Everything on Product Engineering

Performance constraints are often product decisions. Limiting user actions, such as capping emoji reactions, is a valid and effective strategy to mitigate system overload.

Impact: Aligns product features with infrastructure capabilities, preventing costly over-engineering for edge cases.

— from Scaling Slack and GitHub: Architecture, Load Testing, and AI · The Pragmatic Engineer Podcast· Nov 05, 2026

Jev excels in constrained-input scenarios, such as routing user commands or classifying limited sets of options. It can chain multiple decision steps to navigate complex workflows with sub-second latency.

Impact: Allows for the creation of intuitive, voice-driven interfaces and automated workflows that feel instantaneous, enhancing user engagement and operational efficiency.

— from Jev Decision Models: Fast, Cheap AI Routing · How I AI· Sep 30, 2026

Agentic reinforcement learning, where models are trained to use specific tools, dramatically improves task performance compared to static prompting. This method enabled a jump from 25% to 70% accuracy in legal queries.

Impact: Provides a scalable framework for improving AI agent performance in complex, tool-dependent workflows, offering a clear path to higher accuracy and efficiency.

— from Thomson Reuters Launches Thompson AI Model · Chain of Thought | AI Agents, Infrastructure & Engineering· Aug 24, 2026