AI for Excel
Pack the right inputs
Context is a curated evidence packet, not a dump of everything the tool can accept.
Before you start
Why this matters
Without opening an AI tool, write the acceptance test for this job: build and validate a June regional-revenue formula in Excel 365. Name one fact that must be exact, one judgment a person must make, and one condition that should stop the workflow. Compare your answer with the professional standard below; the gap is what you should practice.
1Learn the idea
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Build the input packet
See it
Role + task + context + format = clearer output
For build and validate a June regional-revenue formula in Excel 365, assemble only what changes the answer: column letters and headers, three sample rows, desired cell, Excel version, locale separators, date boundaries, and blank/error behavior. Label each item by authority and date. A source-of-truth document outranks a memory-based note; a current error log outranks a description of last month's behavior. State conflicts instead of letting the model blend them.
Use a four-part packet: task, evidence, constraints, and output contract. Put untrusted content inside clear delimiters and say that it is data, not instruction. Include representative examples, especially one normal case and one boundary case. Omit irrelevant history; excess context can hide the one line that controls the result.
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A concrete handoff
Excel 365, comma separators. A=Date, B=Customer, C=Region, D=Revenue; F2 contains a region. In G2, total D where C=F2 and A is in June 2026. Give one formula, explain every condition, and provide normal, boundary, and blank/error tests. Do not invent columns.
Before sending, annotate the packet. Mark which values are verified, which are illustrative, and which are unknown. If a screenshot is involved, transcribe critical small text. If structured data is involved, include headers, units, software version, and null behavior. If creative material is involved, record ownership and permitted use. This is how context becomes operational rather than decorative.
A useful response would look like this: A SUMIFS formula using >=DATE(2026,6,1) and <DATE(2026,7,1), with an explanation that the exclusive upper bound includes every June timestamp. That description is intentionally observable. “Looks good” is not acceptance. The operator must calculate a tiny hand-checked table, test June 1 and June 30, inspect dates stored as text, confirm absolute references, and compare the total with a filtered sum. Keep the source material beside the draft so review means comparison, not memory.
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Minimize and protect
The privacy boundary is specific: do not upload payroll, customer records, account numbers, hidden sheets, or an entire confidential workbook; substitute synthetic rows. Create the smallest synthetic example that preserves the problem. Replace names and identifiers consistently so relationships remain testable. Redaction is not merely drawing a box: crop surrounding notifications, remove metadata where relevant, and check that hidden sheets, comments, or revision history are not included.
Poor packets lead to predictable failures: wrong locale separators; text dates; shifted ranges; hidden filters; formulas filled down with relative criteria cells. Another common failure is silently changing the source packet mid-run. Save a version or hash of the inputs beside the output, especially when another person will reproduce the work.
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Context quality drill
Rate a packet from zero to two on six dimensions: relevance, authority, recency, completeness, privacy, and reproducibility. A score below two on authority or privacy blocks the run. A low completeness score does not invite invention; it creates a question for the owner.
Continue learning · glossary & guides
- Can a reviewer distinguish supplied fact, example, and model inference?
- Could another person reproduce the run from the saved packet?
- Reference · Related concept
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