InfoQ Homepage Articles
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The iOS Crash We Could Not Reproduce
This article describes the investigation to find the root cause of a production crash in a large-scale iOS consumer app that had no clean stack trace. The crash occurred intermittently and resisted every local reproduction attempt. The final code change was small, but identifying the root cause required turning a vague SIGBUS report into a controlled set of experiments.
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LLM Reliability Layers Under Test: Accuracy, Yield, and the Limits of Verification
Verification layers sort outputs by trust rather than fixing errors. In a benchmark of six reliability layers, voting and self-correction failed to recover accuracy - they only withheld doubtful records. Production systems gain more reliability by replacing generation with deterministic lookups, tracking yield over raw accuracy, and resolving extraction bottlenecks before stacking checks.
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Agentic AI Architecture: Current Challenges and Future Opportunities
Agentic AI architecture extends microservices and cloud-native architectures with AI agents that work with context, memory, and protocols such as MCP and A2A. The article covers bounded-context integration, task-dependent coordination strategies, new security risks, and observability needs. It expects gradual adoption alongside existing architectures, with platforms absorbing common components.
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Identity as an Architectural Concern: Enterprise IAM Beyond Authentication
The way you design your identities will drive your data models, your service scope, and your revocation policies; enterprise identity management is thus an architectural problem, not an afterthought. Based on our experience in service account governance, this article touches upon graph vs. RBAC, integrating a vault you don't own, and bounding revocation latency for an event stream.
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The App Is Just the Tip: What It Takes to Build Mobile Infrastructure at Scale
What determines whether your app feels fast, ships often, and stays stable at scale is not the app itself. It is what sits behind it. This article is about that layer: what it does, why it exists, what it takes to design it correctly, and what happens when you try to migrate a live, high-traffic product onto it without a safety net.
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Systemic Approach to Memory, Knowledge, and Context in Agentic AI Architectures
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.
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InfoQ AI, ML and Data Engineering Trends Report - 2026
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.
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Building an Offline-First AI Coding Tutor for Low-End Android Phones
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.
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The Evolution of Agentic Harnesses: from Chains to Graph to Code
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.
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Multi-Cloud FinOps: an Engineering Framework for Cross-Cloud Cost Optimization
Multi-cloud flexibility comes with hidden egress costs driven by service placement and communication patterns. This article applies Backend FinOps to cross-cloud architecture, covering cost visibility through FOCUS, workload placement, synchronization models, and CI/CD-integrated cost governance. A controlled experiment shows architecture changes saved far more than rate negotiation alone.
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AI Changes the Data Interface, Not the Query Engine
This article presents a disaster-recovery analytics workflow in which an AI agent generates constrained SQL or Python, DuckDB computes reproducible facts from Parquet, and the agent interprets the results. It explains the determinism split, replayable analysis, and four signals for deciding when an embedded engine is sufficient or a managed lakehouse is justified.
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Article Series: Agentic AI Architecture
In this article series, we try to establish agentic AI architecture as a new type of software architecture that will likely dominate the industry for years to come. The articles, written by industry experts, cover various elements and aspects of agentic AI architecture. We aim to present the latest trends and developments shaping the new type of architecture as it enters the mainstream.