ContentPosts from @pnvmadhavarao..
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@faun shared a link, 14 hours ago

You Vibe It, You Run It?

Vibe Coding lets developers create software by chatting with AI, skipping traditional coding. But the non-determinism of AI prompts poses significant risks for reliability and maintainability, potentially leading to addiction-like dependence on this new tool. Think twice before fully embracing this ..

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@faun shared a link, 14 hours ago

TIOBE Programming Index News September 2025: Perl Regains the Spotlight

Perl 5 has risen to **10th place in the TIOBE Index**, increasing in popularity even though the exact reason is unknown. Perl 6, or Raku, lags behind Perl 5 in rankings and has not seen the same rise in attention. Other top languages like C and Java have experienced slight falls in rankings...

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@faun shared a link, 14 hours ago

Using Claude Code to modernize a 25-year-old kernel driver

A long-dead Linux kernel driver for QIC-80 tape drives just got dragged into the present—with help from **Claude Code** and a lot of tinkering. It now builds cleanly and runs as a **standalone module** on **Linux 6.8**, playing nice with modern setups like **Xubuntu 24.04**. **The bigger picture:**..

Using Claude Code to modernize a 25-year-old kernel driver
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@faun shared a link, 14 hours ago

AgentHopper: An AI Virus

In the “Month of AI Bugs,” researchers poked deep and found prompt injection holes bad enough to run **arbitrary code** on major AI coding tools—**GitHub Copilot**, **Amazon Q**, and **AWS Kiro** all flinched. They didn’t stop at theory. They built **AgentHopper**, a proof-of-concept AI virus that ..

AgentHopper: An AI Virus
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@faun shared a link, 14 hours ago

Vibe coding has turned senior devs into ‘AI babysitters,’ but they say it’s worth it

Fastly says95% of developersspend extra time fixing AI-written code. Senior engineers take the brunt. That overhead has even spawned a new gig: “vibe code cleanup specialist.” (Yes, seriously.) As teams lean harder on AI tools, reliability and security start to slide—unless someone steps in. The re..

Vibe coding has turned senior devs into ‘AI babysitters,’ but they say it’s worth it
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@faun shared a link, 14 hours ago

Building Agents for Small Language Models: A Deep Dive into Lightweight AI

Agent engineering with **small language models (SLMs)**—anywhere from 270M to 32B parameters—calls for a different playbook. Think tight prompts, offloaded logic, clean I/O, and systems that don’t fall apart when things go sideways. The newer stack—**GGUF** + **llama.cpp**—lets these agents run loc..

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@faun shared a link, 14 hours ago

Understanding LLMs: Insights from Mechanistic Interpretability

LLMs generate text by predicting the next word using attention to capture context and MLP layers to store learned patterns. Mechanistic interpretability shows these models build circuits of attention and features, and tools like sparse autoencoders and attribution graphs help unpack superposition, r..

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@faun shared a link, 14 hours ago

GitHub MCP Registry: The fastest way to discover AI tools

GitHub just rolled out the **MCP Registry**—a hub for finding **Model Context Protocol (MCP) servers** without hunting through scattered corners of the internet. No more siloed lists or mystery URLs. It's all in one place now. The goal? Cleaner access to AI agent tools, plus a path toward **self-pu..

GitHub MCP Registry: The fastest way to discover AI tools
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@faun shared a link, 14 hours ago

LLM Evaluation: Practical Tips at Booking.com

Booking.com built Judge-LLM, a framework where strong LLMs evaluate other models against a carefully curated golden dataset. Clear metric definitions, rigorous annotation, and iterative prompt engineering make evaluations more scalable and consistent than relying solely on humans. **The takeaway**:..

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@faun shared a link, 14 hours ago

Guardians of the Agents 

A new static verification framework wants to make runtime safeguards look lazy. It slaps **mathematical safety proofs** onto LLM-generated workflows *before* they run—no more crossing fingers at execution time. The setup decouples **code from data**, then runs checks with tools like **CodeQL** and ..