Build adaptive, cost-aware Graph-RAG pipelines that route queries through escalating retrieval stages (local -> bridge -> global) with triple-check verification and provenance map-back. Use when: 'build a graph RAG pipeline', 'implement adaptive retrieval for…
Adapt general-purpose BPE tokenizers into domain- or language-specialized tokenizers using the AdaptBPE post-training strategy. Replaces low-utility tokens with high-frequency domain-specific tokens to improve tokenization efficiency without retraining from…
Explain generative AI outputs using the gSMILE perturbation-based attribution framework. Builds local surrogate models from controlled input perturbations and Wasserstein distance to produce token-level or word-level importance scores for LLM and diffusion…
Automatically evaluate software research artifacts (code repositories with READMEs) by constructing dependency-aware command graphs, building containerized environments, and executing instructions with structured error recovery. Use when asked to: 'evaluate…
Design and implement OS-level resource controls for sandboxed AI agents using hierarchical cgroups, eBPF enforcement, and tool-call-level resource management. Use when: 'set up cgroups for AI agent containers', 'control memory for coding agents', 'isolate…
Build LLM-based multi-agent systems for supply chain inventory management using structured decision prompts and memory-retrieval (AIM-RM). Implements the beer game multi-echelon supply chain simulation with per-stage agents that use stepwise ordering prompts,…
Build intelligent alert lifecycle management systems for cloud infrastructure using graph-based denoising, RAG-powered summarization, and multi-agent rule refinement. Trigger phrases: - "reduce alert fatigue in our monitoring system" - "deduplicate and…
Build multi-agent adaptive learning systems that diagnose knowledge gaps and recommend targeted resources. Implements the ALIGNAgent framework: Skill Gap Agent (proficiency estimation + concept-level diagnostic reasoning) and Recommender Agent…