Outreach Message

Send personalized outreach from prospect to logged outcome. The AI drives Research, Draft, and a send checkpoint.

Sales 5 steps 1 checkpoint Human approval Self-correcting
Use this workflow

Free to start · runs with your own AI

Workflow steps

Runs inside your AI conversation · the orchestrator drives

"Write a cold email to this prospect"

you — in any AI chat

  1. 1

    Prospect Intake

    Capture the prospect and the offer before researching.

    Record:

    • Prospect — name, role, company, and contact channel
    • Your offer — what you are reaching out about, in one sentence
    • Desired outcome — a reply, a meeting, a demo
    • Any prior contact with this prospect or account

    If this prospect came from a Prospect Research workflow, pull their
    entry from that list. If key details are missing, ask the operator.

    Save the prospect and offer as a task note with task_notes_add. The
    next step — Research — reads this note.

  2. 2

    Research

    Read the task notes with task_notes_list — the note from the Prospect
    Intake step contains the prospect and offer. Work from it.

    Research the prospect and account to find a genuine, specific hook. What
    good looks like:

    • One concrete, current detail you can reference — a recent post,
      a hire, a funding round, a product change, a stated pain
    • Why that detail connects to your offer
    • The right angle for this specific person, not a generic pitch

    A relevant hook beats a clever line. If you find nothing specific, say
    so rather than inventing it.

    Save the research hook and angle as a task note with task_notes_add. The
    Draft step reads this note.

  3. 3

    Draft

    Read the task notes with task_notes_list — the Research note holds the
    hook and angle, and the Prospect Intake note holds the offer and
    desired outcome. Work from them.

    Write the message. What good looks like:

    • Opens on the specific hook, not "I hope this finds you well"
    • Connects the hook to the offer in a sentence or two
    • One clear, low-friction ask matching the desired outcome
    • Short — respect the reader's time
    • The right tone and length for the channel (email vs LinkedIn)

    Save the full message as a task note with task_notes_add. The Send
    Review step reads this note.

  4. 4

    Send Review

    Read the task notes with task_notes_list — the note from the Draft
    step contains the message. Work from it.

    Check the message before sending:

    • Right name, role, and company — no merge-field mistakes
    • The hook is accurate and the claim is true
    • The ask is clear and matches the desired outcome
    • Any link works

    Ask the operator to approve the message for sending. This is a
    checkpoint — sending is irreversible, so the AI cannot advance until you
    approve. If you reject, the workflow returns to Draft.

    The AI pauses here and waits for a human to approve before the conversation continues.
    If rejected → returns to draft
  5. 5

    Log Outcome

    The message is approved and sent. Record the outcome so the next person
    — or a follow-up workflow — has the full picture.

    Save a task note with task_notes_add capturing:

    • Who was contacted, on which channel, and the date
    • The message that was sent
    • The result so far — replied, no reply, bounced, meeting booked
    • The next action and when, if any

    This note is the audit trail for this outreach and the named input for a
    Meeting Follow-Up workflow if the prospect responds. Close out the task.

  6. Workflow complete — outcome delivered, every step on record.

Why this workflow?

Without a workflow

  • A generic template goes out with the wrong first name and zero relevance to the prospect
  • The send happens before anyone checks the claim, the link, or the ask
  • Nobody remembers whether this prospect was already contacted or what the reply was

With ConvOps

  • The AI drives a Research step first, so the message lands on something specific about that account
  • The AI pauses at a send-review checkpoint so you sign off before the message goes out
  • The AI logs the outcome as a note, so the audit trail of who was contacted and what happened is already there

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