InfoQ - Languages

Presentation: Beyond Prompting: Context Engineering for Production-Grade AI

Ricardo Ferreira — Wed, 02 Sep 2026 11:00:00 GMT

Ricardo Ferreira discusses moving beyond simple prompt engineering to build production-grade AI applications. He shares practical architectural strategies for integrating long-term and short-term memory using Redis, managing LLM token limits via summarization, mitigating context rot with reranking and semantic caching, and controlling exponential API costs under strict latency constraints.

By Ricardo Ferreira

Presentation: Beyond Line Charts: Why Some Diversity in Telemetry Visualization Is Long Overdue

Yao Yue — Tue, 01 Sep 2026 12:35:00 GMT

Yao Yue discusses the fundamental limitations of standard line charts for system observability. Drawing from 15 years of operating large-scale systems, she shares how engineering leaders and software architects can transform telemetry data - moving beyond simple time-series defaults - to build visualizations that directly answer critical capacity, latency, and fleet-sizing questions.

By Yao Yue

Article: Post-Quantum Cryptography in Spring Boot: Four Patterns You Can Ship This Sprint

Pankaj Sharma — Fri, 28 Aug 2026 09:00:00 GMT

There are four patterns that bring PQC into a Spring Boot fleet: encrypting payloads between services, locking down database fields, signing documents that need to hold up for decades, and moving service tokens off RS256. Along the way, we discuss why Harvest Now, Decrypt Later is already happening, and why none of this is production-safe until KMS or Vault is in place.

By Pankaj Sharma

Presentation: Python, Numba, and Algorithm Design: Building Efficient Models in Financial Services

Chad Schuster — Thu, 27 Aug 2026 09:23:00 GMT

Chad Schuster discusses bridging Python's developer velocity with C-like performance using Numba JIT and GPUs. Drawing from large-scale actuarial modeling, he explains LLVM pipeline architecture, performance gains up to 750x, and essential trade-offs like OOP limits, type inference errors, and compile-time overhead for engineering leaders scaling compute-heavy enterprise systems.

By Chad Schuster