AI Agents vs AI Workflows: How to Choose for Production

A practical guide from AIBackends on when to use deterministic AI workflows versus autonomous agents, why control flow ownership is the deciding difference, and how hybrid agentic workflows hold up in production.

Guide · AI Agents · AI · Software Engineering · Engineering

Benchmarking: An Introduction

“When a measure becomes a target, it ceases to be a good measure” – Goodhart’s law Current AI research, especially the frontier LLM research, is dominated by benchmarks. It is the first thing we look at when a new model comes out, it is the headline of each release, and they dominate the discourse when […]

Guide · AI · Benchmarks · LLMs · Research

Running local LLMs on your Mac: what fits, what's free, and what's overkill

A practical guide to running language models on Apple Silicon: which sizes fit common Macs, free options that work well, and when bigger local models are overkill.

Guide · LLMs · Hardware · Developer Tools · AI

Frequently Asked Questions (And Answers) About AI Evals

Hamel Husain and Shreya Shankar’s sharp FAQ on AI/LLM product evals: start with error analysis on real traces, build targeted evaluators, validate LLM judges with TPR/TNR, and avoid generic off-the-shelf metrics.

Guide · AI · LLMs · Engineering · Machine Learning

Prompting Claude Opus 5.5

Anthropic’s guide to prompting Claude Opus 5.5: how the model behaves, patterns that work for complex agentic and coding tasks, and practical prompt-engineering advice for builders.

Guide · AI · LLMs · AI Agents · Tutorials