irish Council for Civil Liberties
EU ruling: tracking-based advertising by Google, Microsoft, Amazon, X, across Europe has no legal basis
Landmark court decision against “TCF” consent pop ups on 80% of the internet…
Python lib generates its code on-the-fly based on usage (❄️ Score: 150+ in 3 days)
Link: https://readhacker.news/s/6ujvq
Comments: https://readhacker.news/c/6ujvq
Link: https://readhacker.news/s/6ujvq
Comments: https://readhacker.news/c/6ujvq
GitHub
GitHub - cofob/autogenlib: Import wisdom, export code.
Import wisdom, export code. Contribute to cofob/autogenlib development by creating an account on GitHub.
Show HN: Semantic Calculator (king-man+woman=?) (Score: 150+ in 18 hours)
Link: https://readhacker.news/s/6uuXx
Comments: https://readhacker.news/c/6uuXx
I've been playing with embeddings and wanted to try out what results the embedding layer will produce based on just word-by-word input and addition / subtraction, beyond what many videos / papers mention (like the obvious king-man+woman=queen). So I built something that doesn't just give the first answer, but ranks the matches based on distance / cosine symmetry. I polished it a bit so that others can try it out, too.
For now, I only have nouns (and some proper nouns) in the dataset, and pick the most common interpretation among the homographs. Also, it's case sensitive.
Link: https://readhacker.news/s/6uuXx
Comments: https://readhacker.news/c/6uuXx
I've been playing with embeddings and wanted to try out what results the embedding layer will produce based on just word-by-word input and addition / subtraction, beyond what many videos / papers mention (like the obvious king-man+woman=queen). So I built something that doesn't just give the first answer, but ranks the matches based on distance / cosine symmetry. I polished it a bit so that others can try it out, too.
For now, I only have nouns (and some proper nouns) in the dataset, and pick the most common interpretation among the homographs. Also, it's case sensitive.
Working on complex systems: What I learned working at Google (❄️ Score: 155+ in 2 days)
Link: https://readhacker.news/s/6uprB
Comments: https://readhacker.news/c/6uprB
Link: https://readhacker.news/s/6uprB
Comments: https://readhacker.news/c/6uprB
www.thecoder.cafe
Working on Complex Systems: What I Learned Working at Google
This is why recognizing whether a system is complicated or complex is so important: it shapes how we should approach problem-solving.
Malicious compliance by booking an available meeting room (🔥 Score: 155+ in 3 hours)
Link: https://readhacker.news/s/6uwWP
Comments: https://readhacker.news/c/6uwWP
Link: https://readhacker.news/s/6uwWP
Comments: https://readhacker.news/c/6uwWP
www.clientserver.dev
Malicious compliance by booking an available meeting room
In 2011, Larry Page became CEO of Google and tried to fix meetings. But his new policies were no match for Google Calendar pedants.
A Tiny Boltzmann Machine (Score: 150+ in 4 hours)
Link: https://readhacker.news/s/6ux37
Comments: https://readhacker.news/c/6ux37
Link: https://readhacker.news/s/6ux37
Comments: https://readhacker.news/c/6ux37
eoinmurray.info
Eoin Murray Notebooks
Work in progress notebooks