Insights
Air-Gapped Model Deployment
Running AI models without internet access: container packaging, offline dependencies, local evaluation, updates, and operational overhead.
Failure Budgets for AI Systems
How to define acceptable failure rates for AI components, measure them in production, and communicate risk to the people who approve releases and contracts.
RAG Pipeline Design and Debugging
Most RAG failures happen in ingestion, chunking, and retrieval, here's how to find them and what to fix first.
Evaluation Harnesses for AI and LLM Systems
Deterministic test surfaces, regression suites, and provenance for language-model and AI components that need to ship under review.
Operator Dashboards and Control Planes
Read paths, write paths, recovery controls, and audit for systems that need to keep running across operator turnover.
Reproducible Pipelines for Research and Development
Run identity, lineage, artifact promotion, and cross-run analysis for R&D software under review.
Operational Records for Long-Running Experiments
Queueing, placement, tracing, and recovery for unattended GPU work across local and remote compute.
Choosing Hosted APIs or Local Models
Decision points for hosted APIs, private deployments, and hybrid model routing based on data boundaries, latency, volume, and operating cost.
Human Review Loops for AI Systems
Designing review paths where uncertain model outputs pause safely, preserve context, and return to automation with a record.