Hacker News

Article URL: https://createpdfresume.com/

Comments URL: https://news.ycombinator.com/item?id=47270955

Points: 1

# Comments: 0

Article URL: https://ryanshamim.substack.com/p/the-inference-efficiency-paradox

Comments URL: https://news.ycombinator.com/item?id=47270954

Points: 1

# Comments: 1

Article URL: https://nypost.com/2026/03/05/us-news/tech-titans-vow-to-take-back-california-from-lefties-call-out-billionaires-fleeing/

Comments URL: https://news.ycombinator.com/item?id=47270939

Points: 1

# Comments: 0

Article URL: https://aptera.us/first-vehicle-off-validation-line/

Comments URL: https://news.ycombinator.com/item?id=47270935

Points: 1

# Comments: 0

Hey HN,

I got tired of the performative culture on LinkedIn. The platform mostly feels like people just yapping at each other all day to farm engagement, so I decided to build a CLI tool to do the yapping for me. It's called Yappy (because we just yap yap yap).

It is an open-source Python TUI that automates your LinkedIn engagement directly from the command line. It logs in, reads your feed, and uses the Gemini API to generate context-aware comments and drop likes based on your prompt parameters. Everything runs completely in the terminal, so you never actually have to look at the feed yourself.

I know AI-generated comments and web scraping are controversial, and LinkedIn's TOS strictly prohibits this kind of automation. This is built purely as an experimental toy project and a proof-of-concept for integrating LLMs with terminal interfaces. If you actually decide to run it, definitely use a burner account, as LinkedIn will likely restrict you if you run it too aggressively.

I am mostly looking for technical feedback on the Python code architecture and the TUI implementation.

Would love to hear your thoughts. Roast my code or drop a PR if you find the concept funny.

Comments URL: https://news.ycombinator.com/item?id=47270845

Points: 2

# Comments: 0

Article URL: https://lorendb.dev/posts/shut-up-and-take-my-money/

Comments URL: https://news.ycombinator.com/item?id=47270819

Points: 3

# Comments: 0

Article URL: https://spell.sh/

Comments URL: https://news.ycombinator.com/item?id=47270816

Points: 2

# Comments: 0

We built an ant colony simulation as an internal hiring challenge at Moment and decided to open it up publicly.

You write a program in a custom assembly-like (we call it ant-ssembly) instruction set that controls 200 ants. Each ant can sense nearby cells (food, pheromones, home, other ants) but has no global view. The only coordination mechanism is pheromone trails, which ants can emit and sense them, but that's it. Your program runs identically on every ant.

The goal is to collect the highest percentage of food across a set of maps. Different map layouts (clustered food, scattered, obstacles) reward very different strategies. The leaderboard is live.

Grand prize is a trip to Maui for two paid for by Moment. Challenge closes March 12.

Curious what strategies people discover. We've seen some surprisingly clever emergent behavior internally.

Comments URL: https://news.ycombinator.com/item?id=47270807

Points: 9

# Comments: 3

Article URL: https://knhash.in/custom-search-engine-on-safari-and-spotlight-macos/

Comments URL: https://news.ycombinator.com/item?id=47270801

Points: 3

# Comments: 0

LLM agents and tool-calling systems frequently retry or replay actions.

This becomes dangerous when the action is irreversible: - sending emails - opening tickets - executing trades - triggering payouts

SafeAgent is a small Python library that enforces exactly-once execution for agent actions using request-ID deduplication.

Example:

from settlement.settlement_requests import SettlementRequestRegistry

registry = SettlementRequestRegistry()

def send_email(): print("EMAIL SENT")

registry.execute( request_id="email:user123:invoice", action="send_email", payload={"to": "user123@example.com"}, execute_fn=send_email )

If the same request_id is replayed, the action does not run again.

Instead the original execution receipt is returned.

pip install safeagent-exec-guard

GitHub: https://github.com/azender1/SafeAgent

PyPI: https://pypi.org/project/safeagent-exec-guard/

Comments URL: https://news.ycombinator.com/item?id=47270797

Points: 2

# Comments: 0

Article URL: https://medicalxpress.com/news/2026-03-brain-cells-dementia-proteins.html

Comments URL: https://news.ycombinator.com/item?id=47270796

Points: 4

# Comments: 0

Article URL: https://www.seroundtable.com/google-patent-ai-generated-pages-search-41010.html

Comments URL: https://news.ycombinator.com/item?id=47270785

Points: 3

# Comments: 0

Article URL: https://blog.system76.com/post/system76-on-age-verification/

Comments URL: https://news.ycombinator.com/item?id=47270784

Points: 2

# Comments: 0

Article URL: https://www.verak.io/demo

Comments URL: https://news.ycombinator.com/item?id=47270719

Points: 1

# Comments: 0

Article URL: https://odysa.github.io/one-agent-sdk/

Comments URL: https://news.ycombinator.com/item?id=47270716

Points: 1

# Comments: 1

Article URL: https://www.theatlantic.com/ideas/2026/03/intelligence-concept/686121/

Comments URL: https://news.ycombinator.com/item?id=47270715

Points: 1

# Comments: 0

Article URL: https://en.wikipedia.org/wiki/Parakaryon

Comments URL: https://news.ycombinator.com/item?id=47270714

Points: 1

# Comments: 0

Article URL: https://warden.sentry.dev/

Comments URL: https://news.ycombinator.com/item?id=47270710

Points: 1

# Comments: 0

Hello HN,

This is a food log powered by Google Gemini.

Thanks, Enzo

Comments URL: https://news.ycombinator.com/item?id=47270700

Points: 1

# Comments: 0

Article URL: https://lists.debian.org/debian-legal/2026/03/msg00018.html

Comments URL: https://news.ycombinator.com/item?id=47270687

Points: 1

# Comments: 0