Articles
Practical methods for engineering AI agents across the Agent Development Lifecycle.
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Agent Engineering Isn't Software Engineering or ML. It Needs Both.
Agent engineering borrows from software engineering and machine learning but replaces neither. See what carries over, what is new, and where to start on Monday.
· Tune AI EditorialEval-Driven, Spec-Driven, Experiment-Driven: What Each Asks of You
Three labels you will hear for building agents: what eval-driven, spec-driven and experiment-driven work each require, how they combine, and where TDD fits.
· Tune AI EditorialFrom Demo to Dependable: Closing the Agent Maturity Gap
A five-level maturity ladder for agents, from 'it worked in the demo' to evidence-based releases, with signs of each level, a next step and a self-check.
· Tune AI EditorialHow Agent Engineering Changes Your Job, Role by Role
Seven roles, seven new challenges. For each one: what changes when you ship an agent, one habit to adopt this week, and one question to ask your team on Monday.
· Tune AI EditorialWriting Requirements for an Agent You Can't Fully Predict
How to turn 'the agent should be helpful' into acceptance criteria you can measure: hard limits, quality targets, trade-offs, thresholds and who decides.
· Tune AI EditorialWhy AI Tuning Is the Discipline That Separates Demos from Production
Most AI prototypes die in the gap between an impressive demo and a reliable production system. The secret weapon that bridges that gap? Systematic tuning.
· Amir Ben-Efraim