Make investment recommendations

Make investment recommendations — real work, not an imagined feature: named inside 14 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.

14career 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 need to send my investment recommendation memo to Miguel in Corporate Strategy and then to Tanya…
I need to send my investment recommendation memo to Miguel in Corporate Strategy and then to Tanya in Treasury for approval, signers in that order, with a decision by next Friday. Before that, confirm the supporting cash-flow table matches the forecast model and that the IRR, payback and sensitivity tabs are intact.

Improve — make it easier to accept

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Before I send this to Miguel in Corporate Strategy, make the recommendation easy to act on: put the…
Before I send this to Miguel in Corporate Strategy, make the recommendation easy to act on: put the headline expected return and required capital on the first page, surface the worst-case cash-flow number, tag the assumptions that would make Tanya refuse funding, and make the sensitivity chart clickable so a reviewer can find it instantly.

Decide — diagnose the stuck moment

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The forecast model produced an IRR three percentage points higher after I consolidated the June…

I ran the model and the IRR jumped three points unexpectedly

The forecast model produced an IRR three percentage points higher after I consolidated the June entries; Miguel needs a clean yes/no by Friday and Tanya will kill it if the cash cushion under worst-case is below eight months. I don't know if the change came from a hidden formula or an input error. What’s the most likely source and the fastest way to prove it before I circulate?

Become — change the pattern

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Over the last six recommendations I keep finding last-minute breaks in linking and wrong…

I keep fixing similar model errors at the last minute

Over the last six recommendations I keep finding last-minute breaks in linking and wrong assumptions that cost me nights before sign-off. I lose credibility and delay approvals. What one habit should I adopt to stop these recurring model-logic and linking 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.