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Skills from A Smart Bear

Observations: The raw, unjudged facts about who you actually are

Surface the raw material your ideal-customer definition is built from — what customers praise, complain about, and leave over — through twelve unsparing question categories, recorded vividly and judged later. For a company already operating online, it first scans public reviews and press to seed the walk. Adapted from Chapter 2 of Hidden Multipliers: Carol Loves You for You.

Input
Your company or product — plus your team's write-storm notes, if you ran one, or just yourself and an honest hour.
Output
An OBSERVATIONS.md of numbered, vivid, specific observations (O1, O2, …) organized by the twelve question categories — deliberately unevaluated.

What this is about

You must know who you are before you can define the customer who loves you for it. But the instruction "write down our strengths and weaknesses" does not work. Nobody knows where to start. Everyone makes excuses. The loudest voice fills the whiteboard. The book's answer is to start one level lower, with raw observations. You gather these through twelve detailed, vivid question categories. Examples: what customers praise when they choose you despite your faults; the complaint you cannot defend; what you are proud of, whether customers care or not; what separates your most profitable customers from the rest; what you claim to do well but do not; what you envy in competitors; what you would keep even if it cost you money.

This skill runs that fact-finding as a working session. If you bring a team's write-storm output, it processes the notes one observation at a time. It clarifies each one, removes duplicates, and sharpens the wording. If you bring nothing but yourself, it walks you through the twelve categories directly. It presses every vague answer into a specific, vivid fact. For example, it turns "support could be better" into "customers post screenshots of support wait times on Reddit." If your company already operates and strangers already talk about it online, the skill first scans that public record. It checks reviews, forum threads, press, and competitor comparisons. It files what it finds in an External Research section. This section seeds the walk and sharpens its prompts. These findings stay as candidates until you confirm them. A pre-launch company with no public footprint skips this scan. Two rules hold throughout, both from the book. First, observe like an outside consultant: record behaviors and outcomes, never justifications. Second, do not evaluate, blame, or act yet. Judging what is a strength or weakness is the next step's job. This step only gets the truth on the record.

Example invocation

You can invoke the skill like this:

/asb-carol-observations We're a 6-person bootstrapped SaaS doing email
deliverability monitoring, 4 years in, ~$50k MRR. I want to figure out
who our ideal customer really is — start with the honest look at us.

The skill walks you through the twelve question categories one at a time. It presses each answer into a specific, vivid observation and records it in OBSERVATIONS.md as you go. You end with the raw material. The next step, strengths-and-weaknesses, uses this material.

One practical note: say where you are working. Name a directory, or point at your existing files, when you invoke the skill. The skill then keeps the method's files together there. If you do not say, it asks before it creates anything.

From the source

Two sources form the foundation of this skill:

Supporting sources each supply a piece of the mechanism:

  • Write-Storming Workshop (appendix) in Hidden Multipliers — hiddenmultipliers.com — brainstorm alone, process together: the workshop mechanics this skill's team mode follows and its solo mode adapts.
  • Specificity: A weapon of mass effectiveness — why every observation must be specific and vivid: different readers interpret generic words in different ways, so generic words give no evidence.
  • Fail to face the truth, and you fail — the posture behind the whole exercise: look honestly at what is true, then decide what to do about it.