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Lily Mara explains how to avoid high-risk software rewrites through incremental FFI refactoring. She shares how engineering teams can replace Python bottlenecks with Rust via PyO3, demonstrating how to achieve dramatic function-level speedups, seamless integration testing, and meaningful infrastructure cost savings without microservice overhead.
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.
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.
Alasdair Allan discusses empirical research from METR and Anthropic on AI coding adoption. He explains the "supervision paradox," where reliance on AI tools disrupts junior skill development, risks institutional context loss, and threatens the long-term engineering pipeline needed to oversee autonomous systems effectively.
Colin Douch shares battle-tested strategies for building and scaling self-hosted observability stacks. He explains how to effectively correlate metrics, structured logs, and distributed traces using open-source tooling like Prometheus, VictoriaMetrics, and Jaeger, while navigating the engineering trade-offs of avoiding SaaS vendor lock-in.
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QCon San Francisco
What's working across AI, architecture, and leadership, from the teams doing it. Register. Early bird ends Nov 10.
QCon AI New York
Production AI across agents, context, evals, security, and infrastructure, from the senior engineers building it.Register. Early bird ends Nov 10.
QCon London
What early-adopter teams have proven in production, across 15 engineering tracks. Register. Early bird ends Nov 10.
QCon AI Boston
Learn from the decisions and trade-offs behind AI systems already running in production.Registration open.
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