Prompt Engineering

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Scoured 131 posts in 7.3 ms

ChatGPT easily bypasses its own guardrails; all LLMs are inherently unsafe

 🤖ChatGPT  Content type: Blog
techzine.eu·

Meet Hades: The malware that lies to AI security agents

 🐙GitHub  Content type: News

The AI Agents Stack (2026 Edition)

 🤖AI  Content type: Blog
oreilly.com·

Show HN: Axiomax – Cryptographic proof of AI inference carbon footprint

 🤖ChatGPT

Claude Opus 4.8 system prompt leaked

 🤖ChatGPT

What is Agentic RAG? Building Multi-Agent Agentic RAG Systems

 🤖AI Tools
pub.towardsai.net
·

Would an LLM tell you if it’s gaming your eval? Often, no. But we can still catch the model thinking about it.

 🤖ChatGPT
threadreaderapp.com·

ashp15205/guardian-runtime: A zero-latency, local-first runtime firewall for LLMs. Intercept every prompt and response locally to stop data leaks and runaway token costs.

 🤖ChatGPT  Content type: Code
github.com··Hacker News

What does a reranker even do ?

 🗂️Link Curation  Content type: Blog

Show HN: Run Llama.cpp In-Process from Java with Project Panama FFM

 🤖AI

Phoenix

 🤖AI Tools
arize.com·

How LLMs Actually Work: A Friendly Map for Humans • oreoro

 🧠LLM

Engineers building MCPs in regulated industries: what's been the hardest part?

 🤖Multi-Agent Systems
deepsense.ai··Hacker News

LangChain Explained: Understanding Models, Prompts, Chains, Memory, Indexes, and Agents

 🤖AI Tools
pub.towardsai.net
·

Introducing Granite Libraries and Project Granite Switch

 🧠LLMs  Content type: Blog

Casual experiment hint that models seem to search for different stuff

 🤖AI
spock.is··Hacker News

Show HN: Incremental RAG ingestion, only changed chunks get re-embedded

 🏠Self-hosted apps  Content type: Code
github.com··Hacker News

A wild idea: Abstract reality using ontology

 🧠LLM  Content type: Discussion

Build a Basic AI Agent from Scratch: Long Task Planning

 🤖ChatGPT  Content type: Blog
ruxu.dev··Hacker News

Tool to convert technical PDFs into RAG-ready chunks and Obsidian vaults

 🧠Personal Knowledge Management

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