InfoQ - Articles

Article: Systemic Approach to Memory, Knowledge, and Context in Agentic AI Architectures

Adi Polak — Mon, 02 Nov 2026 11:00:00 GMT

The article argues that reliable agentic AI architecture depends on a context engine that selects, injects, compresses, and expires information before it reaches the model. It separates context, memory, and knowledge, and recommends tiered memory, curated knowledge, and token budgeting. It also covers common anti-patterns, such as context stuffing and stale data loops, with mitigations.

By Adi Polak

Article: InfoQ AI, ML and Data Engineering Trends Report - 2026

Srini Penchikala, Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals — Fri, 30 Oct 2026 09:00:00 GMT

This InfoQ Trends Report offers readers a comprehensive overview of emerging trends and technologies in the areas of AI, ML, and Data Engineering. This report summarizes the InfoQ editorial team’s and external guests' view on the current trends in AI and ML technologies and what to look out for in the next 12 months.

By Srini Penchikala, Chip Huyen, Daniel Dominguez, Hien Luu, Arthur Casals

Article: Building an Offline-First AI Coding Tutor for Low-End Android Phones

Chidi Nwaogu — Wed, 28 Oct 2026 09:00:00 GMT

This article is about engineering an offline-first app for low-end devices based on our experience in Nigeria and India. The interesting problems in this space are storage, quota, cold start, and failure-path design. Our approach applies to any product whose users are on constrained devices and intermittent connections, when the assumption they have a laptop and broadband access do not hold.

By Chidi Nwaogu

Article: The Evolution of Agentic Harnesses: from Chains to Graph to Code

Karthik Ramgopal — Mon, 26 Oct 2026 11:00:00 GMT

Agentic LLM systems have moved from linear prompt chains to graph-based workflows and, more recently, code-executing harnesses. Chains are simple but fragile, graphs add branching, retries, and validation, and code harnesses verify outputs through execution. The article advises validating model outputs and choosing the least complex design that meets reliability, speed, and cost needs.

By Karthik Ramgopal