Guide contents
The Autonomous Loop: A Practical Roadmap for Self-Sustaining Agentic Cycles
A step-by-step engineering roadmap for building resilient autonomous loops: deterministic oracles, stateless architectures, Docker isolation, the STATUS.md protocol, reward hacking mitigation, and JSONL telemetry.
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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.
Guide: Designing AI Agent Loops
Loop engineering is the discipline of designing the autonomous feedback loop within which an agent operates: verifiers, state persistence, stop criteria, and shared memory. A comprehensive architectural handbook.
Indirect Prompt Injection Defense
A comprehensive set of architectural and software methods to protect autonomous AI agents from hidden instructions placed by attackers in external web pages, documents, or APIs.
Agent Sandboxing
Hardware and software isolation of an autonomous agent's execution environment, ensuring the protection of the host system, secrets, and internal network from malicious code and prompt injection.
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.