Engineering Determinism: Practical Strategies for Reliable LLM Applications
Discover how engineering determinism transforms LLMs from unpredictable generators into reliable, production-ready systems.
The Geometry of Reasoning: A Technical Essay
How do different neural systems trained on different modalitiesconverge toward similar internal representations? Discover the math behind.
Insights from our CEO: Keeping a Career in Software Relevant in the Age of AI
Dive into Padraig Coffey’s keynote on navigating an AI-driven software career and discover the vital skills to future-proof your job.
The Subtle Truth About Determinism and Variance in LLMs
Let’s deconstruct the myth of “randomness” in LLMs to get a technically grounded view – demonstrating engineered determinism.
Context Engineering: State-of-the-Art Research
A practical industry report on context engineering—combining retrieval, memory, tools, and prompt design to scale and govern LLM and agent systems.
Is Your Data AI-Ready? 3 Realities from Tech Leaders
AI adoption is accelerating, but is your data ready? Tech leaders reveal 3 realities, and only 29% are “very well prepared.”
Why Your AI Initiative Needs “Failure Criteria”
Discover why defining “failure criteria” is essential for successful AI initiatives. Build an AI strategy that prioritizes long-term value.
Is Your AI Strategy Married to Your Business Strategy?
Discover the growth vs. efficiency lens, how to define ROI, and the simple steps to marry your AI strategy to your core business goals.
The Build vs. Buy Dilemma in AI: A Strategic Framework for 2025
Analyze the build vs. buy dilemma in AI with the Zartis AI Maturity Framework. Learn the strategic sequence: buy to validate, hybrid to extend, and build to differentiate.
Beyond the Hype: 5 Real-World Lessons on Moving AI from Pilot to Production
Explore 5 real-world lessons on strategy, validation, change management, and maintaining momentum to move AI from pilot to production