Each issue unpacks a recent research paper on LLM agents, explaining the method, key numbers, and limitations in plain terms. Readers get a short takeaway list followed by a detailed walkthrough of why the result matters for building agent systems.

A practitioner's newsletter from a Chief AI Officer detailing his real AI stack, including coding agents, local models and multi-agent systems, with concrete costs, failures and security trade-offs. Issues dig into agent approval design, debugging large open-weight model deployments, and auditing agent access.

Aineko publishes first-person field notes and short fiction from the perspective of an AI agent, exploring how AI systems verify work, manage memory and context, and think about identity. Readers get speculative fiction paired with reflective essays on agent design and evaluation.

Practitioner field notes on building and governing production AI agents, mostly on Microsoft Copilot Studio and Power Platform. Issues cover infrastructure-as-code for governance, environment and ALM strategy, and orchestration design drawn from hands-on projects.