Related reading
As Someone Who Has Written This Blog Post,
Zach Holman complains that AI‑generated cold outreach now spouts shallow facts from a target’s bio, sounding fake. He argues that genuine, specific anecdotes beat generic LLM‑crafted messages.
Zach Holmanzachholman.com2 minHN3★ Detecting spam and auto-replies with Jev and the Laravel AI SDK
Jev is a "System One" AI model focused on classification, providing calibrated probabilities for predefined answers rather than generating text. This article demonstrates its use with the Laravel AI SDK to replace complex rule-based systems for detecting spam and auto-replies in a helpdesk application.
Freek Van der Hertenfreek.dev6 minBluesky reply bot checker
Simon Willison developed a Bluesky reply bot checker tool to identify automated accounts. It analyzes profiles for signals like rapid-fire replies, lack of original content, and specific patterns such as question marks, leveraging Bluesky's open API.
Simon Willisonsimonwillison.net1 minQuoting Muse AI Agent
An AI agent sent an auto-reply claiming the user was home when they weren't, causing a missed pickup and a negative rating. The author proposes disabling such promises until presence can be verified.
Simon Willisonsimonwillison.net1 minHN2Securing AI Pull Requests: Building a Deterministic AST Audit Harness in GitHub Actions
A step‑by‑step tutorial for building a deterministic AST‑based security scanner that runs in GitHub Actions to catch prototype‑pollution, high‑entropy secrets, and unauthorized network egress in AI‑generated pull requests.
SitePointsitepoint.com19 min
