Discover why traditional sales tactics still dominate AI-native markets. Graham Moreno shares proven enterprise sales strategies that drive results in 2024.
Old School Sales in the AI Era: Why Personal Touch Still Wins
Key Takeaways
- Personal relationships trump technology: Even with advanced AI tools, enterprise deals depend on human trust and face-to-face engagement, not just product features
- Structured sales processes enable freedom: The best organizations combine clear operational stages with autonomy for sellers to innovate and personalize their approach
- Sales excellence in AI companies differs by speed, not substance: AI-native customers move 5-8 business days vs. 6-8 weeks for traditional enterprise, but the fundamental relationship-building principles remain identical
- Enablement and boot camps create cultural touchstones: Competitive training programs build community, establish elite standards, and create shared identity that drives long-term success
- One person should own go-to-market strategy: Fragmented leadership across multiple GTM pillars creates confusion; centralized ownership prevents misalignment and ensures accountability
- Post-sales success directly impacts expansion revenue: In the AI era where multi-year contracts are rare, post-sales retention and expansion account for the majority of revenue growth
- Force-multiplier activities compound results: Focusing 50% of leadership time on partner enablement, boot camp optimization, and one-on-one coaching yields non-linear returns
The Misconception About Modern Sales: Old Playbooks Still Win
The conversation around sales in the AI era reveals a fascinating paradox. When AI-native companies emerged post-2020, there was widespread sentiment that traditional sales playbooks—the ones perfected by Mongo, Datadog, and Snowflake during the cloud era—were suddenly obsolete. Founders and early-stage team members proudly rejected structured sales processes, celebrating Product-Led Growth (PLG) as the new paradigm. The premise was simple: if the product is good enough, it will sell itself. Sales, as a function, became something to minimize rather than celebrate.
The reality, as Graham Moreno discovered through building go-to-market teams at Windsurf, Cognition, and now Parallel, is far more nuanced. "There's a lot of pride in PLG," Moreno explains, "and the idea that we want the product to carry the sales motion forward. But I've found that it's very much in the middle." The anti-sales sentiment among AI companies often stems from inexperience with what truly great sales organizations actually do. Rather than replacing personal relationships with algorithms, the most successful AI companies are actually doubling down on the human elements that made enterprise sales effective in the first place—they're just doing it faster and through different channels.
The fundamental insight is this: technology parity is the baseline, not the differentiator. When you're evaluating one of the top three AI vendors in any category, the technology is likely within 10% feature parity. At that point, the decision comes down to trust, relationships, and confidence that a vendor will show up and support you through implementation. This is where old-school sales excellence becomes not just relevant but essential. The companies that win in AI markets aren't those that eliminate sales; they're those that evolve it.
Enterprise Sales Reality: Why Change Management Beats Technology Every Time
The persistent truth that Moreno encountered across multiple companies is that in enterprise environments, change management dictates success far more than the technology itself. This principle has not changed in the AI era—it has only become more pronounced. Consider the implementation of AI codegen tools at large financial institutions. Banks don't fail to adopt these tools because the technology is inadequate; they struggle because getting thousands of engineers to change how they work requires far more than releasing a product into a marketplace and hoping it spreads organically.
When Windsurf was scaling its enterprise customer base, the company made a deliberate choice that differentiated it from competitors: they invested in physical presence. Two representatives didn't just conduct Zoom calls from San Francisco; they traveled to India, Europe, and across the United States, sitting with different offices at various banks. This wasn't a sales tactic—it was a commitment to understanding workflows, proposing new ways of working, and building confidence through demonstrated partnership.
The data from these rollouts told a compelling story. Banks that engaged in structured, supported rollouts with dedicated vendor presence showed substantially more measurable success at the six-month mark compared to banks that simply deployed multiple tools into an internal marketplace and hoped adoption would happen organically. The difference wasn't subtle. Companies that followed the old-school playbook—dedicated training, executive alignment, ongoing enablement, and visible vendor commitment—saw meaningful adoption and productivity gains. Companies that didn't saw minimal measurable change and users developing their own inconsistent workflows through trial and error.
Why did this happen? Because executives at enterprise organizations understand a fundamental truth: getting large groups of people to change behavior is genuinely difficult. An employee pulled into a two-hour training session is wondering why they're not doing their primary job. For that training to be valuable, it requires an upfront value proposition so clear that employees understand exactly what they'll be able to do differently in week one, week four, and week twelve as a result of attending. Without that clarity, you're asking people to invest time with no guarantee of return.
The best enterprise sales organizations recognize this challenge and meet it with structure, clarity, and presence. They don't just explain what the product does; they explain how it changes work, who needs to be involved in implementation, what success looks like, and crucially, they show up in person to ensure that vision becomes reality. This isn't outdated; in fact, it's more valuable in the AI era precisely because so much of the market is trying to shortcut it.
The Speed Difference: AI-Native Sales Cycles Compress, but Fundamentals Remain
One of the most striking differences Moreno observed between selling to traditional enterprises and selling to AI-native companies is the compressed timeline. What might naturally take six to eight weeks in a traditional enterprise context can happen in five to eight business days when selling to an AI-native customer. This isn't because the sales process is fundamentally different; it's because the communication patterns are radically different, and the baseline familiarity with AI tools eliminates a massive education curve.
AI-native customers—those who grew up using ChatGPT in high school or college—approach technology evaluation completely differently. They don't need someone to explain what an AI agent is or why they might want to use one. They've already been living with these tools for years. The conversation shifts from "what is this?" to "how do I optimize for my specific use case?" This is a critical distinction that changes the sales motion significantly.
The communication style reflects this difference. With traditional enterprises, communication might occur in scheduled meetings and formal channels. With AI-native companies, communication happens continuously through Slack, text, and asynchronous updates. There's an expectation of constant dialogue, similar to ongoing conversations with ChatGPT itself. Sales representatives might provide optimization tips, the customer goes away to implement, provides feedback, and then you jump on a call every couple of days with significantly more context because you've been in real-time dialogue the entire time.
This compressed timeline creates what appears to be a fundamentally different sales process, but the underlying principles remain constant. You're still building understanding of customer workflows. You're still proposing solutions. You're still earning trust through demonstrated competence and follow-through. You're still establishing ongoing relationships that extend beyond the initial purchase. The channel and cadence have changed; the substance has not.
Importantly, this also means that the type of person who thrives in AI-native sales isn't necessarily a different breed of salesperson. A high-performing enterprise seller who naturally overcommunicates, who builds deep relationships, and who genuinely cares about customer outcomes might need to adjust to being on Slack constantly rather than sending weekly project recap emails. But the fundamental personality traits—curiosity, empathy, problem-solving orientation, genuine care for customer success—are identical. What matters most in both contexts is that you hire people who are smart, can think through problems, and genuinely care about helping customers succeed. You can't fake that, and no amount of process can compensate for hiring the wrong person.
The "Squeezing the Orange" Strategy: Simultaneous Developer and Executive Engagement
One of Moreno's most effective strategies at Windsurf and Cognition was what he describes as "squeezing the orange"—applying pressure from both sides of the organization simultaneously. This approach recognized a critical reality: in enterprise software adoption, you need both grassroots enthusiasm and executive mandate. Either alone is insufficient.
From the bottom up, this meant building an exceptional developer relations practice. It wasn't enough to have salespeople talking about the product; the company needed to genuinely understand developer workflows, aspirations, and pain points. This meant meeting engineers where they already gathered—on Twitter, at meetups, at conferences. It meant being present in communities where developers naturally congregate and building a reputation for understanding their challenges and offering genuine value. This developer relations function couldn't be transactional; it had to be built on authentic interest in the developer community's success.
Simultaneously, from the top down, the organization maintained robust executive engagement. This meant direct relationships with CIOs and CTOs, individuals managing massive budgets and increasingly under pressure from CFOs to demonstrate significant productivity gains. These executives were hearing stories of competitors cutting headcount by 40% while tripling productivity. Without direct engagement at this level, grassroots efforts alone would fail to drive meaningful organizational adoption.
The critical insight was that great sales organizations serve as a crucial conduit between these two groups. A CIO at a major bank might be nine organizational layers removed from the engineers actually using the tools. Those executives rarely receive direct, credible feedback about what's really happening in the trenches. However, a vendor conducting extensive training and onboarding can gather invaluable intelligence and bring it back to executive conversations, fundamentally changing the strategic dialogue.
This two-sided engagement also required substantial upfront investment. Moreno didn't wait until the company had massive scale to build out this infrastructure. At Windsurf, when annual revenue was still in the single-digit millions, the organization prioritized hiring a world-class partner manager, an enablement specialist, and a data expert. The conventional wisdom would have been to wait until $250 million in revenue to build these functions. Instead, Moreno built them at $40 million, understanding that these investments would compound dramatically as the company scaled.
By the time Windsurf reached $50-100 million in revenue, the company had established deep relationships within critical centers of excellence—partnerships and influence networks that wouldn't have been accessible without years of intentional relationship building. When a major bank needed vendor presence at a last-minute event in Singapore, Windsurf could mobilize 30 people from trusted partners rather than just sending one or two internal representatives. This force multiplication was possible only because of early, disciplined investment in partner relationships.
Building Elite Sales Organizations: The Boot Camp Effect
One of the most powerful cultural tools Moreno implemented across multiple organizations is the boot camp model—an intensive, competitive, community-building onboarding experience. At Mongo, this became a legendary touchstone. Every new salesperson went through three to four weeks of online training, covering product, market, competitive dynamics, and customer use cases. The training was taken seriously, with meaningful assessments that determined who truly absorbed the material versus who merely went through the motions.
The week-long in-person component wasn't just about knowledge transfer; it was a carefully designed cultural ritual. There were competitions—trivia games designed to force recall after long days of learning, mock discovery calls performed in front of peers who rated performance, role-playing scenarios that built both reputation and friendships. This wasn't drudgery; it was genuinely fun, intensely competitive, and designed to raise standards while making the experience enjoyable.
The genius of this approach lay in its long-term cultural impact. Years later, Mongo employees would ask each other, "What boot camp class were you in?" It became an orienting principle for the entire organization. People would discuss differences between cohorts—"Oh, they had scrapped that training by the time I came through, but we did this version." More importantly, it became a shared cultural touchstone, a source of pride about having survived something difficult and meaningful.
This boot camp effect accomplishes several critical things simultaneously. First, it establishes early that excellence is an expectation, not a suggestion. Second, it demonstrates that being excellent can be fun and engaging rather than a grinding ordeal. Third, it builds community and camaraderie among cohorts, creating networks that persist throughout careers. Fourth, it ensures that every salesperson who exits boot camp has been assessed against clear standards and has proven baseline competency.
This last point is crucial in the context of AI-era sales. With AI tools providing instant information access, there's a temptation to eliminate rigorous training and testing. Why memorize facts when you can ask an LLM? The answer is that real enterprise sales requires judgment, intuition, and the ability to navigate complex human and organizational dynamics. An LLM can provide information about database architecture, but it cannot teach you how to manage organizational change in a financial services institution. It cannot understand the political dynamics of getting a thousand engineers to adopt new tools. It cannot build the judgment that comes only through repetition, reflection, and learning from experience.
The strongest sellers aren't those with the fastest access to information; they're those who have internalized frameworks, developed pattern recognition, and built the intuitive judgment that allows them to navigate ambiguous situations. Boot camp, designed well, creates the conditions for that development. It signals that the organization values mastery, provides the tools for mastery, and celebrates those who achieve it.
The Science of Sales Pipeline: Instrumenting the Revenue Cycle
While culture and relationships are essential, they're not sufficient. Moreno's approach combines relationship-focused selling with rigorous process instrumentation. This might seem contradictory—doesn't measuring and instrumenting everything undermine the personal, relationship-driven approach? In practice, these elements are complementary.
The sales process Moreno typically implements has clear stages, usually three to five, with specific criteria for advancement. The stages might look like: first meeting qualification, use case evaluation, proof of value initiation, scope agreement, and close. At each stage, you ask: What specific outcomes must occur to move forward? What percentage of opportunities move from this stage to the next? How long does each stage typically take?
By instrumenting each stage, you build a heat map of your entire revenue cycle. You discover, for example, that cold outreach takes three weeks to generate a first meeting, that 40% of first meetings convert to use case evaluation, that 50% of use case evaluations move to scope, and that 60% of deals in scope close. Suddenly, the mystical revenue cycle becomes transparent and actionable.
This transparency is powerful because it enables coaching without confrontation. Instead of a manager saying, "You're not closing deals," a manager can say, "Your time in use case evaluation is significantly longer than the company baseline. Let's look at three of those deals and understand what's extending the timeline." This shifts the conversation from performance criticism to problem-solving collaboration.
The heat map also reveals which levers have the most impact. Perhaps discovery calls are taking too long. Maybe qualification is ineffective, letting too many poor-fit deals advance. Maybe scope conversations aren't clarifying customer commitment. Rather than guessing where to focus coaching energy, the data shows exactly where improvements would have the highest impact.
Crucially, this instrumentation should happen at multiple levels: company average, by customer segment (AI-native vs. enterprise), by team, and by individual rep. This allows for personalized coaching. A rep might be below average on initial conversion but above average on deal size and close rate. Another rep might excel at moving deals through early stages but struggle with longer negotiations. Understanding these patterns enables you to coach to strengths while addressing true weaknesses.
The measurement approach changes how you think about sales leadership. Instead of intuition-based gut calls about performance, you have data illuminating the entire revenue cycle. This means, as a leader, you're never in a position of saying, "I have no idea why we missed quota." You can point to exactly which stage underperformed, which segment is carrying the load, and which reps are trending toward or away from target.
Sales Organization Structure: One Owner, Clear Direction
One critical lesson Moreno emphasizes repeatedly is the importance of having a single owner for go-to-market strategy. This seems obvious in theory but is remarkably difficult in practice, especially as organizations scale and functional leaders want influence over strategy.
The problem with splitting go-to-market ownership across multiple people is that it creates exactly the right conditions for misalignment. Imagine taking three people, spinning them around for two minutes, tying their legs together, and then telling them to walk straight. No one intends to pull in different directions; everyone believes they're moving toward the same goal. Yet without explicit alignment, they inevitably lean in different directions, creating tension and confusion throughout the organization.
The optimal structure is to have one person responsible for all revenue-generating and customer-facing functions: sales, customer success, perhaps deployed engineering, and partner programs. This person owns the go-to-market strategy, reports to the founders and board, and has absolute clarity about direction. This doesn't require authoritarianism or top-down control; it simply requires clarity about who owns what.
This is particularly important for post-sales and customer success. The worst-case scenario is when customer success reports to the VP of Product while sales reports to the VP of Revenue. In this structure, customer success optimization looks different from sales optimization, expansion revenue might not align with initial sales targets, and there's no unified understanding of which customer types are most valuable.
The better structure is customer success reporting to whoever owns go-to-market strategy. This individual is responsible for ensuring that customers successfully adopt and extract value from the product, because their compensation and success depends on both initial sales and expansion revenue. They have skin in the game on the entire customer lifecycle.
This unified ownership also enables cross-functional communication in the right direction. Success learns from sales what promises were made and what customers need most. Sales learns from success what customers are actually achieving and what drives retention. These conversations happen naturally when there's a single person owning the outcome for the entire customer relationship.
The Human Element: Why Great Sellers Can't Be Replicated by Process
Throughout his career, Moreno has observed that the most impactful sales moments rarely appear in process documentation. He recalls a representative who discovered that a customer champion's son was taking guitar lessons. The rep mentioned that he played guitar and taught lessons, so he began teaching the customer's son online during COVID—without telling anyone it was happening, without documenting it as a customer engagement strategy, simply because he cared about building a genuine relationship.
Months later, the customer champion mentioned this on a call with Moreno, clearly moved by the rep's genuine interest in his family's wellbeing. This moment—which created immense goodwill and strengthened the relationship—emerged not from process but from the rep's authentic character and willingness to go beyond professional boundaries to be helpful.
This raises an important question about scaling: How do you create a sales organization that has consistent minimum standards without eliminating these magical moments that come from human judgment and generosity?
The answer lies in what Moreno calls "raising the floor while not capping the ceiling." A good process establishes clear minimum expectations. All sellers should be having discovery conversations that adequately understand customer problems. All sellers should be following up appropriately and keeping deals progressing. All sellers should be documenting their activity so the organization can understand what's working. But the process shouldn't be so prescriptive that a rep feels micromanaged into conformity.
The best sales leaders create cultures where the default is "yes" to smart ideas. Moreno describes his approach: "If someone has thought something through, I'll ask a couple of questions, but there's an almost 100% chance I'll say yes. This makes them accountable for the outcome." When the default is "no" without good reason, people stop proposing ideas and start asking permission constantly. When the default is "yes," people innovate within bounds and feel ownership of results.
This requires hiring carefully. Moreno doesn't hire people based on their ability to execute processes; he hires smart, problem-solving people who care deeply about customer success. He looks for curiosity, genuine interest in helping others, and the kind of personality that makes people want to work with them. These traits allow people to operate effectively within a lean process while also having the judgment to do something extraordinary when the moment calls for it.
The guitar lesson story isn't an outlier; it's an example of the kinds of relationships that emerge when you hire the right people and give them enough autonomy to be themselves. The trick is measuring performance in ways that reward these relationships without being so rigid that they can't happen.
Compensation Structure: Aligning Incentives with Behavioral Expectations
Sales compensation deserves careful attention because it signals what the organization actually values, separate from what leaders say they value. Moreno advocates for commission-based compensation structures for sales roles, not because it's the only right answer but because it aligns incentives and attracts a particular type of driven, competitive person.
This isn't about creating greed or unhealthy competition. Rather, it's about recognizing that highly motivated people respond well to clear, measurable incentives. These individuals are often successful because they have "chips"—drivers that push them to succeed, whether that's overcoming adversity, proving something to themselves, or living up to family expectations. Appropriate compensation structures amplify these drives in productive directions.
The math of commission structures has evolved significantly. While a 5x OTE commission structure was once considered spectacular, modern quota structures often target 10x OTE, with accelerators reaching 20x or 30x. At those levels, top performers are generating value many times over what they're being compensated. When a single deal has margins that allow a rep to earn 20x their base salary, that rep has paid themselves and everyone else back many times over.
What's interesting is that these accelerator structures attract different types of people and change behavior. Even highly motivated people, genuinely committed to doing the right thing for customers, will be slightly more attentive when there's significant money on the table. It's not about creating wrongdoing; it's about amplifying already-present drives.
More importantly, healthy commission structures signal organizational values. If you're willing to pay exceptional performers substantially more, you're signaling that sales contribution is genuinely valued. If you're capping upside and keeping commissions minimal, you're signaling that sales is a necessary function, not a celebrated one. Top talent responds to these signals.
There's one final element of compensation worth mentioning: the best leaders are actually more excited about paying out commission checks to team members than earning their own. Moreno describes the moment when Cognition acquired Windsurf, and he saw the impact on 200 people he'd been mentoring and leading. That collective success—people he'd invested in achieving financial wins—was more gratifying than any individual achievement.
This perspective matters because it indicates a healthy relationship with money and success. If a leader is keeping commission money for themselves or creating compensation structures designed to disadvantage salespeople, the best talent will eventually leave. If a leader is genuinely excited about team members succeeding financially, that excitement becomes contagious and builds culture.
Enabling the Seller: AI Tools and the Irreplaceable Value of Human Judgment
The rise of AI tools has raised important questions about enablement and seller development. If AI can instantly provide information about competitive positioning, customer use cases, or industry dynamics, why invest heavily in training and knowledge development?
The answer separates effective salespeople from those merely using information lookups to sound credible. There's a critical difference between having information at your fingertips and having judgment. An LLM can tell you what Cursor does; it cannot tell you how to navigate the political dynamics of a bank's IT department adopting new developer tools. It can't explain why change management failures often stem from insufficient training and executive alignment. It can't help you understand which customer segments will be early adopters and which will resist.
This judgment comes only from deep study, pattern recognition across many situations, and learned intuition about human and organizational behavior. The sellers who will be most effective in the AI era aren't those who can access information fastest; they're those who have developed judgment about what that information means in context.
AI enablement tools, used correctly, can actually amplify this advantage. Rather than watching a single example of a discovery call, a seller can use AI simulation to practice dozens of scenarios, learning to string concepts together and develop deeper understanding. This forces more complex thinking than passive information consumption and builds the underlying neural patterns that develop actual skills.
The challenge is ensuring that sellers use AI tools to develop judgment rather than outsource it. This comes back to hiring. If you hire inherently curious, driven people who want to be excellent, they'll use AI tools to deepen understanding rather than replace it. If you hire people just looking for a paycheck, you'll get representatives who read AI-generated talking points over Zoom and lack credibility in real relationships.
Leadership: Multiplying Force Through People and Systems
Moreno describes his approach to high-impact leadership as identifying the most force-multiplicative activities and dedicating significant time to them. At Windsurf, where the organization decided to route 100% of revenue through partners, this meant devoting substantial time to the partner organization. Rather than trying to build a massive direct sales team, he worked extensively with the partner leader and their direct reports, building deep relationships with systems integrators and value-added resellers.
This approach generated non-linear returns. A well-enabled partner selling Windsurf's product into their existing customer relationships had far greater impact than an additional internal rep. The partner already had trust, existing service relationships, and ability to integrate Windsurf into broader offerings. The leverage was massive.
Similarly, in enablement, he focused extensively on boot camp optimization. By analyzing ramp data across cohorts and continuously refining the program, they discovered opportunities to shave entire weeks off new hire ramp time. With 40-50 people going through boot camp monthly, reducing ramp by one week meant 40-50 person-weeks of productivity gained. Multiplied across quarters, this was substantial impact.
This analysis led to what Moreno describes as roughly 50% of his time dedicated to these two or three force-multiplicative areas. Another substantial portion went to one-on-one meetings—often dedicating two to three full days weekly to individual check-ins with team members. Some were scheduled regular touchpoints; others were ad hoc conversations when reps were working through deals or facing challenges.
This accessibility matters more than many leaders realize. A rep struggling with a renewal knows they can grab time with leadership to think through the problem. A rep closing a major deal can debrief and discuss strategy. The message this sends is that leadership cares about the individual, not just the result. Over time, this builds cultures where people feel supported rather than just measured.
The return on this time investment compounds significantly. Strong cultures attract similar people, creating concentric circles of like-minded individuals who enjoy working together, trust each other, and feel invested in collective success. The time spent on hiring, developing, and building culture yields multiplicative returns as the organization scales.
Forward Planning: Building Capacity Models and Strategic Evolution
Once a sales organization has reached operational stability—typically around six to nine months into the intentional build—the leadership focus should shift toward strategic evolution. At this point, basic activities like hiring, onboarding, and process refinement are functioning smoothly. The opportunity moves toward anticipating future needs and building capacity in advance.
This requires working backward from desired future states. If a product launch is planned for Q3, you should be hiring ahead of that in Q1 to ensure onboarding is complete and reps are productive by launch. If the organization wants to focus on specific verticals like insurance or healthcare, field marketing, product marketing, and sales collateral need to be developed well in advance. If executive relationships will be critical to expansion, you need to identify and build those relationships months before scaling the team.
This forward-looking approach prevents the chaos of mid-year structural changes. Rather than surprising the organization with a major change mid-quarter, you prepare for it, ensuring all stakeholders understand the strategy and have the resources they need. You're not just reacting to market conditions; you're positioning the organization to capitalize on them.
This is where capacity modeling becomes essential, even though some leaders dislike it. Working through spreadsheets that project hiring timelines, onboarding curves, and ramp rates feels bureaucratic. But without this analysis, you're flying blind. You might hire 10 reps assuming they'll be productive in 8 weeks, only to discover your onboarding infrastructure can only absorb 5 reps productively. Suddenly, you have underutilized team members, inconsistent results, and culture problems.
The best leaders spend 70-80% of their time, once the foundation is established, looking three to six months ahead—anticipating needs, building relationships, preparing for changes, and ensuring cross-functional alignment. This forward-looking stance is what separates organizations that scale smoothly from those that repeatedly experience chaotic transitions.
Conclusion
The fundamental insight about sales in the AI era is that the most important elements haven't changed—they've become more important. In a world of AI feature parity and rapid technological change, the differentiators are profoundly human: Do you build genuine relationships? Do you show up when it matters? Do you understand your customer's business well enough to offer real guidance? Can you manage organizational change effectively?
These questions would have been valid when selling databases or infrastructure software. They're equally valid now. What has changed is the speed at which things move, the channels through which relationships develop, and the baseline competency expected from everyone entering the field. But the core truths remain: great sales is about understanding customers deeply, building trust through consistent delivery, and being willing to invest in relationships that create mutual success.
The best go-to-market organizations recognize that old-school sales excellence hasn't been replaced; it's been accelerated. They combine rigorous process discipline with cultural investment in people. They measure what matters while empowering individuals to innovate beyond the baseline. They hire smart, driven people who care genuinely about customer success, and they create environments where those people can do their best work.
For founders and go-to-market leaders navigating the AI era, the playbook is clearer than it might appear: invest in people, build systems that provide clarity without stifling innovation, enable sellers with both knowledge and judgment, and be willing to show up in person to build the relationships that ultimately drive success. The technology will evolve. The fundamentals of human connection, trust, and reliable delivery will not.
Original source: Why old-school sales work still wins in the AI era | Graham Moreno (Head of GTM, Parallel)
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