Artificial intelligence

How to Stop an AI Agent From Giving Away Your Money in a Negotiation

A voice agent that negotiates freight rates, ten scripted attacks, and the difference between “never crossed the limit” and “never gave the limit away”

Make Your AI Agent Ask Before It Answers

AI agents guess when a question is vague. Two things help: write down your rules first, then add a separate check that asks.Continue reading on Towards AI »

The Paranoid Agent: Unleashing Chaos Monkey on a LangGraph4j State Graph

Every agent looks great when the mock API responds in 100 milliseconds and the demo run is scripted.Continue reading on Towards AI »

Transparent AI UX: 7 Rules for Designing AI People Actually Trust

Most people use AI answers without checking them, yet less than half say they trust AI. That gap is a design problem. Here is how to close…Continue reading on Towards AI »

RAG vs. Long Context in 2026: When Retrieval Still Wins

Claude Sonnet 5 and Gemini 3.1 Pro ship 1M-token windows, but RULER and Chroma's research shows retrieval still beats stuffing on cost and recall accuracy...

Qwen 4 Is in Training. You Can Already Run Its Architecture.

What’s new in Flash-Next, and the Mac and PC setups that get its long-prompt speed today.Continue reading on Towards AI »

Your AI Isn’t Hallucinating. Your Data Is Lying to It.

Most of what we call hallucination is a model faithfully repeating data we never checked

Tuning Jev as a Quality Judge: A Decision Model vs. Two Cost-Effective LLMs

First in a two-part series on tuning Jev as an LLM judge: this post covers judging response quality; the next covers judging response safety.

Meet Jev: The AI Model That Doesn’t Write, and Why Data Engineers Should Care

A plain-English guide to “System One” models, with patterns, code, and honest caveats

AI Agents Need More Than an LLM. Here’s the Full Stack

Learn the full AI agent stack: LLM, context, tools, memory, orchestration, runtime, guardrails, and observability. A clear guide to…Continue reading on Towards AI »

ChatGPT Pro $200 Cut to 10x: is a Mac Studio Worth it for Local LLMs now?

I priced 50 days of my own $200 AI plan at API rates first. The number a Mac Studio has to beat is a lot smaller than $200.Continue reading on Towards AI »

I Installed 40 Claude Skills. Three Survived.

superpowers has 291K stars — and it actively slows me down on half my work.Continue reading on Towards AI »

Redis for AI Agents: Memory, Queues, Checkpoints

Your framework is the brain. Redis is the hands. Here’s when the hands are overkill.Continue reading on Towards AI »

How to Write an Agent Eval Rubric: Why Your LLM Judge Averages 4.8 on Useless Replies

AI Models Are Starting to Communicate Without Words

Cache-to-Cache lets one LLM pass internal representations directly into another. What looks like an inference optimization may become…Continue reading on Towards AI »

How Jev Picks an Answer Without Writing One

Scoring instead of generating: what open Qwen2.5 experiments show about speed, accuracy and calibration, and how to build it on AzureContinue reading on Towards AI »

GPT-6 Astra vs Gemini 4 Argon vs Claude Fable 5.1: The Benchmark Winner Is the One You Can't Buy

Gemini 4 Argon beats GPT-6 Astra and Claude Fable 5.1 on most of the benchmark table Google published on September 30, and almost nobody…Continue reading on Towards AI »

IT Recruitment in the Age of Generative AI

For roughly the last ten years, I have participated in hiring students and full-time employees at a large corporation. I was one of several people involved in hiring for my unit. The process changed over time, but its general shape will probably sound familiar.