# Ross Keating

Ross Keating builds tools and practices for sales teams. Keating is launching Overpath, an AI sales teammate called Molly, designed to help reps manage deal follow-up, CRM updates and coaching.

- Profile: https://b2binfluencer.marketing/creators/ross-keating/
- LinkedIn: https://www.linkedin.com/in/keatingross
- LinkedIn followers: 34,627
- Topics: artificial-intelligence, sales
- Based on 9 dated posts, latest 2026-10-08

## Summary

Ross Keating is most useful for explaining how AI agents can handle sales follow-up, CRM updates and live-deal coaching.

- Best for: A B2B SaaS sales-enablement company wanting a conference talk for sales leaders considering an AI sales coach.
- Not for: A consumer lifestyle brand seeking paid endorsement, product demos or broad lifestyle content.
- Check first: Confirm audience seniority, geography and engagement, plus availability and terms, before planning.

### Takeaways

- Reps must carry deal information between calls, CRM updates and forecasts.
- Molly prepares for a call, surfaces a MEDD(P)ICC gap and drafts a CRM update.
- Teams experimenting with AI-native workflows differ from those relying on manual updates and weekly methodology reviews.

## Main ideas

- **Disconnected sales tools make reps the integration layer**: Keating says each sales tool may serve a purpose, but manually moving context between them creates gaps in follow-up, CRM records and forecasts. The problem is the handoff between tools, not simply the number of tabs.
- **AI should do work for sales teams, not just add another interface**: Keating presents AI agents as teammates with specific responsibilities, not as a feature list or a new destination reps must visit. In the Overpath launch post, Molly is described as helping with deal execution, CRM hygiene and coaching, while leaders get signals about deal attention and sales behaviours.
- **AI readiness depends on context and follow-through, not a licence alone**: Keating contrasts teams building AI-native operations with teams still centred on manual CRM updates and weekly methodology discussions. The distinction is whether agents have enough organisational context to act and provide useful insight—not whether staff have access to an AI tool.
- **Sales methodology matters most when it reaches the live deal**: Keating’s examples put coaching into the work itself, rather than treating training or methodology as separate from selling. The idea connects the execution-gap argument to the claim that CRM records alone do not make salespeople more effective.

## Work to read

- [The execution gap between sales tools](https://www.linkedin.com/posts/keatingross_open-a-reps-screen-during-a-live-deal-and-activity-7508072631070326784-_2eu)
- [Launching Overpath and Molly, an AI sales teammate](https://www.linkedin.com/posts/keatingross_revenueexecution-aisalesagents-futureofwork-activity-7510984419692679169-LU65)
- [The AI maturity gap across go-to-market teams](https://www.linkedin.com/posts/keatingross_im-amazed-at-the-spectrum-of-ai-maturity-activity-7513212784764125184-nW2L)

## Brand relationships

- **Overpath** (disclosed_partnership)
- **Elkstone** (mention)
- **Sure Valley Ventures** (mention)

## Partnerships

Ross Keating's posts focus on the launch of Overpath, the team's AI sales teammate Molly, and uneven AI adoption across go-to-market teams. They do not describe brand partnership or sponsorship formats, and contain no sponsor disclosures, pricing or rate information, media kit, format specifications, or partnership contact route. Ask Keating for available sponsorship formats and an official inquiry route.

## Alternatives

- Rishabh Jain: Choose Rishabh Jain when a campaign is about the engineering behind an AI sales coach, not only the selling problem it solves. Jain's posts argue an AI product is about 20% model, and that what users actually notice is agent routing (a planner and coordinator deciding which skill answers a question), guardrails that check before an agent touches pipeline data, and an audit trail a rep can read back after the fact. That is directly useful for a sales-enablement company deciding what its coach must build: which component answers a rep's question, what stops an agent reaching records it should not, and how a rep or manager can reconstruct what the coach did. The same posts also show awareness of the rep-facing problem — one counts the tabs on a rep's screen and describes a brief before the call, a qualification gap surfaced after it, and a CRM update ready to approve in one click. One post credits Ross and Dermot among the people who argue over those product decisions, so Jain is close to the same subject matter rather than an outside observer.
- Matt Doyon: Choose Matt Doyon when a campaign aimed at sales-enablement buyers needs call-data evidence rather than product argument. Doyon's posts describe scoring roughly 500,000 Aircall calls and 500,000 video calls, and separately more than 11,000 MEDDICC calls across geographies, languages and company sizes. The findings are specific enough to carry a talk: MEDDICC rarely happens in one conversation and usually covers only two or three categories at first; reps often tick a framework box after hearing something as thin as a desire to improve CAC, while stronger sellers push for baselines, financial impact and ownership of the metric; and Decision Process scores lowest, with procurement requirements, legal timelines and approval paths surfacing late and stalling deals. For a sales-enablement buyer, that is a ready-made case for measurement and for the specific coaching an AI sales coach should deliver, and it points at the paper-process gap without needing product claims.
- Chris Tveter: Choose Chris Tveter when the payoff is adoption inside the CRM and the practical friction reps and admins hit on day one. Tveter's posts walk through specific HubSpot releases — a Claude sales plugin with eight pre-built skills and a Deal Progression public beta — and explain what each one is for: a ten-minute call prep, a morning brief of open deals and stalled contacts, logging a call in plain language, drafting follow-up from deal history, a pre-review pipeline scan, contact lookup, imports. Tveter flags what teams get wrong: every deal record gains a Catch-Up tab and a default layout rename that reps should be told about, recording must be switched on for any of it to work, methodology configuration (MEDDIC, BANT, SPICED) and Deal Plans each need an admin to activate, and writes to the account are shown for confirmation first. There are also concrete usage opinions, such as starting reps on call logging and follow-up. For a sales-enablement company, this is the change-management and enablement layer that sits between buying an AI coach and reps actually using it.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/