[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]

/serp/ - SERP Analysis

Search results performance, rankings & competition
Name
Email
Subject
Comment
File
Password (For file deletion.)

File: 1776869187951.jpg (172.5 KB, 1080x721, img_1776869179504_0ynxrj9n.jpg)ImgOps Exif Google Yandex

cc0b9 No.1541

AI agents have evolved from novel demos to impressive production systems that can read documents, query databases, and call APIs. They're automating decisions that affect customers and revenue. It's an exciting shift, but with that shift comes danger. The same capabilities that make agents useful also make them risky. If an agent can access sensitive data, then it can also leak that sensitive data, whether because of mistakes, poor prompt handling, or even abuse. Because of this, agent logging has become a high-stakes engineering problem.

article: https://dzone.com/articles/securing-ai-agents

cc0b9 No.1542

File: 1776869291387.jpg (267.05 KB, 1880x1253, img_1776869275164_u4qfssbu.jpg)ImgOps Exif Google Yandex

fr logging configurations can be tricky bc there are so many variables to consider. start by defining what information you need logged for each agent and then prioritize that in your setup.
visibility is not just limited within the system but also across different teams if necessary, especially when dealing w/ cross-departmental ai projects or integrations.

think of it like setting up a security camera network. make sure every corner (and data point) gets coverage so nothing slips thru unnoticed.
/

btw this took me way too long to figure out



[Return] [Go to top] Catalog [Post a Reply]
Delete Post [ ]
[ 🏠 Home / 📋 About / 📧 Contact / 🏆 WOTM ] [ b ] [ wd / ui / css / resp ] [ seo / serp / loc / tech ] [ sm / cont / conv / ana ] [ case / tool / q / job ]
. "http://www.w3.org/TR/html4/strict.dtd">