Technical Advisory
Implementing Self-Optimizing HVAC Systems for Cleanroom Environments
Self-optimizing HVAC for cleanrooms delivers stable temperature, humidity, and particle control with minimal manual intervention.
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Technical Advisory & Systems Research
Engineering Perspectives
Deep dives into Agentic Workflows, distributed systems, and the architectural rigor required to move AI from experimentation to enterprise-grade production.
Technical Advisory
Implementing SKILL.md: Best practices for portable agent logic
SKILL.md provides a portable contract that codifies agent skills for distributed systems. In production, teams need deterministic data contracts, bounded.
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Applied AI
Implementing Sustainable Procurement Guardrails in SAP Ariba: A Practical, AI-Augmented Framework
Guardrails for sustainable procurement in SAP Ariba are not a nicety; they are a production capability.
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Applied AI
Improving Client Communication with AI in Enterprise Environments
Enterprise client communication powered by AI can be reliable, auditable, and scalable when you design for production-grade workflows that balance autonomy with governance.
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Applied AI
Improving inter-rater reliability for AI QA
Inter-rater reliability is the backbone of credible AI QA in production. When multiple evaluators judge model outputs, consistency reduces risk, improves governance, and speeds up delivery cycles.
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Applied AI
Improving RAG accuracy in production: practical strategies for enterprise AI
RAG accuracy in production is a function of data quality, retrieval topology, and continuous evaluation. In practice, you measure and optimize end-to-end fidelity across the user journey, not just model scores.
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Technical Advisory
Incentivizing Innovation with Internal Agents
Internal agents are not speculative features; they are disciplined platform capabilities that translate governance, observability, and incentives into dependable automation at scale.
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Applied AI
Incident response for AI failures: a field-ready playbook for production systems
Failures in AI deployments are not a hypothetical risk; they are a production reality. This article offers a field-ready incident response playbook to shorten MTTR, preserve user trust, and enforce governance during AI outages.
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Applied AI
Including Supabase table policies in AI project instructions for safer production
In production AI, policy clarity is not optional—it's the difference between reliable systems and costly incidents.
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