AI Insights & Technical Compliance Hub
Field notes from production AI.
Deep technical breakdowns from PTForce AI engineers on inference optimization, retrieval architecture, continuous training and agent orchestration — plus practical compliance guidance for leaders building global AI teams.
Navigating STEM OPT Extensions for Enterprise AI and Machine Learning Engineers
How AI teams can structure roles, training plans and supervision to support a compliant 24-month STEM OPT extension.
Read article →Technical ComplianceDay 1 CPT to STEM OPT Trajectories: Maintaining Compliance in AI R&D Roles
Understanding the scrutiny around Day 1 CPT programs and how to evaluate continuity risk for AI research hires.
Read article →Technical ComplianceH-1B Specialty Occupation Petitions for Generative AI and LLM Architects
Articulating why LLM architecture roles require specialized degrees — and avoiding vague job descriptions.
Read article →Technical CompliancePrevailing Wage Classifications & LCA Compliance for Senior MLOps Specialists
Choosing occupational classifications and wage levels for MLOps roles and maintaining public access files.
Read article →Technical ComplianceCap-Gap Protections: Continuity Strategies for Machine Learning Researchers
How cap-gap extensions keep ML researchers working between OPT expiration and H-1B start dates.
Read article →AI InfrastructureOptimizing Large Language Model Inference Latency with vLLM and TensorRT-LLM
Practical levers — batching, KV cache, quantization and speculative decoding — for cutting LLM latency and cost.
Read article →Model EngineeringArchitecting Production-Grade Retrieval-Augmented Generation (RAG) at Scale
Hybrid retrieval, re-ranking, chunking strategy and evaluation for RAG systems that hold up under real traffic.
Read article →AI InfrastructureMitigating Model Drift: Building Continuous Training Pipelines on Kubernetes
Detecting data and concept drift and automating safe retraining and promotion on Kubernetes.
Read article →Model EngineeringMulti-Agent Orchestration Patterns: Moving Beyond Basic Prompt Chains
Supervisor, planner-executor and critic patterns for reliable, observable multi-agent systems.
Read article →AI InfrastructureEnterprise Zero-Trust Data Governance for Private On-Premise LLM Deployments
Identity-aware retrieval, network isolation and prompt-injection defenses for private LLM platforms.
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