◆ MATLAB

Calculate weekly and yearly averages

This is real work, not a feature someone invented — it comes from real job ads and real questions people asked. Below are four ready AI prompts: get it done, make it easy for the next person to say yes to, work out the right move when you are stuck, and stop it coming back.

4prompts

The same task, four prompts

today's deadline · the next reviewer · the stuck moment · the pattern
AExecute — do the immediate taskCalculate the weekly and yearly average temperatures from the 'sensor_data.csv' file,…+
Calculate the weekly and yearly average temperatures from the 'sensor_data.csv' file, specifically for the 'Outside_Temp' column, and save the results to a new file called 'temperature_averages.txt'.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
BImprove — make it easier to acceptBefore I finalize these sensor calculations for the quarterly report, make sure the weekly and…+
Before I finalize these sensor calculations for the quarterly report, make sure the weekly and yearly averages for 'Outside_Temp' are robust. Exclude any readings marked as 'NaN' or outside the expected -20 to 50 Celsius range, and flag if any week has fewer than 100 valid data points.
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
CDecide — diagnose the stuck momentI just ran the average power consumption calculation for Q3, but the results look off. We had a…+
I'm trying to calculate the average power consumption for the last quarter, but the data has gaps and spikes, and I'm worried about under- or over-reporting to the board.
I just ran the average power consumption calculation for Q3, but the results look off. We had a sensor outage in July and a known power surge in September. If I just average everything, it won't reflect real usage. How should I best handle these missing values and outliers to give the board a truthful picture without causing alarm?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?
DBecome — change the patternI spend too much time cleaning up sensor data before I can trust the averages. Every time I get…+
I keep struggling to get reliable averages from noisy sensor data, leading to rework and questions from management.
I spend too much time cleaning up sensor data before I can trust the averages. Every time I get a new dataset, I have to manually identify and handle missing values, outliers, and unit inconsistencies. What habit can I change to build more reliable and repeatable averaging processes from the start, so I'm not constantly re-validating numbers for the project lead?
when the reply comes backPush once: ask it to sharpen the weakest part, and to say what it assumed. Helpful?

Questions people actually ask

honest answers, no sign-up

Every task here was seen in the real world. Someone doing the job named it, a real job ad asked for it, or a lot of people asked about it online.

If nothing real showed a task, it is not on the page. That is the whole rule.

They are the same job approached four ways, because what you need depends on where you are.

Get it done today. Make it easy for the next person to say yes to. Work out the right move when you are stuck. Learn the pattern so the job stops coming back.

For most of these jobs it can carry the heavy thinking - draft it, sort it, check it, rehearse it with you.

It cannot sit in your chair, take the blame when a number is wrong, or notice what nobody wrote down. Let it do the first 80%. Keep the last 20% that is truly yours.

No. Copy any prompt and paste it into the AI you already use. No account, no score, no wall in the way.

Any of them. The prompts describe the work rather than naming a product, so they are not tied to one assistant.

That is also why they keep working when you switch.

Change it freely. Every prompt is a starting line, not a rule.

Put in your real numbers, your real names and your real deadline. The more you make it yours, the better the answer comes back.

The tasks come from real job ads, published job data and the questions people ask in public forums.

The steps come from MATLAB's own documentation, with practitioner sources for the traps the manual does not mention.

Push once. Ask it to sharpen the weakest part and to say what it assumed.

Most wrong answers come from a missing detail rather than a bad prompt - tell it the thing it could not know.