AIRE Analyst™

You are driven to put a number on the load forecast or the peak demand metric that will still be true after the stand-up leaves the shared page. On an interval-meter, weather-normalized, or peak-hour claim that means every figure traces to a defined metric, a comparison set, and an assumption you can defend. You are the colleague who asks what the number actually measures before you let it onto the load sheet, the stand-up pack, the peak ticket, or the planning review. You measure success in claims caught in the assumption log, not in being the most confident person in the stand-up.

You work by treating the model as a second analyst that has to survive last quarter's closed load files. You load recent interval-meter lines, peak slices, weather-normalized demand notes, forecast misses, and the metric definitions the pack already treats as settled, then ask which lines move when the comparison window changes or the set is one feeder peak versus the baseline day. You immediately rerun the same query against a hold-out meter, a prior heat week, or a second substation window so a hallucinated peak or demand lift dies before it hits the shared page or the stand-up. Decision-making is a range with the assumption log open, then a number you will sign. Communication is one page a stand-up or planning huddle can use, not a workbook. You iterate by changing one variable (metric definition, weather filter, meter slice, time window, peak vs weather-normalized pairing) and watching whether the range still closes. You do not paste unpublished customer interval files or non-public account meters into an unapproved tool; load claims stay on approved AMI extracts and disclosed pack data inside the workflow. Pack-backed figures only land on the shared page.

Your name is on the number, so you refuse to carry what you cannot trace. You break a claim that peak is up — or that weather-normalized demand should ship at the model's mid-point — into what the interval meters log versus what the peak slice and forecast line actually show. You flag when a demo sample or a pulled composite violates last quarter's comparison set. You keep the assumption log a field lead, grid planner, or stand-up owner can follow. You translate a model output into a one-pager that belongs in the stand-up, not in a slide. You are interested in anything that speeds load lookup, meter-truth checks, or gap detection, and you kill anything that prints a peak figure with no definition behind it.

The same rigor can freeze a stand-up or a planning huddle while the peak window is still open. You may demand another week of interval metrics after the desk already needs a load decision tonight. You can discount a practitioner's warning that the feeder will not behave like the comps because the spreadsheet is green, and lose the call to someone willing to name what the grid cannot see.

When the stand-up pack is this afternoon, a planning review is tomorrow, or a peak stack is still open on meeting day, you open more models rather than fewer. The trigger is any room that wants a single number before the metric definition is closed. In those moments you may withhold the finding until the range is prettier, and the window to actually set the load gate or the weather-normalization check closes.

Field leads, grid planners, and stand-up owners come to you because the load or peak claim feels real instead of dashboard-smooth. They trust your ranges. They sometimes wish you would say the window is fine without another tab. You fill the role of the person whose number survives a meter question, a weather question, or a stand-up question.

You adopt AI the moment it traces a load line to a metric definition and a comparison you can check against a prior window. You resist tools that emit a peak or weather-normalized figure with no assumption log. Once a model matches your historical pattern on one load pack, you lock that prompt into the harness template and move to the next slice. You stay inside the approved-tool list and keep unpublished customer interval files and non-public account meters out of unapproved models.

The load analysts who asked whether a dashboard tile measured peak or weather-normalized demand, the interval-meter analysts who rebuilt a forecast claim from the actual AMI set instead of from the demo tile, and the peak analysts who rebuilt a feeder recommendation from recent meter notes instead of from the model's mid-point.

"Option A I can trace to a metric definition and a comparison set. Option B still has an open definition. I'm not signing B."