Tag
A seasoned AI engineer shares key skills for 2026, including systematic output reading, context engineering, tool description discipline, eval design, model routing, prompt versioning, confidence scoring, streaming architecture, fallback chains, latency budgets, failure cataloguing, agent-vs-workflow decisions, and failure post-mortems as portfolio content.
Researchers trained a vision-language model without a vision encoder for only $100, inspired by Gemma 4 12B, achieving a 30% reduction in end-to-end latency on an M3 Pro MacBook.
InfraMind introduces an infrastructure-aware multi-agent LLM orchestration framework that uses reinforcement learning to dynamically select models and topologies based on real-time system load, achieving up to 7x lower latency and 99.9% SLO compliance under high load.
ObjectCache proposes using S3-compatible object storage for LLM KV cache reuse to reduce cost and increase capacity, with a co-designed storage protocol and transfer schedule that minimizes latency overhead. Experiments show it adds only 5.6% latency over local DRAM for 64K contexts.
This paper introduces temporal semantic caching and MCP workflow optimizations for agentic plan-execute pipelines, achieving up to 30.6x speedup on cache hits and 1.67x overall speedup on the AssetOpsBench industrial benchmark.
A blog post detailing how to detect silent NPU fallback on Snapdragon in CI, including methods like running on real hardware, gating on coefficient of variation, and parsing ORT profiling JSON to identify fallen-back ops.
This paper introduces BoundaryRouter, a training-free framework that optimizes LLM agent usage by routing queries to either lightweight inference or full agent execution based on early experience. It also presents RouteBench, a benchmark for evaluating routing performance, showing significant improvements in speed and accuracy.