Grok Bot for GTM

This is how I use Grok Bot for Enterprise GTM at SpaceXAI.

When we were initially dogfooding this product internally, Grok Bot rapidly gained adoption throughout the company, and I created an internal Notion doc on how I use Grok Bot to share with my team. I wanted to share it externally if it's helpful for other GTM orgs setting up @bot .

Grok Bot feels different for me as it's not just a thinking partner, but I can trust it to go off and actually do things end-to-end. Every week it learns more about how I work, and gets sharper.

Tips for getting started

Make sure @bot is connected to what you leverage daily, ie: Salesforce, Gmail, Calendar, Sheets, Drive, Slack, Notion, Granola for meeting notes, Figma for slides, X, LinkedIn, your data warehouse and more.

Bot has its own computer that runs 24/7 so you can accomplish tasks while your laptop is shut.

Your bots have memory so will remember your preferences, and will learn your writing style. Ask bot to scan your gmail and slack for how you write.

One of my favorite ways to use bot is through the mobile app, and voice input so I can give bot tasks when I'm not at my computer. This makes putting together slides or pulling information from tools really convenient when I don't have access to my laptop.

Run your own team of bots

Chief of staff

My Chief of Staff owns meeting prep, inbox and post-call drafts, orchestrates the rest of the team. You can tell your chief of staff to spin up other agents, and organize your bots in sections. I like to pin my Chief of Staff as I use this bot most frequently.

Daily meeting prep

Tell your bot to create a routine to prep you for meetings for the day and pull from your tools (Salesforce, Gmail, Slack, Granola, Gong, or online research if it's a new meeting), I prefer a short, skimmable, output that I can read on my phone as I'm commuting to work. You can also have your bot create customized decks ahead of your calls for the day (it calls my slides bot).

Routines

Scan inbox and auto draft replies:

1Scan my work inbox for messages since the last run that plausibly need a reply: customer and prospect threads, renewal or pricing questions, intros, direct questions to me. Skip newsletters, automated notifications, receipts, calendar RSVPs, and internal noise. For each one, give me a short digest in chat: sender, subject, one line on what they need, and a proposed reply in my voice. Do not auto-send. If nothing needs a reply, send no message at all.

Automate follow-up drafts from Granola or Gong notes:

1Find external calls that ended since the last run, meaning any meeting with an attendee outside my company's domains. Meeting notes are the source of truth. Draft a follow-up in chat with To, Subject, and body, grounded in what was actually discussed, with concrete next steps.

Prospecting bot

Builds pipeline gen plans, pulls intent data, does deep research (will watch webinars, listen to podcasts, find blog posts, scan LinkedIn/X for relevant posts). Customizes messaging based on company priorities and personal hooks, drafts in gmail, and puts together messaging in your voice. I like to run this overnight to have it ready in the morning.

1Build me a prospecting sheet. Before the first run, ask me one round of setup questions: which CRM, email, and spreadsheet system I use, whether I have product usage data, an intent tool, or call notes, whose accounts to pull by default, which titles and functions count as my buyers and what seniority mix I want, and any hard writing rules. Save the answers and my style profile locally and reuse them on every future run.
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3Before drafting any outreach, learn my voice from real sent mail: pull 15 to 30 recent sent messages, prefer genuine prospecting emails over internal one-liners, strip signatures and quoted threads, and save a style profile covering greeting, sentence rhythm, how I open, how I make the ask, and my sign-off. Refresh it if it's older than about 30 days.
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5For each run: confirm the parameters with me if I didn't specify them, especially which titles and functions to target this time, the seniority mix, and how many accounts and contacts. Don't assume last run's title filter still applies, ask. Then discover my CRM's real field and stage names first, don't assume them. Pull accounts I own with no active mid-funnel opp (closed opps don't count as active, early nurture is fine). Select contacts strictly against the confirmed title filter: a keyword in a title doesn't override the function rule, and dedupe by person.
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7Enrich every row: per-account compelling events (funding, launches, AI initiatives, exec hires) and per-contact recent posts or talks, with citations. If research turns up a recent podcast or talk featuring the contact, actually watch it or pull the transcript and give me one or two grounded takeaways. Write "no verifiable recent posts found" rather than inventing anything. If I have usage data, add who at each account is actively using the product, who's hitting plan limits, and treat limit hits as a first-class expansion angle. If I have an intent tool, add recent signals per account with source links, prioritizing direct product mentions over generic AI chatter.
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9Guardrails: surface open opp stage, amount, and last CRM activity on every row so we never treat warm pipeline like a cold list. Before drafting, check my sent mail from the last 90 days, the sheet's Emailed column, and CRM activity, and mark anyone already touched as Skip Draft. Keep them on the sheet, just don't re-pitch them.
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11Deliver a live spreadsheet link, never a CSV. Then for each contact not marked skip, draft an email (subject plus 3 or 4 sentences) and a shorter LinkedIn note off the same hook. The LinkedIn note never mentions that I emailed them. Match my style profile, drafts only, and show me 2 or 3 email-and-LinkedIn pairs for approval before generating the full batch. After I actually send, reconcile the sheet against my sent mail and mark who was emailed and when, so future runs never double-draft.

Customer expert

One agent per strategic account (works for top prospects too). It watches the relevant Slack channels, digests calls, emails, and Slack threads, and runs a weekly media rundown on the account (relevant exec posts on X / LinkedIn, watches webinars, finds podcasts and blog posts). It also flags feature requests from calls, updates me on support tickets, and finds relevant new features for the customer.

Weekly media rundown:

1Weekly media rundown for [account]. Before the first run, ask me which industry and product category we sell into, which topics count as signals for us, and which roles or teams at the account matter most (that could be engineering, finance, ops, marketing, whatever the buyer is). Save the answers and use them on every run.
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3Scan for NEW content only: web search for webinars, podcasts, and recorded talks featuring people at the account, prioritizing the roles I told you matter, plus exec strategy interviews. Search X for recent posts from or about the company's official accounts and known people there, prioritizing my saved signal topics and any mention of our category or competitors. Keep a state file of everything already covered and compare against it so you only report genuinely new items.
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5For each new item, actually consume the content. Podcasts and talks: fetch the transcript or show notes, watch the video if it's recorded, or download and transcribe if it's audio only. Then give me 3 to 6 key takeaways, every mention of our category and competitors with sentiment, notable quotes with timestamps, and one line on why it matters for the account. For X posts: author, date, the text, a link, and why it matters. Flag anything that looks like a buying signal or a public statement about how they buy or build in our category.
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7Send one weekly roundup. If nothing new, send a single line saying so. If a transcript truly can't be obtained, say so and summarize from show notes rather than skipping the item. Update the state file after every run.

Data analysis agent

I connect this to the relevant tools to track usage data across my book.

Product expert

I call this one "Cursor 10x engineer". An agent connected to the codebase for questions deeper than my product knowledge. When a customer asks something technical live on a call, I ask this agent and get a customer-facing answer back, and don't need to ask an engineer or dig through Slack, Notion, docs, etc. If you don't have repo access, an internal knowledge tool like Glean works as the source instead.

1:1 agent

Preps my weekly manager sync, I Granola our meetings so I can hand off tasks my manager and I discussed from our 1:1s and set up reminders.

Forecasting bot

Pulls from Granola, Gong, Slack, and email, and auto updates Salesforce opportunity notes. I give it the format I want the updates in, and this helps me streamline forecast calls and ensure my notes are constantly up to date.

Slides

My slides bot owns customer decks in Figma using our brand system and a master deck it maintains. It makes copies to customize per customer and even translates decks into other languages. Give the bot your design guidelines up front.

My favorite skill is to auto-update slides while I'm on a customer call, based on the Granola transcript.

Stop the Granola recording 5 or 10 minutes before the call ends and run it live, so you wrap up the call with a slide built from what the customer just told you during Discovery, or use it as a follow-up or opener for the next call.

1Fill or rewrite the "What we've heard" slide in my deck from the meeting notes. Prefer the meeting notes tool over memory, Slack, or email. Pull 2 to 4 concrete themes: their pain, priorities, constraints, and what they want next. Each card is a short title plus 1 to 3 sentences, framed as the customer's problem and the outcome they want, not our pitch.
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3Edit the existing slide in place: keep the layout, remove placeholder copy from other accounts, fix stale logos or wrong company names, match whatever brand styling is already there, and show me the result when done. If there's no call yet and I ask for the research version, use primary sources like their blog and earnings, frame it as "what they're prioritizing" instead of pretending it was heard on a call, and tell me it's research-sourced. Don't add next steps or roadmap slides unless I ask.

Sales Coach

Have your bot watch your external calls on Gong, and give you feedback on what you could improve or what went well.

Helpful tips/skills

1. Onboard Grok Bot like a new teammate. The first time we do a task together, I ask the agent to record, take over the computer and demonstrate, then have it turn the recording into a skill. ie: I showed my bot how I like to research stakeholders on X.

1. Feed it your writing. Have it scan your sent mail and build a style profile before it drafts anything. Give your bot a few examples of outreach you're proud of.
2. Give your bot feedback and make rules for output you don't like. I create skills (ie: I have a anti-slop skill) and rules that I continuously edit over time, and every time I steer my agent I have it add to my skill.
3. Your bot can parallelize work, tell your bot to spin up multiple cloud agents for parallel tasks, and create a skill for this.
4. Ask your Chief of Staff to take a look at all your bots/tasks and if there's anything you can further automate, parallelize, or better organize. You can also ask for it to clean up unnecessary routines.
5. You can put bots in a group chat to work on a task, and your bots can call your other specialized agents. (ie: to create slides my Chief of Staff bot often calls my slides bot).

Every week I iterate on how I use Grok Bot, it's the first AI tool that feels like a trusted colleague, and I don't need to constantly rewrite output or babysit the agent. Most of my time during the day is on calls, so I used to have to spend hours of the day in the evening catching up on admin work. Now I can pass much of that work to my bots and spend more time in front of customers.

You can try Grok Bot here and let me know your feedback!