LLMOps: Turning Chatbots into Production-Grade Systems
Aaron Wise
LLMOps is the essential framework for transforming experimental chatbots into reliable, production-ready systems.
Tag
ai governance
MLOps vs. LLMOps: Choosing Between MLOps and LLMOps for Business Impact
Aaron Wise
MLOps industrializes predictive models, while LLMOps operationalizes large language models for generative tasks.
The Sunk Cost of Intelligence: Lessons from AI’s Failures and False Starts
Aaron Wise
AI projects fail not because the models are flawed, but because organizations ignore data quality, business alignment, and long-term operational costs.
When Models Wander: Managing Drift in ML and LLM Systems
Aaron Wise
Model drift in ML and LLM systems demands continuous monitoring, evaluation, and retraining to keep outputs relevant and aligned with real-world changes.
The Secret Life of Data: How Labels, Embeddings, and Vector DBs Power Intelligence
Aaron Wise
Modern AI depends on integrated ecosystems of labeling, embeddings, vector databases, and feature stores not isolated tools.
When Prompts Attack: Building Defensible LLM Infrastructure
Aaron Wise
LLM security requires layered guardrails across the AI software development lifecycle to prevent injection, leakage, and abuse.
Terms of (Algorithmic) Endearment: Engineering Trust into Your AI Stack
Aaron Wise
Engineering trust into your AI stack demands ethics embedded in product design through bias audits, explainability tools, and cross-functional oversight.
Scaling Wisdom: Designing Human-in-the-Loop Architectures for Intelligent Agents
Aaron Wise
Human-in-the-loop agentic AI combines autonomous decision-making with strategic human oversight to balance speed, control, and accountability.
Automate the Boring, Govern the Risky: The Dual Mandate of Modern Data Teams
Aaron Wise
Data teams must automate routine workflows while actively governing high-risk AI and data practices to ensure both speed and trust.