Context Bloat: Implementing Progressive Discovery in Agent Memory
Using progressive discovery and smart tool-search to keep agents lean. Learn how to prevent context window overflow and infinite reasoning loops in multi-agent systems.
From the Front Lines of Tech
Sharing strategic insights and lessons from over 20 years of building scalable systems, leading high-performing teams, and navigating complex technology shifts.
Multi-Cloud GPU Arbitrage: Routing Workloads Between Hyperscalers and Neoclouds
Don't lock into one vendor. Learn how to use an abstraction layer to route training and inference workloads to the cheapest available capacity across hyperscalers and neoclouds.
Semantic Caching at Scale: Vector Embeddings for 5x Latency Reduction
Moving beyond exact-match caching for repetitive zero-shot inference workloads. Learn how to architect semantic caching to slash latency and compute costs.
· StrategyPortfolio-Based Budgeting for AI Initiatives
Moving away from siloed project funding based on projected margin impact. Discover how to transition from project-based to portfolio-based AI funding to optimize ROI and survive the pilot phase.
Chunked Prefill: Solving the Noisy Neighbor Problem in Inference
When a massive prompt stalls your entire inference server, you have a noisy neighbor problem. The solution requires rethinking how we process context with Chunked Prefill.
Agent FinOps: Architecting Economic Constraints into LLM Routing
We built autonomous agents that can think, reason, and execute. Now we need to stop them from bankrupting us. Here is how to build economic constraints directly into your LangGraph loops.