Tools

MILP works for small routing problems, but ALNS scales further. This article applies Adaptive Large Neighborhood Search to a complex pickup-and-delivery problem

Graph engineering treats AI applications as explicitly designed workflows. Learn the core components and build a reliable LangGraph research workflow.

Claude Code isn't the only option for agentic CLI coding. These seven alternatives offer more model flexibility, lower costs, and stronger harnesses.

Prompt compression reduces token usage and cost while preserving answer quality. This guide covers the main techniques and how to apply them.

Most enterprise "agents" are still chatbot wrappers. A new survey of 101 firms reveals a wide gap between orchestration ambition and deployed reality.

Meta-prompting asks a model to design reusable prompts before completing a task. It improves consistency, scalability, and output quality.

DeepSeek's DSpark module boosts LLM generation speed 60–85% by combining parallel drafting with lightweight sequential correction.

Data scientists at AI-driven companies now spend more time on oversight and system supervision than model building, as 2025–2026 job data confirms.

AI coding platforms are moving away from "unlimited" plans. Here are five token, credit, and quota-based subscriptions worth the price.

Self-improving loops let AI agents evaluate their own outputs, store lessons, and get better with each task cycle.

Sakana Fugu coordinates multiple expert agents internally while exposing a single OpenAI-compatible API. Here's how it works, what it costs, and when to use it.

Agentic loops in Claude Code let AI work autonomously end-to-end. Here's how the /goal command makes that happen.