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Mike said nearly every CRO gives the same six-month answer for how long it takes to onboard a rep, regardless of company. He argued that figure does not hold once territories are warmed in advance. In his own approach, ramp moved to 90 days once warming came first.

“It's like the common lie. They all say, how long does it take to onboard a rep? Six months it's the same answer for everybody no matter what”

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Mike said the theoretical six-month ramp was really closer to a year and a half in his experience. He moved ramp to 90 days by warming accounts through marketing outreach so they understood the problem before a seasoned rep entered. He said the accounts had not been physically touched or talked to, but they understood the problem and could resonate with the issue.

“That would move my ramp time from the theoretical six months was probably more like a year and a half to 90 days.”

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Garrett said reps can practise as many role plays as they want with an AI tool built on Brex's sales methodology and scoring system. They no longer need to wait for a manager to score a recording or run a mock scenario. He said this has helped Brex keep or raise efficiency while hiring at greater scale.

“people can do what used to take them weeks or months to do because they're waiting for other people in hours or days”

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Ghazi said the first-half plan assumed respectable ramp times, but reps are accelerating faster than expected. He said about 30 days is the average for a first deal, and that it happens predominantly in commercial but also in enterprise.

“I would say about 30 days is probably the average for the first deal.”

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Alex Bilmes said a new rep with complete information on every account can ask about their book of business and what to do about it. He said Endgame customers see ramp acceleration from six months to two months and that he had numbers he could share later.

“We see ramp acceleration going from six months to two months”

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Michelle said she did not cut headcount by 20 percent on the basis of AI, and that she would rather overreach on heads than fail. She said her plan is to use AI to take the five-month ramp down to three months, which describes an intention she is working towards rather than a result.

“What I'm going to use AI for is to take my five month ramp down to three months.”

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Coaching is one of the most time-consuming parts of a sales manager's job. He argues AI can review 70 calls rather than two, and can learn from past coaching sessions which kind of coaching each rep responds to best.

“But today's AI is a better coach than humans. They can look across 70 calls, not just two.”

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Selling time, the share of the week a rep spends in front of buyers or customers, goes from 25% to 75% once admin, CRM work, prep and pipeline reviews are removed. The rep-to-manager ratio goes from about 7:1 to 14:1. Reps who have averaged $250K a quarter would average $500K a quarter.

“Number one, selling time goes from 25% to 75%.”

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Roberge says managers hire, coach and hold people accountable to process, and that AI can do most of this, especially coaching, better than most managers. He says this creates an opportunity to at least double the ratio, which he says could accelerate enablement and productivity. His example for an AI-native team is 15 reps per manager.

“the traditional rep -to -manager ratio in the industry has been about 7 to 1”

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He said spans of 15 to 1 are not unheard of and that higher is possible now. He said companies are slow-rolling decisions to add frontline managers that the old 8-to-1 norm would have triggered. He tied the change to AI tools making the work easier.

“Right now my VP of sales has 35 direct reports. We're obviously going to change that.”

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Liz says she thinks people managers will remain but their number will drop dramatically, and the SDRs each manager oversees will rise. She does not think spans will reach 100, but she expects them to more than double. She also expects total SDR headcount to decline dramatically.

“Probably more like 15 to 20. I don't think it's going to go to like 100 but I bet it more than doubles.”

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Freya says when marketing and sales feel far apart, a marketer can start with one SDR or BD. She suggests asking the sales manager for a pilot of three to six months, matched to the length of the sales cycle. Marketing should share content with context on the stage and pain points it reflects, ask to shadow calls or get recordings and transcripts, and show the rep how the data helps them. Once the rep books more meetings, she says AEs will want the same support.

“I wanna run a pilot with this individual for three months, six months.”

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Kyle describes an internal AI-driven outbound tool tested first with four BDRs, with the GTM AI lead and a BizOps person sitting alongside them and iterating hourly. Within two days, output had risen sharply, and other BDRs then saw the improvements in decision-maker connects and booked opportunities. The tool was rolled out to the outbound BDR team and is now going to the other BDR and SDR teams.

“within two days, they had like cranked the output massively.”

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Usha describes running an experiment by setting a hypothesis, choosing the apparatus, running a pilot with a SWAT team of top sellers or account managers, and reviewing results. The pilot can be done manually in spreadsheets, and only after it works does the team ask ops or DevOps to build the structures and workflows for scale.

“You don't want to take that template now and give it to your ops team and say, you know what, go and build it into my system.”

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Mark said that when he was a senior advisor at BCG, he helped companies with ten-billion-dollar on-prem businesses move into SaaS. He said the core should keep running while the company finds a sandbox, such as an open territory or a new product, and stands up an inside sales team with MQLs. He said the core then serves as a control group to measure the experiment against.

“I think that's going to be the key is to have these competitive teams to experiment and try to outperform the core.”

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Kyle said the team ran a pilot last week to better prepare reps for calls and reduce the time between them. The task was fully handled by an agent, and he said it was then scaled across every customer in the database. He said the work took two weeks and could roll out to every BDR once enablement was done.

“this pilot group made 85 % more calls and produced 85 % more opportunities than their baseline”

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Mark says the advantage of choosing two people is that all the learning moments sit with two people rather than being spread across the sales organization. He describes this as a way to replicate a cross-functional seed-funded business inside the company and give it space to learn.

“we're putting all the learning moments in two brains as opposed to 300, where it would be diluted.”

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He illustrated this with golf, saying he focuses less on a golfer's swing and more on whether they can hit a draw when they need one. He said a system should recognise when a behaviour is not producing the target output and evaluate it quickly. He added that roughly 80% of behaviour can stay the same while leaving room for the 20% that differs.

“I focus less on what your swing looks like, and I'm asking myself, are you able to hit a draw when you need to hit a draw?”

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He recalled reps he hired in 2007 telling him that when phone time was used for comp, reps passed around 1-800 numbers to inflate their phone time even when no customer was on the line. He said his instinct is that it is dangerous to put comp on the metric.

“I'd run sales contests on it potentially, but I think that would be my instinct is like it's dangerous to put comp on it.”

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Slevin recalled a quarter at Axial when his team could earn about a $5,000 bonus for getting customers to pursue a set number of deals. Sam Jacobs explained the goal was to show deal senders the platform was alive and attract better deals, but agreed it became an end in itself. Slevin used it to illustrate how comp drives behaviour.

“But it became an end unto itself”

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He says sales is often scripted and activity-driven, with reps incentivised to do more meetings regardless of outcome. He says he would rather a rep do one meeting and close a good customer than do twenty meetings and close three, and that Linear's remote culture judges output rather than input, since it cannot track inputs well.

“I value the actual output versus the input more.”

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On her first day leading a team, Bove was told to fire a rep. She asked for data first, and the data looked good, so she called the rep's SE and then had lunch with the rep. She concluded the rep needed help with one thing rather than firing, and says he later went to President's Club year after year.

“First I need data, then context.”

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Garrett said he taught the question to this seller at a previous company, and the seller later told him it was the only change they had made. He described the seller as having been worried about being fired before the change. He presented this as a single example of the question's impact.

“Three months later, they went from being one of the bottom quartile performers in the team to the top performer in the segment.”

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McMahon said that when a rep had potential but stayed at the same level for a long time, he booked an hour in their calendar so they could not leave, then asked many questions about where they thought they were and why they were not progressing. He said reps squirmed and expected to be fired, but once they realized he had their best interests at heart and believed they could reach the next level, the conversation changed. He said some people called it the McMahon hot seat.

“some people used to call it the McMahon hot seat”

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Jeremy described a rep at AppDynamics who had been there 18 months without selling anything, and said the team kept analysing the problem. He described getting involved in one deal because she needed a win, and said it fell through because the customer did not actually have the money. He said she became the top rep in the world the year after, was promoted to a director role and later became head of global accounts at Rubrik.

“she'd been at AppDynamics for 18 months and hadn't sold a thing”

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Donald Kelly said the rep was right around the 70% threshold that put him in danger, and that the turnaround came from better conversations and fundamentals rather than a secret system. Donald said the rep moved from about 70% to 100% and then 120% of quota.

“then he went over to 120% of quota”

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Instead of hiring 18 reps in January, Mark suggests treating something like two reps a month as a hypothesis, running it for six months, and checking the product-market-fit and go-to-market-fit leading indicators. If they stay green, go to four a month for six months, then eight, then 16. If anything breaks, stop and fix it, hopefully within a day or a week rather than a month or a quarter.

“So you don't think about, Scale as a one -time hiring event after a fundraise or at the beginning of a fiscal year You think about it as a pace”

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His example: a company raises $15M with a $20M target and two reps producing $1M each, so it plans to hire 18 reps next month. He says this ignores demand gen capacity, rep-to-manager ratios and recruiting capacity. If you want to keep quality at a 10:1 screen-to-hire ratio, you'd need 180 qualified candidates in a month, which he says won't happen.

“We have to hire 18 reps. Let's go hire 18 reps next month. That's how everyone does it. total failure, unnecessary failure.”

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He gives the example of planning to hire 10 sales people in a quarter and cutting that to four. He argues that hiring into a broken go-to-market motion accelerates the path to bankruptcy, and that slowing down buys time until the next fundraise.

“if you miss it by 20% in Q2, do not increase hiring to catch up.”

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Roberge describes a Microsoft leader, who had worked as an operating partner at Stage 2, who used this 5-50-500 approach to launch a new product. He says the leader used Roberge's retention-based definition of product-market fit and a leading indicator of retention, and expanded headcount only as each gate was passed. Roberge says the GM accepted the approach because it set out a clear narrative for the path to scale.

“I'm gonna have five reps on this team until we have product market fit”

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He describes a hypothetical company where 10 reps averaged $1 million each and the plan is $25 million next year, so it hires 15 more reps at once, often after starting planning late despite a six-month ramp. He expects one strong rep, seven middling and the rest weak, after which managers push reps hard on quota, people say they cannot work in that culture, and about six months later comes a bad quarter that leads VCs to pull back.

“when you hire 15 more right now, you're not going to get all A's. You're going to get one A, you know, seven B's and the rest are going to be C's.”

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Roberge describes a common plan to go from five reps to 15, which means adding eight salespeople, with all of them hired in January. He argues that hiring should be a pacing that runs through the year and continues, not a single batch.

“we need to triple this year from five to 15, which means we need to add eight salespeople. Let's do that in January.”

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Wayland says the AE side of planning hasn't changed much because you still need distribution capacity. However, hiring pace now flexes depending on whether the business is running hot or cold, rather than being a standing green light. Supporting roles such as SEs and managers for resellers, ISV partners and SI partners are where budgets are tight. In annual planning, AEs get funded first, and every supporting role then becomes a negotiation where a request for 10 heads yields 7, and each must have a business case and ROI.

“basically when you go through annual planning you fund the AEs and then and then all the other roles you know I want 10 I get 7 and you get that sort of a conversation across every one of the supporting roles”

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At Salesforce in the early days, capacity planning was simple math: if each head is worth $1M a year and you want $100M, hire 100 heads as early as possible in Q1, then add more if things go well. After pausing hiring around the mortgage crisis left them short of capacity, Salesforce resolved never to pause hiring again. Wayland says that approach is over because the buying motion has changed, citing an Okta report that the average enterprise has 187 SaaS applications. He says reps now need strong onboarding, enablement and lead generation, and the whole go-to-market system needs much more scrutiny.

“And now the Okta reports as the average enterprise has 187 SaaS applications. So it's just that the buying motion is different. And so this idea that you can just like never stop hiring, you have to have really good onboarding programs, really good sales enablement capabilities”

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Mike said he presented to the executive team a plan to hire 30 sales reps in three classes of 10, committing to a certain dollar output and saying he would be wrong if it did not work. The experiment was successful and became the data set for bigger bets to hire 100, then 300, 500, a thousand and eventually thousands more. Mike says the team needed to prove human sellers would not be a waste of time, money and energy.

“and that I would commit to a certain dollar output, and if it didn't work, I'm wrong.”

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Mark Roberge said companies going upstream often have little experience doing so and hire five enterprise salespeople first. He argued leaders should instead return to the start of the business and first find product-market fit and messaging, and only then hire the five reps.

“the first thing they do is hire five enterprise salespeople”

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At Axial, a private equity buyer told a colleague that the better the salesperson, the worse the product must be. Sam's team saw the reverse case in a weak LinkedIn Sales Navigator rep, which they took as a sign of how strong the product was. He allows that great sellers can come out of true enterprise organisations with a CRO who invests in training.

“I think there tends to be an inverse correlation between the quality of the brand on your business card and the quality of the salesperson.”

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Liam, Kleiner Perkins' sales operating partner, had spent a lot of time inside Parallel and talked to all its reps before telling Mirzadegan he was at least 50% interested in joining. Mirzadegan says salespeople have a good nose for whether a product will sell, and Liam later joined Parallel. Mirzadegan tells his own team that the measure of doing a good job is a founder trying to hire you.

“they've sold like tens of millions of dollars of revenue with like four people and like it's in spite of themselves.”

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Mark pointed to the Google era, when the hiring profile was Ivy League with no sales experience, and said it was replicated at Slack and, to some degree, at OpenAI today. He said OpenAI is struggling a little in the enterprise because it never really fixed this. He said the product-led success covered the inefficiency until it ran out.

“you could get away with an inefficient sales org and people who didn't really know the basics of selling that looked really good”

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Roberge says that when product, marketing and demand are strong enough, below-average sellers hit quota by cherry-picking, for example closing four of 50 leads. As territories shrink, such as from 100 accounts in San Francisco to two, that stops working. He cites studies showing the best sellers speak less than half the time in first meetings, probing for pain, while below-average sellers feature dump. He says a shift to Rule of 40 means upgrading sellers and moving out those who haven't learned consultative skills. He frames this as a dramatic shift in hiring profile, even though Wayland said his own profile did not change.

“There is a dramatic. shift in the hiring profile for sellers in the grow it all cost versus the rule of 40”

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Ann says she restructured the sales team early and quickly because she had numbers to hit. Most people who were given the chance to show enterprise skills chose to leave the enterprise motion, saying enterprise selling was not in their DNA.

“to be honest with you, 90 % of the people tagged themselves out and said, I don't have enterprise selling in my DNA.”

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He says enterprise carries enough risk that the company should not be learning the motion while its first person learns it. He says he often has to hire from outside for the first enterprise seller.

“I need an experienced enterprise salesperson to be my first person. I often have to go outside.”

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Chris Degnan said Frank Slutman, who became his new boss, told him that large enterprises cannot be sold the way small and mid-sized businesses are. Within three to four months, in the middle of a fiscal year, Snowflake reorganized the sales team to pursue large enterprises more deliberately. Chris said they got it wrong the first time, and it matured into what they call vertical sales, while the high-velocity motion stayed.

“you can't sell to the large enterprise the same way you're selling to the, you know, the small medium business.”

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Adam says he does not think AI replacing salespeople is happening anytime soon, or ever in certain types of sales. He says AI can help with execution tasks, so reps can focus on relationship building and psychology rather than more tedious tasks. He is describing airspeed's aim, which he presents as a view rather than a finding.

“We're not Saying that AI will replace salespeople or anything like that. I don't think that's you know happening anytime soon or ever really in certain type of type of Sales”

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Kaplan argued that AI tools can tell a seller why they lack a champion, but knowing how to build one still depends on human skill. He said sellers should keep learning the human behaviour of sales and practise their openings. McMahon added that sellers should not hide behind AI tools or skip face-to-face meetings.

“It gets me fired up because I think it's going to make the lazy sellers worse and the great sellers better.”

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Alex Bilmes said he tells enablement audiences that human judgment is why they still have a job and that they should invest in it. He said thinking and articulating thoughts, and understanding the human on the other end of the conversation, matter more as AI does more of the workflow.

“don't outsource human judgment. Don't outsource your brain.”

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Alex says email has been taken over by AI slop, and predicts that buyers will crave human fallibility, custom-made emails and face-to-face meetings. He argues sellers should keep their interpersonal and communication skills while also learning to work with agents.

“The email is dead. It's just been taken over by AI Slop.”

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She said the remaining AEs will be highly skilled strategic sellers. The skills she named were navigating the org, understanding the product's nuances, and knowing what people are really asking at the final mile. She said some of these may be automated later, but that executives on big deals will still want to speak with a person.

“It's the strategic seller.”

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Grosser said quotas have gone up every six months of her roughly year and a half at Vercel, and its headcount-to-revenue ratio keeps rising meaningfully. She credited part of this to product maturity and market readiness, not only AI efficiency gains. To illustrate, she said the traditional approach is about $1M per head, so $10M more means 10 more reps, whereas now you can, for example, take the $1M per head to $1.5M and not need 10. She said reps accept this because exponential growth makes most people 'come along for the ride', though not everyone loves her at the start of each half.

“I want 10 million, but I can take the million bucks to a million five. And so now I, you know, don't need 10.”

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Host Mark River suggested that a 12-year veteran who sells into healthcare could be enabled by agents to do the prospecting for about 1/100th of the effort, and Dan Lee agreed. Dan said the general bar rises, companies can grow without hiring armies of reps or lower-quality ones, and agents can help with the research, emails and calls.

“that is enabled by this tech such that they're actually doing the prospecting, but it's like 1/100th of the effort.”

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Asked whether $2 million per rep is a lot, he said no and that reps can do a lot more. He said enterprise reps were already well above their $1.5 million annual number in H1.

“Yeah, you can do you can do a lot more”

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He said this is partly AI but not all of it. He said quotas have been raised over the past year and will keep rising, which is also driving ARR per rep higher.

“We were a hundred and forty thousand dollars of new business per rep the first new business on the sales team.”

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The speaker says companies believe they need fewer salespeople because those reps can cover more, so territories stay larger for longer while quotas rise. Reps in the right company earn more as a result, and the pressure to fall back toward OTE after a strong year is lower than before. The speaker contrasts this with the past habit of cutting a rep's territory to a fraction of its size after a good year.

“territories are larger for longer. They are reducing but at a rate.”

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The speaker argues companies still need salespeople but fewer of them, so each rep covers more. The example given is a company doing 150 million in ARR with about 35 salespeople, whose quotas are larger than before and who are achieving at a very high rate.

“a company that's doing 150 million in ARR with about 35 salespeople”

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Asad described a friend who joined this company, which has 150 million ARR and 30 salespeople. He said it would once have had 60 to 90 salespeople at this ARR, and that headcount is now lower per dollar, although the company still has many open roles.

“150 million in ARR, 30 salespeople. In the past, that company would have had 60 or 70 or 80 or 90 salespeople.”

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He cited one rep who will do $400,000 in new business this quarter. AJ said AI is part of the gain, and described sales and marketing agents plus an orchestration platform called Dust, with the team now focused on QA of its automated workflows.

“Today, it's 175 to 200 K. per quarter”

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AJ Bruno started QuotaPath after reps at his previous company repeatedly complained each quarter that they weren't paid correctly, which he traced to a spreadsheet problem rather than cash flow. His conclusion is that if company objectives aren't matched to incentives and reps lack visibility into them, comp becomes a mess.

“if you don't match company objectives to incentives, reps and reps don't have visibility to it. It's just like, it's a mess. It's a total mess. And so why are you even paying a variable commission comp if you don't actually have a behavior that you want to incentivize?”

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Chuck says he frustrates clients by insisting that compensation be tied to the activities the company wants employees to do. If those activities do not produce the KPIs, he says it is the leader's fault for designing them, and he contrasts this with telling reps they must sell a set dollar amount each month.

“the compensation needs to be based on the activities that you want those employees to do.”

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Mark said Tenable modified its comp plans to drive platform behaviour and used sales kickoff sessions focused on Tenable One. He said the company disincentivized selling an individual product, which may be the easy way to get a quick land but does not give the expansion a platform does. He described this as the right long-term choice for the company and the customer.

“You disincentivize other type things that aren't the right thing for the company long term like selling an individual product.”

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Mark says the first principle of a comp plan is aligning company strategy with the behavior you push on the front line, but many companies just copy someone else. He recently took a startup through this: list the CEO's top five things for the year and ask which can be reinforced through comp. Choices like quarterly or monthly payout on closed-won contracts are, in his view, design dimensions often driven by system limitations.

“You have to start with, what is your strategy as CEO? Top five things this year. Can any of those be reinforced with a comp plan? That's where you start.”

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He traces sales specialization to Aaron Ross and Predictable Revenue at Salesforce, and says many companies over-specialized last decade because it was in vogue rather than right for their context. He argues that handoffs are inefficient for both customer and organization, and that AI lets one person handle all the roles. Consolidating the roles does not mean getting rid of the people.

“So I've been talking and inspiring a lot of companies to get rid of the concept of an sdr, an AM and a cs. It doesn't mean you're getting rid of those people. It just means we're going to a single role.”

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He notes that around 1995 there was one role, the salesperson, and that over 20 years it split into SDR, AE, AM, CSM, support and RevOps. Specialization matches talent to role but creates local-maximum optimization. He says AI will 'probably' bring back the generalist athlete, and that in a post-AI world the full-cycle salesperson will be the optimal design.

“Specialization is great. It allows you to align the talent with a role and use the hardest to find skills in that most important part of the funnel. But it comes with a cost, a cost of local maximum optimization. In a post AI world, the full cycle salesperson will be the optimal design.”

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Alex Bilmes said the email channel has made SDR mean different things to different organizations, and that RevOps and go-to-market engineering are building more efficient pipeline machines. He said a system could produce pre-call briefs, stakeholder maps and decks for an AE who owns their own pipeline, so fewer SDRs may be needed.

“I don't think you need as many individual SDRs building that stuff and sending out emails because you can train an agent to go do a lot of that stuff really well.”

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Alex Bilmes said the biggest impact is at headcount and team structure level, with adjacent supporting functions collapsing as well. He said many organizations are being redesigned with fewer siloed functions and a more full-cycle orientation.

“A lot of orgs are getting redesigned to have fewer specialists.”

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Mark said the SaaS era specialized roles, starting when SDRs were carved out from AEs and later when CSMs were carved out, and he said that went too far. He said AI should allow the field to reverse specialization and reach a much higher level of efficiency. He called this and the selling time target his two convictions.

“collapse your go to market org from SDR plus AE plus AM plus CS to one role that owns the whole thing”

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He said that outside a hot company that steps on the gas and hires more outbound SDRs, he thinks the outbound SDR job can be absorbed into the AE role. He said AI accelerates this because it makes it easier to have discipline around who you engage and how you engage them.

“I think you can absorb the outbound SDR into the AE's job.”

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Dan Lee said Nooks is growing more than three times year over year, and that upside from new products and enterprise growth is hard to predict. For sales goals they have generally picked targets the team is likely to hit, while company goals are set higher so the team pushes to overachieve. He said he wants to avoid a company tripling year over year whose sales team misses its goals.

“we generally tend to like underestimate a little bit.”

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Dan Lee said the average quota attainment across the sales team was around over 130 percent across the last five quarters. When asked what percent hit quota on a quarterly basis, he said over 90 percent. He attributed the team's reputation to that run of results.

“I think our average quota attainment was around like over 130%.”

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He said this comes alongside quota increases over the past year. He noted that quota capacity, financial plans and incentives all shape the figure, so it is a complicated measure to read.

“we're probably like 70 to 80 % of our reps hitting quota on any given quarter, which I would say is probably close to best in class.”

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Kyle Norton says his company's OTEs are not crazy and quotas are fair for SMB, so most reps earn above OTE. He contrasts this with companies that set high OTE and then have only about half of reps hit it. He gives the 80% and 138% figures as his company's results.

“Ours are fair for SMB, but our OTE attainment is like 138%.”

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At Roadrunner, the head of sales wanted the head of implementation on every call, including pre-sales, to put the company's best foot forward. Mirzadegan argued she needs to go hire, and that he himself had stepped back from selling despite possibly being the best seller, to avoid being the bottleneck on every customer. He accepted there may have been a short-term tax. Zhang added that recruiting feels like a short-term opportunity cost but skipping it creates much higher long-term costs.

“Was there a tax that we had to pay by like not putting our best foot forward in air quotes? Maybe. But like eventually, like what am I going to do? Just like be the bottleneck to every customer. It doesn't work.”

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John Kaplan says early-stage companies, often led by technical founders, ask for more domain expertise in sales hires. He reads that as a sign that expertise has not yet been turned into skills sellers can use in front of a customer. He uses the zoologist and hunter analogy to say a company needs experts early on, but must transfer their knowledge to hunters, and that a company where experts must join every call does not scale.

“All that's telling me is that domain expertise has not been translated into”

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She says she told the sales team she can't be on 20 calls or every first call anymore, and will be on bigger deals. She adds that joining calls had been embarrassing, knowing little about the prospect's business and reading prep just 30 seconds before.

“I can't be on 20 calls. You're still going to be on calls. You're just going to be on bigger deals.”

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Justin said Terret made a bet that a smart, hard-working rep with no complex-sales background could succeed if plugged into the system that surfaces the top sellers' playbook. He said the rep applied that guidance quickly and his close rates ramped to the point where he performed like an experienced rep.

“in terms of the ramp time, his time to first revenue, it was about 60% of what we had seen historically”

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Yash said his own early career as a teacher and his first sales role both relied on asking questions that make a buyer think critically and become a partner in the process. He said discovery is similar to a teacher's approach. He added that a teacher's approach combined with systems thinking and automation is what he now draws on in running Clay's ecosystem.

“I actually think teachers, really great progressive ones would make some of the best salespeople you have, especially on the discovery qualification side of the equation.”

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Ghazi said the Marine was already the company's number one seller when he arrived, and has since moved into a technical role. He said a schoolteacher who had never sold is one of the top commercial sellers for the downmarket business and has one of the largest forecastable pipelines for the quarter.

“when I got here, our number one seller in the company, and the person was already here, was, came from the military, was in the US Marine Corps. Never sold a day in his life.”

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John says knowledge and skills can be picked up on the job, and gives PTC and Snowflake as examples where reps were hired without industry or mechanical engineering backgrounds. Mark adds that boards that make resume hires on industry experience often end up with bottom-quartile performers.

“they just hired they didn't care somebody knew what a data warehouse was”

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Grosser said Vercel runs internal mobility twice a year with a formal process. Many of its BDRs were technical founders whose companies failed and who found they loved customer discovery. They were willing to start as BDRs because that is the required entry point into sales at Vercel. Vercel also hires former founders into other go-to-market roles.

“our BDR function, we graduated as many to be account executives as to be solution architects”

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The 54 qualifiers spanned sales, partnerships, customer success and support. Lauren Hughes uses the result to show SDRs the career path available if they follow the playbook. Kyle Norton added that SDR is a momentum game in which visible promotions attract talent and effort.

“we have 54 qualifiers across sales partnerships, customer success and support and 24 of them came from the sales development organization”

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Lauren Hughes said this has been proven repeatedly at Justworks. The company invested in a better AE readiness program to move SDRs through faster. Within about four months of taking over SDR, six SDRs were promoted to AE, two moved to partnership acquisition, one became a manager and one joined revenue effectiveness.

“the best reps are from the SDR organization.”

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Rather than squeezing more out of SDRs through higher quotas, Garrett said, Brex gives SDRs who exceed a set performance percentage for a set period the chance to work an open AE book. If they close enough deals while still hitting SDR numbers, Brex promotes them whether or not headcount is available. He said that is not a hard argument to make to finance, because most CFOs would agree to more AEs who can generate revenue.

“But if they could close those deals, we just would promote them on the spot.”

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He said Brex went a different direction from AI SDRs, which many companies were investing in at the time. He argued that the best SDRs are valuable because they can later close deals, and that the company should optimise for that longer-term value. He said SDRs and the company share this incentive.

“the primary reason that you employ SDRs is actually not for the pipeline they generate”

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Adam Aarons said he started his own career as an SDR and has a passion for that group. He treats the SDR team as a farm team, teaching them the process so that when they are promoted they are better at the job.

“it's a farm team for me and so i'm taking those people trying to teach them the process”

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He says agentic AI should supervise and give feedback to everyone in real time, from lead gen through closer, account manager and supervisor, not just one stage. He criticizes the historical pattern of going back two weeks to correct a mistake today and then blaming the rep tomorrow.

“This is real time. We are not going back to two weeks ago and try to help someone to change its mistake they made two weeks ago today and then blaming them tomorrow.”

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Lauren Hughes found reps were taken off the floor for over an hour of country launch training when they might not sell that country for six to twelve months, and they did not retain it. She cited this as part of a serious enablement problem that pushed her toward personalised, just-in-time learning.

“we were pulling people out of the field to give them training for stuff that they didn't need to be trained on at that given point in time.”

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With 600 customer-facing staff across 20 unique roles, she said Justworks could not staff field enablement for every specialist role. A product launch now goes through an AI enablement planning system built in ChatGPT and Claude that uses ride-along-based role profiles to tailor what SDRs, AEs, onboarding, success and support each need.

“You can't have 20 field enablement people running around to these like specialist roles.”

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He described pulling his team out of the field for a week into a conference room, where reps tried to digest the material and then forgot it at the bar that night. He said reps and managers need help at the moment something matters, when they are focused on a specific deal or conversation.

“this idea of trying to enable a sales team is an antiquated model”

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Alex says he recruited from Snowflake for elite sellers who had worked on a novel architecture, and likes EMC sales culture. He says what he needs are the transferable intangibles, because the new market is novel territory for everyone, including the sellers.

“I went and pillaged Snowflake. I mean, what an incredible company.”

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He said a candidate may never have sold into engineering or used PLG, but prior sales at multiple companies to multiple personas shows they can understand and communicate new things. He said he does not need MIT, Stanford or Harvard graduates, but does need people who can understand technology quickly.

“somebody that has had the ability to sell at multiple different places different products to different personas”

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Brian said innovation is governed by how fast the field can digest a new product and bring it to market, not by how fast the company builds it. He said clock speed has become the most critical element in a fast-moving business and that he is focused on smart sellers. He tests for the ability to understand technology quickly and articulate it to the end user and buyer.

“the governor on innovation is how fast your field can digest it and bring it to the market”

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He says the expertise in how to talk to people, convince them to buy and explain why a product exists and is valuable applies to any strategic company that wants to grow. He expects the market to create a natural bridge, with robotics companies hiring revenue leaders who have built sales teams in B2B SaaS.

“Those are not specific to SaaS.”

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Mark Roberge says that when early-stage startups and their boards look for a sales leader, the first thing they ask for is experience with the company's tech and industry. He contrasts this with experienced leaders such as Lauren Nemeth, who would take a top sales performer and teach them the tech and industry.

“The first thing they say is experience with our tech and experience in our industry.”

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In a hypothetical comparing a top sales rep with no AI knowledge against someone who knows AI well but ranks around 500 out of a thousand reps, Lauren Nemeth said she would take the top performer. She said AI is very teachable, just like any technology, and that she came to Pinecone with no AI experience herself.

“I'll take the top sales rep every single day.”

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Dan Lee said that when Nooks moved past founder-led sales they hired two reps at the same time, on advice they had received. His reasoning was that a single bad hire takes three to six months to identify, then a couple of months to replace, which could set the company back almost a year.

“if they don't work out, uh, you know, it takes like, you know, three to six months to figure that out”

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Roberge says the timing depends on the founder's skills. A founder from sales can keep selling for longer, while a top technical founder should bring in a seller early so they do not spend half their week selling. He also says founders should try to reach product-market fit on their own before hiring a seller, and that a founder who has built a sales process should hire two reps and teach them.

“So, obviously, if I have a founder who comes from sales, it's going to be delayed quite a bit and I want the founder to stay close.”

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Once a rep could replicate what the founder is doing, Kerrest hires three at a time. Reps will sell their own way even with a methodology, so three show which approaches work, and a scoreboard harnesses their competitiveness. On quota: if you guessed $1M and one rep does $1.1M while another does $3.6M, he says quota is probably about $3M.

“If you had three and one does 1 .1, one does 3 .6, probably $3 million.”

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When she joined Stripe there were only account executives and account managers, with no technical sales roles or BDRs. As Stripe moved upmarket into migration conversations and regulated industries, it added specialisation about every six months. Her stated aim was 'we'll never reorg', just take the natural next step each time. At Vercel, selling to e-commerce differs enough from selling to tech companies that it had just created an e-com vertical. Her signal for the next step is when a generic sale stops working in a newly opened part of the market.

“If I'm doing my job right, we'll never reorg.”

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Grosser said reps' livelihoods depend on quota attainment, so you can't change everything on a random Tuesday. At Vercel she made major go-to-market changes four and a half months in, faster than she naturally would have, because waiting until six months would have landed mid-Q3. The executive team agreed beforehand to accept a possible near-term trough for the upside. About six months after the changes she was again not sleeping well, because not everything could be operationalised cleanly; roughly six weeks after that, the change looked right.

“it's easiest to change a sales team sort of at the halves.”

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Ian says you can't look at a reorg through rose-tinted glasses and must map the downsides, with finance modelling them. When Kyle suggested risks such as lower win rates or distraction from pipeline generation, Ian agreed. As an illustrative number, he says moving 30% of accounts means 30% of reps need new quotas, comp plans and territories, and 80% would be 'a phenomenal amount of work'. The back end has to be in place to support the change.

“Here's the upside but what could we break as well? Because you have to be realistic.”

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Asad says enterprise sellers who travel, meet people in person and attend dinners and conferences have a limited number of hours. He expects their quotas will not grow much, but says that in a more competitive market, where win rates are going down, they may need somewhat more pipeline to hit the same numbers, though not multiples of what they had before.

“I don't think their quotas grow up that much, but they might need a little bit more pipeline than before”

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Rick says quotas were already high at ShipHero and the company has a rationale for the OTE-to-quota multiple. The company has expanded the team and allocated more quota across it rather than raising individual quotas. Rick says he does not believe doubling someone's quota would give them any chance to succeed, because the selling variables AI has not changed still apply.

“We have not raised quotas on anybody on the team.”

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Ryan Smith said growth in a B2B software sales org comes from new reps or higher productivity, so a company growing 20 percent has to increase its sales reps by 20 percent. He used a score-per-game analogy and said that in his 20-plus years in tech it has been very hard to get people averaging 15 points a game to average 30.

“I think it's very hard in my 20-something years in tech to count on getting people who are doing 15 points a game to go to 30 points a game.”

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Dan Lee said many of the early sales teams using Nooks were junior reps in their first job out of school. They learned by getting feedback once a week from their manager on recent calls from recordings, rather than sitting on the sales floor. He said this made collaboration a strong fit because reps need a tight feedback loop to share what works.

“the way they're learning is by getting feedback once a week from their manager”

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Kaplan agrees that reps often know people are listening to their calls but do not listen to their own. He compares this to a player going into a game without watching the film and waiting for the coach to say what went right or wrong, and calls that insanity.

“they're not the ones listening to their own calls”

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Bob says tools available today let reps self-assess whether they are curious, prepared, calm and clear on differentiation. He gives the example of noticing when a buyer starts looking at a phone or computer screen. He compares this to reviewing game film in sports.

“We can now have technology that can self assess.”

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Mark said Jonathan puts the person on the hot seat and has them self-assess first. Mark added that he likes to have some people give positive feedback and others give areas for improvement, which he said Jonathan probably does as well. Mark said he does not think any seller would listen to a recording and think it was perfect, so there is always something to improve.

“So what he does is he has that person on the hot seat self-assess first. That's critical.”

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Mark said he calls this the film review and that he has used it on discovery calls, while Jonathan uses it on cold calls. He described the process as a team listening session where the rep on the hot seat assesses their own call first, followed by positive feedback and areas to improve from others.

“It's probably the biggest driver of performance optimization that I've used as a leader at scale.”

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Jonathan gathered his five reps each week in a meeting room and listened together to about 10 cold calls, each over three minutes, then asked what they heard, what was good and what to improve. He said reps were uncomfortable hearing their own voices, but judging themselves on the calls, sometimes weeks later, helped them grow.

“we sit in a meeting room and we pick up 10 different calls, 10 different cold calls that were more than three minute minimum calls.”

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Replit had no quotas or compensation plans until January 1 of this year, so H1 gave the first six months of data. For H2, Ghazi split the team into new-logo and expansion teams, since in H1 reps had been doing both. He said enterprise reps had a $1.5 million annual number in H1 and every one of them was well above it. He is running quarterly plans instead of half-year ones so reps can earn accelerators twice and leadership can adjust if conditions change, and he is raising H2 quotas.

“greater than 90 % of our team overachieved their number and just blew it through the socks”

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He said he does not think it is a positive sign, and that he asks why the company is not hiring more. Another participant agreed that this leaves money on the table.

“I actually don't even think it's a really positive sign nowadays when companies say i have a salesperson who does like. 10 times their OTE in revenue, I find that somewhat inefficient.”

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Ghazi said nobody was on quotas until January, when everyone had been on full OTEs, and that it was hard to set a line because the business was moving so fast. He chose half-year plans for that reason, and said that by May 1, with Q1 behind them, everyone was smashing quota. He plans to raise quotas in the second half to normalize them, while still building a winning culture.

“Nobody was on quotas up until January of this year.”

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Mark Roberge said that below 60% of reps hitting quota, the culture will go south and people will start quitting. Above 80%, he said quotas are too soft, or the hiring is weak and quotas should rise. He suggested asking whether quotas are too high and can be lowered, or whether performance needs to be driven harder.

“I like it to be between 60 and 80%.”

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The aim is to comp on LTV rather than just ACV, without turning reps into CSMs, so they 'sell the deal right'. Joubin Mirzadegan asked whether paying the same commission rate on expansion would achieve the same thing; Mark said it helps but reps aren't long-term planners. They are trying to make the quarter to keep their job and will accept smaller expansion later, whereas the LIR split pulls the consequence forward into this paycheck.

“You can comp them 50 % on the contract signature and 50 % on the LIR. I'm not trying to turn them into a customer success manager. I'm just trying to make them sell the deal right.”

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Dan describes LTV as factoring in retention, expansion and gross margin, and says finance teams can calculate it or his software can. He says he was told, though he calls it folklore, that Segment used LTV by segment in its comp plans. His dream is for LTV to be the north star of an AE comp plan, so sellers focus on accounts that stay and grow.

“So like that would be my dream is LTV becomes the North Star and a comp plan for an AE.”

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Roberge says this forces reps to focus on lifetime value without waiting a year for retention data, since many customers reach five features within a week or two of signing. Where there is a free trial, he says reps may get customers to hit the indicator before signing to accelerate their commission payment.

“We can pay the reps half of the commission when the customer signs the contract and half when the LIR is achieved.”

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Mark Roberge describes a plan he says he has used in many cases, where the account manager handles onboarding, renewal and expansion. He says most good customers reach the leading indicator within about 30 days, so the second payment lands in the same quarterly commission cycle.

“You get paid half of your commission when the customer signs the contract. You get the other half when they achieve the leading indicator of retention.”

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Mark Roberge says that if sales roles are specialized, the compensation plan should solve for the overall go-to-market goal of lifetime value rather than for each role's local metric. He is stating a design principle rather than describing a plan he ran.

“That compensation plan should not be correlated to ACV and ARR. It should be correlated to LTV.”

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Mark offers this as a comp plan structure. He says he does not know Miro's leading indicator, so the example is hypothetical. He frames the aim as short-term focus at the point of sale while aligning the plan with customer value.

“Hey, you get paid half your commission when you, they signed the contract and half the commission when the lead indicator of retention occurs.”

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Mark says paying a share of the monthly or annual customer payment would let sellers collect every month without doing anything. He argues sellers should feel the pain of a missed month or quarter and the upside of a strong one, so the plan should carry end-user value back to the point of sale. The leading indicator is the action a customer takes in the first month that predicts they will stay. He gives HubSpot's five or more features and Slack's 2,000 team messages a month as examples.

“we can't pay them like a percentage of the monthly payment from the customer or the annual payment from the customer, because then they'll just be like collecting money every month without doing anything.”

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Tunguz said he no longer measures companies by the AE-to-SDR ratio the way he used to, and that an AE-to-CSM ratio often does not exist at AI-native companies. He said the sales models are so different that the old ratios cannot be applied across companies. He pointed to account-level quotas in the tens to hundreds of millions for a single insurance customer as radically new.

“I don't really measure companies on like AE to SDR ratio the way that we used to or AE to csm that doesn't really exist.”

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He gives the example of how many solution engineers are needed per account executive, and says traditional metrics and processes are in some ways no longer directly applicable. He says organizations and functions must change and that leaders need an open mindset. He is describing how he sees the change, not a Glean-specific ratio.

“The ratios of like, you know, do you need, you know, one solution engineer for one account executive or whatever that those things are. Like none of that traditional those metrics or those processes in some ways are all directly applicable anymore.”

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Signals include attendance and how hires show up on Zoom onboarding. Keeping cameras on is a mandated requirement at Justworks. These signals sit alongside quiz, checkpoint and AI role-play results.

“But yeah, we can tell somebody is not going to make it just based on how they show up first couple of days.”

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Justworks measures onboarding with quizzes, checkpoints, AI role plays and attendance. If SDRs are ready to dial by week three, Lauren Hughes asks why they are held to week four. If 2 of 12 AEs fail, the team checks for patterns such as no industry background or a first sales job, then adjusts the program or works with the manager on extra coaching.

“Why are we holding them in training to week four? Let's just let them go at week three.”

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After company onboarding, reps go through a two-week bootcamp based on their role and graduate with a certification, which is when they get their territory and book. Ghazi said a recent bootcamp had people who did not pass, which serves as an early test to course-correct or make a different decision.

“they actually graduate with a certification. And that is the time you're actually allowed to hit the street.”

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Rick says the framework depends on the sales cycle. In enterprise, he says the constraint is travel and meetings, so a seller may handle only a limited number of demos. He then considers expected conversion rate, deal value and time period, and says he is open to higher productivity if the logic supports it.

“how many leads can a person reasonably handle in a month?”

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Kyle Norton says his team analysed the right number of leads per SDR, because too many leads mean they do not follow up all the way and the AQL to opportunity conversion rate falls. Too few leads means lost productivity. He says the same analysis applies to AEs.

“We've done a bunch of analysis to look at like what is ex what is the exact right number of leads to give to an SDR”

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Jeff Perry said rep productivity is easy to test by asking whether people are busy, whether they generate their own leads, and whether they have too many leads. He described an enterprise AE with half-hour demos stacked all day and no time for a bathroom break, which he said signals a need to consider adding AE capacity in that segment. He then suggested checking attainment levels and the balance of inbound and outbound within the segment.

“you know, it's easy to test, like, are people busy or not?”

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John McMahon says less experienced first-line managers prefer to show off a veteran's million-dollar deal, while a new rep struggles with discovery and cannot close a first deal. He says this loop drives attrition, and that replacements with new resumes then make the same mistakes. He says holding managers accountable for new reps' first deals is how to break it.

“They go to drag the bear in from the woods with the million dollar deal and bring it back to the campfire.”

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Jason said he focuses on the middle class of sellers, drawing on a Harvard Business Review idea that a strong middle makes a healthy sales economy. He said the top performers will do well anyway, but the middle group is the bread and butter that makes forecasting predictable. He said his aim is predictable growth, not just revenue.

“you're not going to get there just because the top 5 % of your teams did 150 % of your number.”

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John McMahon said managers tend to go on deals with their top performers, who may not need the help, because they want credit for the win. Meanwhile, other reps who are meeting technical buyers or potential champions get no support. Jason agreed that this produces a lumpy pipeline and forecast over time.

“they are chasing the deals with the top people”

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A host described a common pattern where a few reps carry most of the deals and most others miss quota. Jason said leaders should be honest about the situation, then inspect the other four or six people and ask what is causing the gap. Possible causes he listed included tenure, pairing with the best SEs, geography, use cases and stage-to-stage conversion.

“what is your process and your cadence for continuing to inspect what's going on in the other four or six people?”

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Jonathan said the common advice to ignore poor performers and spend time with top performers is the opposite of how Toast operates. He presented coaching as a right for every rep in a coaching culture. Mark Roberge added that managers in general tend to overcoach their bottom performers, so the allocation matters as much as the principle.

“We believe the exact opposite. Everyone deserves the right to be coach”

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Mark Roberge presented this as rigorous research consistent with Jonathan's view that bottom performers should not be ignored. He said sales managers tend to overcoach bottom performers. His reasoning was that two hours with an A player moves them to the next level, and two hours with a B player can activate untapped potential.

“It's if you have 100% coaching time, 20% of your top performers, 20% of your bottom performers, 60% of your middle performers.”

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Potter moved from solutions engineering into sales at WRQ, where he says his first attempt was a dismal failure. Colleagues told him to stop trying to be the smartest person in the room and to show customers he was part of a team that could deliver, which he calls the most critical point in his career.

“you got to stop trying to be the smartest person in the room and you got to make sure that the customer understands you're part of a team that can deliver.”

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Potter says technical knowledge earns credibility because buyers can tell the pitch comes from experience. But when a seller becomes the only source of answers, it hides the company's depth and resources and suggests the seller cannot work on a team. He says successful customers get a team that includes an account manager, a technical account manager, a solutions consultant, consulting, customer success and tech support.

“when you become the sole source of all of the answers to a customer, my experience has been that it creates a gap.”

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Stuart says reps must avoid playing hero ball, since no one can be in every discussion on an account at this scale. He describes investing in teaching the inside team, trusting them, and accepting their mistakes, until a quarter or two later everyone is running around ten meetings a week. He argues that 70% quality delivered at scale beats 0% from a rep who lacks time.

“70% is a lot better than 0% if I didn't have time to get there.”

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Bob Kocis said reps who complain to managers about lacking resources are often not the best performers, because the best are the ones taking the resources. He said the top reps act as the quarterback of the deal, and that colleagues who work with them have more fun, are taken care of, and enjoy the journey. He said these colleagues gravitate to top reps even though those reps have no authority over them.

“Because they are the quarterback. The resources know if they're with that person, the chances of winning the deal are way higher.”

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Tunguz said the supply side has not become 10x more productive; demand budgets have increased by a factor of 10, and that is what is driving quotas. He was agreeing with Asad Zaman, who said high AE output at AI companies may reflect demand flying at reps and high close rates from customers experimenting, so the signal has to be read with squinted eyes. Tunguz added that this is a market dynamic, so a sales discipline from one AI company does not transfer to another.

“It's not the supply side has changed and suddenly become 10x more productive. It's the demand side. Budgets have increased by a factor of 10 and that's what's driving quotas.”

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Asad notes the claim that reps at some AI companies are performing at two to four times prior quotas. He says a gold rush, where buyers are throwing money at a market, produces word-of-mouth demand that cannot be counted as a repeatable result. He does not think enterprise sellers who travel and meet in person can do three or four times their quotas once the market settles.

“I don't think that there's a lot of reason to believe that people that have to travel to see customers and do dinners and do conferences can do three, four times their quotas.”

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Cedric Pech describes his earlier manager Carlo Carpinelli, who never went into a sales call without him, even with the chief executive of Ferrari. Carpinelli gave him credit with the customer, put him in the driver's seat to develop him, and stepped in only if needed. In a later role, Cedric says a leader took over the whole meeting and left him with zero empowerment, and he told the leader it sounded like he had promoted himself into being the rep on that account.

“In a sales -driven organization, the most important people in the room is a rep.”

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Carlos described how his first manager at PTC told him, after he had been doing the reps' meetings, that he was paid to be a manager and not a rep. The lesson he took was that solving problems through reps builds their skill, even if it takes twice as long or the problem is solved half as well.

“your job is to make the sales reps self-sufficient”

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Simon said Bloomreach was largely focused on gross revenue retention when he joined five and a half years ago, which made sense because customer success grew out of retention. They rebalanced CSM comp to 50% GRR and 50% NRR, reasoning that CSMs are in the account every week and know the customer's priorities, pain points and where they are growing or struggling, so they are best placed to find expansion opportunities.

“Now it's 50 % GRR focused, 50 % NRR focused”

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Cassie Vaughn said monday.com changed its compensation model this year so CSMs have variable pay on retention and growth. She said the retention piece is what lets CS organisations prove they influence revenue, and that taking a stake in the game is what that requires. She said it also rewards CSMs who do strong work but do not get to celebrate when a deal closes.

“They have variable compensation on both retention and growth.”

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