Content cluster
AI Engineering Practice
The craft behind AI agents: retrieval, evaluation, tool design, routing and cost control.
The craft behind AI agents: retrieval, evaluation, tool design, routing and cost control. This cluster currently holds 5 published articles, all written by Muhammad Usman Akbar and anchored to a pillar page that covers the topic in full.
Start with the pillar
The pillar page for this cluster covers the subject as a whole. The articles below go deeper on specific questions within it.
Articles in this cluster (5)
AI Engineering Practice
How to Build an Evaluation Harness for LLM Agents
Why agent systems degrade without evaluation, how to build a trajectory-level harness, and what to measure beyond simple final output correctness.
3 min read
AI Engineering Practice
Reducing LLM Costs in Production: What Actually Works
The techniques that genuinely reduce language model spend in production, ranked by impact, and the ones that look promising but rarely move the number.
4 min read
AI Engineering Practice
RAG vs Fine-Tuning: How to Decide
A decision framework for choosing between retrieval and fine-tuning, the situations where each clearly wins, and why most teams should try neither first.
4 min read
AI Engineering Practice
Guardrails for Production AI Agents: A Design Guide
How to constrain what an agent may do, design escalation paths that preserve context, and decide which actions should never be automated at all.
4 min read
AI Engineering Practice
Model Routing with LiteLLM: A Practical Guide
Why a model gateway belongs in front of every production LLM system, how routing and failover should be designed, and what to instrument from day one.
4 min read
Frequently asked questions
What does the AI Engineering Practice cluster cover?
The craft behind AI agents: retrieval, evaluation, tool design, routing and cost control. Articles in this cluster link back to the pillar page at /solutions/ai-agents, which covers the subject comprehensively rather than in article-sized pieces.
What is a content cluster and why use one?
A cluster is a pillar page plus supporting articles that all link into it. It exists because search and answer engines reward demonstrated topical depth rather than page count, and clustering makes that depth legible to both.
Who writes these articles?
Muhammad Usman Akbar, founder of Hire Unicorn Developers and principal engineer at FISTA Solutions. Every article carries him as the author entity, with structured data linking to his verified profile.
How often is this cluster updated?
Articles are added in batches and existing ones are revised when the underlying facts change — particularly in the circular economy cluster, where delegated acts under EU ESPR are still being adopted. Each article shows its last updated date.