Evidence-led analysis for models, agents, automation, research and technical procurement.
A production-readiness framework for engineering leaders
A coding agent should earn autonomy through controls and repeatable evidence—not through an impressive demo. This framework turns repository access into a staged engineering decision.
Turn model selection into a workload decision
A practical way to select models using task evidence, constraints and switching costs rather than a single public score.
Design approval around consequence, not anxiety
A control map for deciding which actions can run automatically and which require informed human approval.
An evidence ladder for technical teams
How to decide whether a research result deserves a prototype, a controlled trial or no engineering time yet.
Measure systems, interventions and failure—not demos
A benchmark design for teams evaluating tool-using agents on their own operational tasks.
A buyer guide for engineering and AI leads
A vendor-neutral scorecard covering evidence, integration, security, economics, operations and exit risk.