Who it is for
For managers who dread the feedback, 1:1 prep, reviews, and tough conversations the job demands.
Draft and rehearse feedback, 1:1 prep, reviews, and tough conversations with AI.

Most of what makes managing hard isn't the work — it's the words. You know someone is coasting but can't say it without blowing up the relationship. The 1:1 is in two days and you've got nothing.
Six weeks in, most people hit the same wall: reviews got easier, but the conversations they avoid stayed avoided. You close that gap.
For managers who dread the feedback, 1:1 prep, reviews, and tough conversations the job demands.
You watched a direct report dominate last Tuesday's planning meeting. Three quieter teammates went silent after the second interruption. Now you can name it out loud.
Ask managers what 1:1s are for and you get a shrug dressed as an answer: "staying connected," "checking in." Ask their reports and it's a status update that could've been an email. You make it worth showing up for.
Some conversations you replay on the drive home — not because they went badly, but because you never had them. The report who keeps missing deadlines while you keep absorbing it. You practice it before it's real.
The convenience is the danger. To get a useful edit on a hard review, you paste in the name, the incident, the salary band, maybe the medical leave behind the dip. You learn where to draw the line.
Spend fifteen minutes building the foundation you'll use throughout. Pick your tool and one AI model — ideally one your employer approves. Find its data-retention setting, turn off training on your inputs if you can, and write down what you found.
When a prompt works, don't lose it — but keep only the ones that earn their place. Run each through this: Does it name a role for the model? Does it carry specific context, not a category? Are length, tone, and format explicit? Is it anonymized — no names, no sensitive data?
Type "Help me give feedback to an employee" into your AI tool right now. What comes back is generic — timely-and-specific tips you already know. Nothing is wrong and nothing is usable, because you gave the model nothing. It filled the vacuum with averages.
Treat these as ingredients, not a script. You won't always use all five, but you'll know which one is missing when output disappoints. Role — who the model should act as: "an experienced people manager coaching me," which sets vocabulary and judgment. Context — the real situation, in specifics.

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EPUB, PDF, and HTML are included so you can read on an e-reader, keep a designed copy, or use the searchable browser version.
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