Analyze investment projects

Analyze investment projects — real work, not an imagined feature: named inside 17 evidenced career tasks. Below are four ready AI prompts for it, one per height of help: do it, make it easier to accept, decide when you are stuck, and change the pattern for good.

17career tasks name it
4prompt heights

The four heights

The same task, four distances: today's deadline, the next reviewer, the stuck moment, the pattern.

Execute — do the immediate task

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I have projected cash flows, capex schedules and discounted returns for a proposed conservation…
I have projected cash flows, capex schedules and discounted returns for a proposed conservation lodge investment. Send the 'Lodge_IV_Proj' spreadsheet with a summary sheet showing NPV, IRR and payback to the investment committee members Sam and Noor, asking them to sign off by Wednesday so we can proceed to term-sheet drafting.

Improve — make it easier to accept

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Before I present to the investment committee, make the model board-friendly: put NPV, IRR, payback…
Before I present to the investment committee, make the model board-friendly: put NPV, IRR, payback and the five-year revenue sensitivity at the top, label assumptions with sources, highlight any inputs that swing equity returns by more than 2 percentage points, and add a short note on which operational risks would most affect those numbers.

Decide — diagnose the stuck moment

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I updated occupancy from 60% to 45% and the IRR fell below our hurdle rate; Sam and Noor will want…

The IRR dropped sharply after I updated occupancy assumptions.

I updated occupancy from 60% to 45% and the IRR fell below our hurdle rate; Sam and Noor will want to know if the drop is realistic or an overly conservative assumption. I don't have recent comparable occupancy data and fear either understating upside or getting the committee to reject the project. What's the most defensible next check and the phrasing to present both scenarios?

Become — change the pattern

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We keep losing time and credibility rebuilding full models for every small investment because…

We keep rebuilding financial models for small projects the same way.

We keep losing time and credibility rebuilding full models for every small investment because assumptions are scattered and sensitivity checks inconsistent. Recommend a lean model template and three modeling habits I can enforce so future project reviews are faster, assumptions comparable, and committee discussions focus on trade-offs not spreadsheet errors.

Where the evidence lives

Who was seen doing this, and what people really ask.

Software tasks in the LLOS Work Atlas come from evidence, never a feature list: careers attested to do the work, real job descriptions, and the questions people actually ask (with their view counts). Facets — feature, workflow, troubleshoot, administer, deploy, scale — are open metadata: the work decides, not a taxonomy.
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The rest of the map

Same library, five ways in.