Guide contents
Loop Engineering: Architecture of Autonomous Agentic Loops and the Post-Prompting Era
A deep dive into Loop Engineering: self-sustaining execution loops for Claude Code and autonomous agents, the DOER/CHECKER topology, deterministic verification, the /goal primitive, and reward hacking mitigation.
This guide is available to AI-Base subscribers
Get full access to this practical guide, ready-made configurations and terminal scripts.
Related Ecosystem Resources
Explore practical workflows, core terminology, and engineering tools
Practical Reference: AI Agent Architecture in 2026
A production reference for autonomous agent architectures: six system layers, five orchestration patterns, memory tiering, loop circuit breakers, and a production readiness checklist.
Claude Code /goal: Autonomous Agent Execution Without Human Intervention
Claude Code is a tool for working with code directly from the terminal. By default, it works in step-by-step mode: you write a request, get an answer, write again. The /goal command fundamentally changes this logic.
Agent-to-Agent Protocol (A2A)
An open standard for network interaction, decentralized discovery, and secure context exchange between independent AI agents across various vendors and platforms.
Plan-and-Solve Prompting
A two-stage agent architecture that separates the strategic decomposition of a task into a global plan from its sequential tactical execution with dynamic replanning.
Thinking Machines Releases Inkling 2 Small: a 594B MoE Model That Can Fine-Tune Other Models
Thinking Machines released Inkling 2 Small, a 594B-parameter MoE model that leads among open models in several benchmarks and demonstrated autonomous fine-tuning of Qwen3.5-4B.
Thinking Machines releases Inkling 2 Small: a MoE model that competes with larger flagships
Thinking Machines introduced Inkling 2 Small, a multimodal Mixture-of-Experts model with 594B total parameters and 17B active per token. Full weights are promised next week under Apache 2.0.