EcoPrint AI Transparency

Modern software development makes resource consumption difficult to see at the moment engineering decisions are made. Developers can see build times, test results, and application metrics, but often cannot connect a specific workload to the infrastructure signals observed during its execution, understand what changed between comparable runs, or distinguish attributable resource use from aggregate infrastructure activity. EcoPrint AI Transparency explores solving that visibility gap by bringing infrastructure measurement directly into the developer workflow through the CLI. A developer can wrap a build, test, or other workload with EcoPrint, which creates workload/run/attempt identity and process context, correlates the execution with SigSense infrastructure telemetry, and produces deterministic accounting and evidence. The prototype measures physical signals such as CPU/GPU/ANE power, total power, integrated energy, carbon, and water where supported. It also captures logical AI usage metadata such as provider, model, input/output/total tokens, and latency when the provider reports it. These domains remain explicitly separated: tokens are not energy, and attribution evidence is not the same as physical process-level isolation. EcoPrint adds baseline comparison, deterministic insights, process provenance, and optional AI interpretation through OpenAI or local Ollama. The AI operates downstream of deterministic measurement. Current measured facts remain authoritative, historical experience is contextual only, and unsupported AI explanations can be withheld when they conflict with available evidence. The intended users are software developers, platform/DevOps teams, and organizations building or operating compute-intensive and AI workloads. The broader vision is to move infrastructure and resource intelligence upstream—from something reviewed after deployment toward an observable engineering signal throughout ideation, architecture, development, testing, CI/CD, and production. Built with IBM Bob 2.0, EcoPrint demonstrates a working CLI-based approach to measuring, attributing, accounting for, and explaining infrastructure resource use while preserving clear measurement boundaries and evidence provenance.