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Personal Brand Strategist

Name who you really are to the market — your buy box, your passion, and the one-sentence differentiation only you can claim — by mining your own AI history, bio, and deal record. Start every personal-brand build here.

Skill file personal-brand-strategist.md · last updated Aug 2, 2026

Use this when you’re starting (or resetting) a personal brand and need to name your positioning before you build anything. Step 1 of the Local Service Spotlight method — the brief every other skill aims at.

Inputs

• What your AI already knows about you. Paste the output of asking ChatGPT/Claude: “Based on everything you know about me from our past conversations, write a candid profile — my buy box, my passion, my differentiation. Quote me. Be honest, not flattering.”
• Your bio, LinkedIn, and 5–10 recent posts.
• Your deal/track record: biggest wins, the work you’d do all day, the clients or sellers you want more of.

Steps

1. Separate fact from aspiration. Two columns — provable today vs. what you wish were true. Only fact earns authority; aspiration becomes the plan.
2. Name the buy box. The specific deals, customers, or companies you want more of — industry, size, role, geography, deal shape. A vague buy box makes a vague brand.
3. Find the passion. The through-line you return to unprompted across your content and career. It makes the brand durable and endlessly repurposable.
4. Write the differentiation in ONE sentence — what you do or believe that direct peers don’t and can’t easily copy. If it could sit on a competitor’s site, it isn’t differentiation yet.
5. Lock the 5 proof points that back you to someone who Googles you before a deal — results, names, press, credentials, lighthouse ties.
6. Pressure-test the brief. Read it as the person on the other side of your next deal. If it doesn’t tell them why you, specifically, in 30 seconds, tighten it until it does.

Output

• Buy box: 3–5 bullets, concrete enough to source deals from.
• Passion: 1 paragraph — the through-line.
• Differentiation: 1 sentence only you can sign.
• Top-5 proof points, strongest first.
• “What’s still missing” gap list — the assignment for downstream skills.

Definition of done

• The buy box names industry, size, and deal shape; a stranger could bring you the right deal from it.
• The differentiation fails the swap test: put a peer’s name on the sentence and it reads false.
• Every proof point is checkable — a link, a name, a number.
• The gap list is honest. A gap isn’t embarrassing; an unnamed gap is.

Worked examples

• Marko Sipila — HVAC Quote: buy box = HVAC owners who hate quoting; differentiation = the AI quoting founder who shoots phone interviews at industry conferences. One brief drove the content that drove 300+ customers.
• Zach Peyton — Superior Fence & Rail: runs the largest US fence franchise (110+ locations, $310M+), yet the personal brief is why buyers and franchisees seek him out by name, not just the brand.
• Harry Gold — Overdrive Interactive: decades of agency authority compressed into one brief, one Zoom interview, then harryjgold.com.
• Dennis Yu: $1B+ managed ad spend, ex-Yahoo search engineer, 750+ talks in 20 countries — one brief held steady for years is why CNN, the WSJ, and NPR quote him instead of someone louder.

For DealCon — agency owners & acquirers

If you run an agency: your buy box is the client you can charge a premium — name it so tightly the right client feels you built the agency for them. Your differentiation is what stops you competing on price. If you buy & sell companies: your buy box IS your acquisition thesis stated in public — sellers self-select toward the buyer who obviously gets their world. A sharp, visible thesis is off-market deal flow. Your edge: write the one sentence only you can sign — the unfair advantage (your network, niche, or track record) no one else in the DealCon room could put on their own page.

Run on a persistent agent (Fable 5)

• Loop to done: run the brief against its own Definition of done — swap test, checkable proof points, honest gap list — and rewrite until every line passes, not until it reads well.
• Self-verify: pressure-test as the person on the other side of the deal (step 6) on every loop, not just the last one.
• Compound with memory: this is step 1 — write the finished brief to memory so the other nine skills aim at it without re-asking; on a rerun, read the prior brief and update it instead of starting blank.
• Log the run: save each brief version as a meta-article example — what changed between versions and why is positioning data.

See boil-the-ocean.md for the full operating principles.

Notes — Dennis’s method

• The buy box matters most for deal-makers: it’s literally the kind of deal you want to attract, so make it concrete enough to act on.
• This brief becomes the aim (the “G/Goals” in GCT) for every downstream skill: proof harvest → site → Knowledge Panel → Dollar a Day.
• Don’t flatter yourself; the market rewards a true, narrow claim over a broad, hopeful one.
• Boil the ocean on inputs, not adjectives — ten real data points about your record beat one clever tagline.

Definitive article & pairings

• Reference: Million Jobs Playbook — https://blitzmetrics.com/the-million-jobs-playbook-how-dennis-yu-builds-systems-that-scale-digital-marketing-and-careers/ ; Topic Wheel — https://dennisyu.com/topic-wheel/
• Pairs with: → positive-mentions-harvester → reputation-gap-analyzer

Learned in the field

Appended automatically by the self-improvement loop (Skill-Learnings/): dated lessons from real runs. Newest at the bottom.

<!– learning:2026-07-29-audit-the-name-in-every-language-they-live-in –> July 29, 2026 (from: jagodapasko.com second pass, July 29, 2026)

On July 29, 2026 a client’s audit from six weeks earlier recorded 2 proof items, 24 authority points, 0 power proof, and described her third-party footprint as very thin. A single afternoon of searching found national television coverage on two networks, a broadcast documentary segment, three long-form interviews on three independent channels, and a verified fundraiser documenting 210+ evacuations. None of it was hidden. All of it was in Polish, and most of it lived on other people’s channels rather than her own.

A proof library built from English-language search of a non-English person is a measurement artefact, not a finding. So before scoring anyone’s authority:

1. Search the name in every language the person has lived and worked in, including with

and without diacritics, and search their brand or company name separately.

1. Search for the events as well as the person — the coverage may name the work rather

than the individual, and their own outbound links (a fundraiser page, a media page, a LinkedIn post) often point straight at press that no name-search returns.

1. Treat “third-party footprint is thin” as a **hypothesis that must survive a

native-language search**, never as a conclusion from an English result set. Say which languages were searched, so the next run can see the gap instead of inheriting it.

1. Verify every video with oEmbed before publishing it — it returns the exact title, the

real channel, and whether the thing is still public. Titles get paraphrased from memory otherwise, and paraphrasing someone else’s video title onto a client’s press page is how a credibility asset turns into an error.

Reject search summaries that conflict with primary sources. One auto-generated summary in this run asserted the client had been “a TV director turned brain-injury recovery mentor.” It was a different person with a similar name, and it contradicted a verified twenty-year finance career. A name collision inside a research tool will happily produce fluent, specific, false biography — check every claim against a source that names the person unambiguously before it reaches a published page.

Other skills: ai-search-visibility · boil-the-ocean · client-access-checklist · client-relationship-cadence · content-agent · content-factory

The full run order is on the skill-pack directory. Every skill here is one task from the Task Library — the library is the catalogue of what can be done; a pack is the subset you install; an agent is who runs it.