# Gaurav Nisar

Gaurav Nisar writes about using AI to improve sales enablement, including how sales teams find approved information and how reps learn and practise. His posts also discuss Tangelo.ai’s sales enablement goals.

- Profile: https://b2binfluencer.marketing/creators/gaurav-nisar/
- LinkedIn: https://www.linkedin.com/in/gauravnisar
- LinkedIn followers: 7,723
- Topics: artificial-intelligence, sales, ai-in-sales, sales-enablement
- Based on 10 dated posts, latest 2026-10-06

## Summary

Gaurav Nisar is useful for practical arguments about AI in sales enablement, especially onboarding, roleplay, and approved knowledge.

- Best for: A campaign for AI sales roleplay, onboarding, or rep readiness software.
- Not for: Campaigns needing quota, comp, territory planning, or measured reach claims.
- Check first: Whether paid collaborations, rates, deliverables, inquiry route, and audience data are available.

### Takeaways

- Experienced hires need less onboarding, not more, if they prove readiness.
- Prompting is a people skill: choose which expert persona answers.
- Approved knowledge must be easiest path, or reps use unsanctioned AI.

## Main ideas

- **Experienced hires need less onboarding, not more — as long as they prove readiness**: Nisar argues that a single onboarding track wastes veteran reps' time and can push them out the door. The fix is a demonstrated-skills bar rather than a fixed number of weeks: readiness stays the same; the wasted weeks go. They write that they had AI's application backwards, assuming personalisation meant more content, more modules and more practice. The reframe came from a conversation with Nick Saunders, quoted in the post as saying that for the best reps personalised learning could mean less learning rather than more.
- **Prompting is a people skill, because you have to pick which expert answers**: Their recurring argument is that AI is not a search engine but a shapeshifter: the same model can act as a chief revenue officer, a top account executive, an enablement lead or a day-one SDR, and nothing in the tool picks for you. People arrive at work with a role built in, and you adjust automatically; a language model does not, so specifying who is in the room is the real skill. The bottleneck is not access to intelligence but directing which version of it you need.
- **Approved knowledge must be the path of least resistance, or reps will use unsanctioned tools**: They argue content hubs are not failing because the content is bad, but because AI changed what people expect from search and how fast they want answers. Enablement's job shifts from maintaining a tidy library to making approved, current company knowledge retrievable wherever reps already work. Without that, reps reach for unapproved tools, carrying outdated messaging, unapproved claims and shadow AI into live deal cycles.
- **Five things they say Tangelo.ai is trying to fix about enablement software**: In the most product-facing post, they write in the first person about a goal at Tangelo.ai: fixing what people dislike most about sales enablement software. The stated priorities are analytics tied to business outcomes, finding the right answer instantly, AI roleplays reps actually want to practise, AI that does the work rather than acting as another chatbot, and learning in the flow of work. Ask about their role and commercial terms before treating the post as a product offer.

## Work to read

- [Why a top sales hire quit on day 18 (and what AI roleplay changes)](https://www.linkedin.com/posts/gauravnisar_on-day-18-our-highest-potential-new-sales-activity-7513221694241632257-yySd)
- [AI is not a search engine, it is a shapeshifter: prompting as a people skill](https://www.linkedin.com/posts/gauravnisar_most-of-us-started-out-using-ai-in-sales-activity-7511774221149106176-_lwX)
- [What Tangelo.ai says it is trying to fix about enablement software](https://www.linkedin.com/posts/gauravnisar_tangelo-ai-enablement-platform-agents-activity-7510333829409103872-MNER)
- [Reps give up on the content hub and ask Claude: where enablement content is going](https://www.linkedin.com/posts/gauravnisar_a-sales-enablement-leader-told-us-something-activity-7511047460627283969-BqS0)

## Brand relationships

- **Tangelo.ai** (disclosed_partnership)

## Partnerships

Gaurav Nisar writes about sales enablement AI and refers to Tangelo.ai as a company they work with: “One of our goals at Tangelo.ai is to fix the things people hate most about sales enablement software.” The posts don’t describe sponsored placements, paid collaborations, rates, deliverables or an official inquiry route. Ask directly about these before planning a paid collaboration.

## Alternatives

- Marcus Chan: Choose Marcus Chan when the decision-maker is the sales manager rather than the enablement stack owner, or when the product is bought by the person running the weekly team call. The two posts use the same named-character structure as Nisar’s, but focus on manager behavior and deal execution. One tells the story of Sarah, a rep who missed her number by 15 percent, was asked in front of eight teammates to explain what went wrong, and quit two days later after her manager learned she had been flying between cities while her father was in the hospital. The concrete changes that follow: praise publicly, coach privately, ask questions instead of making statements, and treat the job as making the team successful. The other argues that reps lose complex deals because they sell to champions instead of teaching champions how to sell. It offers three questions to ask before negotiated pricing goes to a CFO: whether approval means the deal moves forward, whether the CFO will push back, and how to get the CFO fully on board before asking for a discount. For campaigns needing a manager-behavior hook—roleplaying internal deal conversations, coaching cadence, or why a readiness program gets ignored after week one—these posts offer stronger stories than a roleplay-focused creator does.
- Jackie Smith Norton: Choose Jackie Smith Norton when the buyer task shifts from pre-ramp readiness to adoption, retention, and customer community—the post-sale half of the same enablement spend. Written from inside a customer success role, the customer-awards post names outcomes a vendor might want a collaboration to celebrate: admins who created thousands of in-app assets, an enablement team that raised adoption by 1,350 percent, teams that influenced millions in revenue, AI search counts above 1,700, more than 3,000 pieces of content created, 45 percent adoption lifts, and 85 deal rooms launched. It closes by arguing that the real measure is partnership rather than net revenue retention. The hiring post lists traits the team looks for in a customer success manager: adapts quickly, builds from the ground up, is coachable in a real way rather than a checkbox way, learns fast, is comfortable operating in the grey, and cares about outcomes. That gives a campaign about who succeeds in an AI-first adoption role usable raw material. For customer-recognition or case-study formats, or vendors selling post-sale adoption rather than pre-ramp preparation, this is the closer match.
- Christina Brady: Choose Christina Brady when the buyer's product is revenue intelligence or proactive risk detection rather than rep readiness. One post argues that today's stack identifies symptoms—conversation intelligence can flag a deal that lacks multithreading, and dashboards can flag slowing stage velocity—but stops at visibility. It cannot explain the behaviors behind the outcome or predict where revenue will leak before it hits the bottom line. The post positions a behavioral revenue intelligence product as predicting leak across active opportunities before performance declines and labels the approach predictive enablement. The second post argues that data cleanup, lead routing, attribution, and CRM adoption projects should not block enablement work: two quarters later, you can have a perfect machine delivering leads to reps who never learned to convert them, with churn rising and the sales cycle 30 percent longer. Vendors pitching revenue protection alongside business improvement—or selling to a revenue operations leader rather than an enablement manager—get an argument that already matches the product category.

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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/