▸ USE AI TODAY · a workflow to steal

Rehearse a hard conversation with AI first

Say: 'Play [my manager / this client]. I'll practice asking for [X]. Push back realistically, then tell me how I did and what to say instead.'

Why it works: The raise, the pushback, the tough client call — rehearsing once against a realistic counterpart beats winging it live.

⌘ TODAY'S PROMPT · copy & paste  ·  From PromptSharp Sales

Account research brief: from raw filings to a first-touch angle

You have 30 target accounts and one hour. Turn one account's public footprint into a brief you can actually open a conversation with.

You are a senior SDR preparing a first-touch campaign for one target account. I will paste raw public material about the account. Produce: A) ACCOUNT SNAPSHOT — a table with columns: dimension (what they sell, who they sell to, revenue motion, recent trigger events, tech-stack clues), what the material says, and the exact quote or source line it comes from. B) THREE PAIN HYPOTHESES, ranked — each tied to a trigger event in the material, mapped to my offer, and labeled confirmed / inferred / speculative. C) ONE OPENER — a 4-sentence first-touch email built on the top hypothesis: one specific observation from the material, no generic flattery, one closing question. Materials: [PASTE: 10-K EXCERPT / EARNINGS-CALL NOTES / PRESS RELEASES / JOB POSTINGS / SITE COPY] My offer: [ONE SENTENCE: WHAT YOU SELL AND THE PAIN IT REMOVES] Rules: Do not invent facts about the account — if a claim is not in the pasted material, label it "assumption" and list it separately. Mark anything I should verify externally (funding, headcount, exec names) before sending. Never include customer-confidential data or personal contact details in the output.

Why: Reps stall on research because the raw material is unstructured. Forcing a quote-level source column kills the hallucinated 'insights' that make outreach sound templated, and the confirmed/inferred/speculative split tells you exactly what to verify before you hit send.

🔭 Where the signals converge

Where independent intelligence streams — macro podcasters, our email-intel desk, AI-lab feeds — line up on the SAME read, cross-checked against our own live trading algo. The one AI brief that shows you where unrelated operators agree.

AI as an INFLATIONARY / capex-supercycle force (not just deflationary productivity) [MEDIUM · email intel + podcasts agree]

AI capex & compute economics — hyperscaler buildout / 'the AI trade' [MEDIUM · email intel + podcasts agree]

The cross-source read: Cross-source tape today: 3 of 10 convergent themes lean defensive/structural-risk. Highest-conviction edge: 'Mega-cap tech distribution / late-cycle topping' (3-layer agreement, incl. our own algo model). Convergence = where independent operators agree; that's the higher-conviction read for brief/newsletter/algo than any single source.

Where they split: Direction tally across convergent themes: 3/10 lean defensive/structural-risk — the CONVERGENT sub-themes are more informative than aggregate inbox sentiment (which is typically split).

▶ Watch this week · stay an AI expert

The Cognitive Revolution

with Nathan Labenz · YouTube

Deep, practical interviews on how AI is actually deployed inside companies — the implementation reality between the hype and the research. Great for operators planning a real rollout.

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