LLM Powered Autonomous Agents: Components, How They Work, and How to Deploy Them
LLM-powered autonomous agents plan, act and adjust with minimal human input. The core components behind them, how they work, and what deploying one actually involves.
Eigenform Articles
ML Model Serving: How It Works, Methods, and Best Practices
Model serving is what turns a trained model into something an application can actually call. How it works, how it differs from deployment, and how to do it reliably at scale.
LLM Agent Architecture: Components, Patterns, and How to Choose
LLM agent architecture is the arrangement of components (planning, memory, tools) that determines what an agent can do. The common patterns, and how to choose.
LLM Infrastructure: Components, How It Works, and What It Costs
LLM infrastructure is the compute, storage and serving stack that makes training and running large language models possible. Its components, how to build it, and what it costs.
What Is AI Orchestration? Components, Frameworks, and How to Implement It
AI orchestration coordinates multiple models, agents and tools into one working system. How it works, its core components, and when an organization actually needs it.
What Is AI Routing? How LLM Routing Works, Strategies, and Common Mistakes
AI routing sends each request to the model or tool best suited to handle it, instead of one model for everything. How it works, common strategies, and where implementations go wrong.
AI in Mineral Exploration: Methods, Data Sources, and Challenges
AI is changing how mineral exploration targets get generated and ranked. How AI-powered methods compare to traditional ones, what data they run on, and where they still fall short.
How to Test Generative AI Applications: Methods, Tools, and Challenges
Testing generative AI applications means covering risks static software testing doesn't touch: hallucination, non-determinism, unsafe output. The methods, tools and challenges involved.
Model Accuracy: What It Measures, Its Limits, and How to Improve It
Model accuracy is the most-cited performance number and the most-misread one. When accuracy is the right measure, when it isn't, and how to actually improve it.
LLM Use Cases: Applications Across Industries and How to Implement Them
Where large language models are actually being deployed today, how businesses implement them, and what to weigh before committing to a use case.