---
title: "From $500M to $10B: The CRO Playbook for Constant Reinvention"
episode: 71
podcast: "The LeanScale Podcast"
publisher: "LeanScale"
guest: "Alex Loktev"
guest_title: "Chief Revenue Officer, P2P.org"
date_published: 2026-05-15
date_modified: 2026-07-22
duration: 00:58:20
word_count: 8115
topics: ["gtm-strategy", "revenue-operations", "ai-in-gtm", "sales-leadership", "mergers-acquisitions"]
canonical_url: https://leanscale-knowledge-hub.netlify.app/podcast/alex-loktev-cro-playbook-reinvention/
source: "LeanScale Podcast Knowledge Hub — https://leanscale-knowledge-hub.netlify.app"
license: "Free to quote and cite with attribution to The LeanScale Podcast."
---

# From $500M to $10B: The CRO Playbook for Constant Reinvention

_Alex Loktev on scaling P2P.org through five GTM pivots — who controls the client, the Golden Era trap, and going AI-native_

**Episode 71 · The LeanScale Podcast**  
Alex Loktev, Chief Revenue Officer, P2P.org · Hosted by Anthony Enrico  
Published May 15, 2026 · Updated July 22, 2026 · 00:58:20  
Canonical: https://leanscale-knowledge-hub.netlify.app/podcast/alex-loktev-cro-playbook-reinvention/

**Topics:** GTM Strategy · Revenue Operations · AI in GTM · Sales Leadership · Mergers & Acquisitions


## Executive summary

Most GTM playbooks assume the market holds still long enough to run them. Alex Loktev's doesn't. As CRO at P2P.org — one of the largest institutional staking-infrastructure providers, managing over $10 billion in staked assets for 130-plus institutional clients — he has rebuilt his entire go-to-market four times in four years, and is mid-way through a fifth pivot as he sits down with LeanScale co-founder Anthony Enrico. His business earns a fractional commission on every blockchain transaction it validates, at a scale of millions of validations a day, and the whole company grew from $500 million to $10 billion in assets while the market underneath it reinvented itself roughly every six months. This is a clinic in building a revenue function that is designed to be torn down and rebuilt on schedule.

The spine of Alex's thinking is a single question he returns to at every phase: who controls the client, the revenue, and the margin? Early on, P2P controlled the client's decision-making — the market barely existed and reps had to educate every buyer from scratch. That phase, he argues, is paradoxically the best one: competition is lowest and margin is highest because customers have no idea what a fair price is. But educating the market is the same act as accelerating your own commoditization. As buyers get smart, intermediaries (custodians, banks, wallets, exchanges) step between you and the client, and eventually the regulator becomes the actor who really controls the buyer. Each shift in control forced P2P to rebuild its product strategy, sales team, brand, and materials — moving from direct sales to a channel motion that now drives 80% of revenue.

The most uncomfortable lesson is about people. Surviving each transition means replacing team members who are genuinely succeeding in the current phase but can't retool for the next one — trading technology enthusiasts for practical account executives, then rebuilding again for relationship-led commodity selling. Anthony connects it to 'raising your floor' from The Science of Scaling: judge talent by how they perform on their worst day, not by their potential, and you'll stop holding onto people too long. Alex pairs this with a 'Golden Era trap' warning — the moment business feels easy is the exact signal that commoditization has begun and you should already be building the next high-margin product behind it.

The second half turns to how Alex sees around corners. He runs a GTM R&D function — housed under RevOps, seeded by his very first hire — whose full-time job is watching where venture capital flows at the seed and pre-seed stage. VC money, he argues, is the smartest and cheapest market signal available: it tells you what to replicate, what to acquire, and where competition will bubble up, two or three years early. He manages a fractal product portfolio around that intelligence — a commoditizing core product used as an entry wedge, with higher-margin products still early on the educational curve layered on top.

Finally, both operators land on AI. P2P is an AI-native firm running its own internal LLM, using Clay and Apollo, testing AI-native CRMs, and running company-wide hackathons where more than half the participants are non-technical. Alex's paradigm shift came when he vibe-coded his own sales-prep tool in five evenings for $200 using Cursor — proof that if a tool doesn't exist or is too expensive, you now just build it. LeanScale made the same move: max Claude Code accounts for everyone, two-hour onboarding sessions per employee, and consultants shipping more tools than the engineers. Both reject the layoff narrative: if a person can produce 10x, you don't fire 90% of the team, you 10x what you produce. Who should listen: CROs, founders, and GTM leaders in fast-moving markets (AI, crypto, SaaS) who need to reinvent before the market forces them to.


## Key takeaways

1. **Ask who controls the client, the revenue, and the margin** — Alex's master signal across four years and five pivots is a single triad of questions: who controls the client, who controls the revenue, and who controls the margin. As control shifted — from P2P owning the buyer's decision, to intermediaries owning it, to the regulator owning it — every answer forced a different GTM.
   _Why it matters:_ Instrument your business around control, not just pipeline. The moment the answer to 'who controls the client' changes, your motion, product strategy, brand, and team have to change with it — usually before the numbers show it.
   _For:_ Revenue Executives, Founders, RevOps Leaders

2. **The hardest phase to sell is also the highest-margin one** — In the earliest phase you struggle in every meeting just to explain what you sell — but that's the easiest time in the business economically: competition is lowest and margin is highest because clients have no idea what a fair price is. There is no price pressure at all until buyers get educated.
   _Why it matters:_ Don't confuse effort with disadvantage. Early market-education pain is where the fattest margins live; harvest them deliberately, because educating the market is the same act that ends the golden margins.
   _For:_ Founders, Revenue Executives, Sales Leaders

3. **The Golden Era is the start of commoditization, not the reward** — The 'golden era' — strong demand, high margin, still-low competition, buyers who finally get it — feels like earned success. Alex's warning: the second it feels easy, VCs are funding the segment, enterprises are moving in, and price pressure and commoditization are already beginning.
   _Why it matters:_ Treat 'easy' as an alarm, not a milestone. When you hit the golden era, you should already be building the next high-margin product, because your current core is about to become a low-margin entry wedge.
   _For:_ Founders, Revenue Executives

4. **Rebuild the team at every phase — even replace successful people** — Each transition needs a different seller: technology enthusiasts to educate the market, then practical account executives, then relationship-led reps who can win commodity and pricing wars where product excellence is merely table stakes. The hardest part is replacing people who are currently closing deals but can't retool for the next phase.
   _Why it matters:_ The team is the first thing to rebuild, not the last. If a high performer in the old context can't re-educate for the new one, moving them on is a survival decision, not a performance one.
   _For:_ Revenue Executives, Sales Leaders

5. **Raise the floor — judge talent by their worst day, not their potential** — Anthony brings in 'raising your floor' from The Science of Scaling: like a professional athlete, the greats are strong on their worst days rather than showing flashes of brilliance and being average on Sundays. Evaluating potential makes you hold onto people too long; evaluating the floor tells you who clears the next stage's bar.
   _Why it matters:_ As you scale phases, raise the floor of your team, your customers, and what's acceptable at the company. You'll quickly find too many people below the new standard — and that clarity is the point.
   _For:_ Revenue Executives, Sales Leaders, Founders

6. **When intermediaries — then regulators — take the client, pivot the whole GTM** — P2P moved from direct control of the client, to a phase where custodians, banks, wallets, and exchanges controlled the buyer (triggering a shift to channel sales, now 80% of revenue), to a phase where the regulator is becoming the controlling actor. Like the Devil Wears Prada line about fashion: even if you don't care about the regulator, the regulator cares about you.
   _Why it matters:_ Watch for control migrating up the chain. Channel and regulatory shifts are whole-GTM events — new team profiles, new brand, new materials — not marketing tweaks. The most regulator-adapted company in a segment wins the biggest profits.
   _For:_ Revenue Executives, Founders, Sales Leaders

7. **Run a fractal product portfolio** — Decisions center on product strategy: the core product generates less and less margin but stays a significant, sticky entry tool for customers. Around it, Alex hunts for smaller players sitting earlier on the educational curve with higher margins — products to replicate in-house or acquire — repeating fractally to keep expanding portfolio and account depth.
   _Why it matters:_ Use your commoditizing core as a wedge and constantly stack higher-margin, earlier-curve products on top. This is how you thicken each customer relationship and keep blended margin up as any single product commoditizes.
   _For:_ Founders, Revenue Executives

8. **Follow VC money as the cheapest signal of the next big thing** — The smartest money on the market is VC money. By tracking where funds — especially seed and pre-seed — allocate capital, categorized by segment in a monthly-reported spreadsheet, you get near-free visibility into the next big thing two to three years out. Even a failed individual investment still validates the segment, because seed capital flows when a startup first hits product-market fit.
   _Why it matters:_ Build a running, segmented map of venture flows in your industry. It tells you which products to replicate, which companies to acquire early, and where competition will emerge — market proof, not hypothesis, at almost zero cost.
   _For:_ Revenue Executives, RevOps Leaders, Founders

9. **Put market intelligence — GTM R&D — under RevOps** — Alex's first-ever hire was a RevOps lead, and a large part of the RevOps mandate is scanning the market and overviewing trends. In a fast-moving segment you must allocate budget to an R&D function whose day-to-day job is watching startups and VC flows — now orchestrated cheaply by AI agents rather than someone manually reading Crunchbase.
   _Why it matters:_ RevOps is the natural home for GTM R&D. Fund a small trend-watching function (or agent fleet) inside revenue ops; it's one of the highest-ROI, lowest-cost bets a revenue leader can make.
   _For:_ RevOps Leaders, Revenue Executives

10. **Go AI-native: if a tool doesn't exist or is too expensive, build it** — P2P runs its own internal LLM, uses Clay and Apollo, and tests AI-native CRMs. Alex's paradigm shift came when he couldn't find a tool to challenge reps with tough questions before calls, so he vibe-coded one himself in five evenings for $200 using Cursor. The company now runs hackathons where more than half the participants — finance, legal, sales — are non-technical.
   _Why it matters:_ Default to build-or-buy at the individual level. Arm every employee (technical or not) with agentic tools and a basic AI-competency bar; the highest leverage often comes from non-technical people finally able to build what they understand.
   _For:_ Revenue Executives, RevOps Leaders, Founders

11. **AI abundance grows teams — it doesn't trigger layoffs** — Both operators reject the workforce-reduction narrative. If a person can now do 10x the production, that doesn't mean firing 90% of the team; it means producing 10x more, and then hiring more people who can produce at that level. There's no limit to human curiosity or an organization's appetite to create — Alex compares AI to the first tool in a human hand, calling it the second most important technology ever.
   _Why it matters:_ Frame AI as an abundance and throughput multiplier against unbounded demand, not a cost-cut. Cheaper niche products, faster iteration, and more output — not smaller headcount — is the growth-oriented response.
   _For:_ Founders, Revenue Executives, RevOps Leaders


## Frameworks

### Who Controls the Client, Revenue, and Margin (04:23)

**Definition:** The single diagnostic Alex uses to decide when and how to change GTM: at any moment, identify who controls the client's decision, who controls the revenue, and who controls the margin. When the answer changes, the go-to-market must change.

P2P's control migrated from itself (educating a market that didn't exist), to intermediaries like custodians, banks, and exchanges (forcing a channel-sales pivot), to the regulator. Each migration was the true trigger behind a product, team, brand, and materials rebuild — the master variable behind every pivot.

### The Educational Curve (05:13)

**Definition:** A market maturity curve every industry travels: from a phase where you must educate buyers from scratch (highest margin, lowest competition), through growing awareness and competition, to full commoditization where price pressure peaks.

The paradox is that the hardest phase to sell in is the most profitable, and the act of educating the market accelerates your own move down the curve. Reading where you sit on the curve dictates the seller profile, sales materials, and margin expectations for each phase.

### The Golden Era Trap (15:51)

**Definition:** The 'golden era' — strong demand, high margin, still-low competition, educated buyers — is not a reward to enjoy but the starting point of commoditization, and it signals you should already be building the next product.

When business gets easy, VCs are funding the segment and enterprises are entering; price pressure and competition follow fast. Recognizing the golden era as an alarm, not a milestone, is what separates proactive reinventors from startups that coast and die.

### Raise the Floor (22:14)

**Definition:** A talent principle (from The Science of Scaling) of evaluating people, customers, and standards by their worst-day performance rather than their potential — like a professional athlete who is great on their worst day, not just in flashes.

Judging potential makes leaders hold onto people too long; judging the floor reveals who can't clear the next stage's bar. As a company moves through GTM phases, it must raise the floor of the team, the customers it takes on, and what's acceptable — which quickly exposes how many people fall short.

### The Fractal Product Portfolio (32:30)

**Definition:** A portfolio-scaling model where a commoditizing, lower-margin core product is used as an entry wedge, and higher-margin products sitting earlier on the educational curve are layered on top — replicated in-house or acquired — repeating at every level.

You always keep a bigger product (high revenue, thinning margin) surrounded by smaller ones still early on the curve with higher margins. Finding and adding those early-curve products thickens each customer relationship and keeps blended margin up as any single product commoditizes.

### VC Money as a Market Signal (GTM R&D) (36:17)

**Definition:** A market-intelligence practice of tracking where venture capital — especially seed and pre-seed — allocates capital, categorized by segment, as the cheapest and smartest signal of the next big thing two to three years out.

Housed inside RevOps and increasingly run by AI agents, the function maintains a segmented, monthly-reported map of venture flows. It reveals what to replicate, what to acquire early, and where competition will emerge; seed funding is treated as market proof of product-market fit, not hypothesis.

### Build It Yourself (Vibe Coding) (46:56)

**Definition:** An AI-native operating default: when you have a real need you'd pay for but can't find the right tool (or it's too expensive), build it yourself with AI coding tools rather than waiting on a vendor.

Alex, a non-technical sales lifer, built a secure, polished sales-prep tool in five evenings for $200 using Cursor. Scaled across a company via hackathons and universal AI access, this collapses the old technical moat and lets non-engineers ship the tools they best understand.


## Quotes

_Speakers inferred from an undiarized transcript — verify before attributing._

> "The funny thing is that even right now, we're going through the fifth pivot in our business model, so it has continued changing."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (01:32)

> "The most important things we kept a look on for that period were who controls the client, who controls the revenue, and who controls the margin. Depending on how that changed, we adapted our GTM."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (04:23)

> "This early phase looks very difficult, because you struggle in every meeting just to explain what you're trying to sell. At the same time it's probably the easiest time in your business — competition is the lowest and your margin is the highest, because clients don't have a clue what a fair price is."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (05:13)

> "If right now you're in this golden era, this is the starting point of the future commoditization."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (15:51)

> "Product excellence begins to be just a hygiene layer of your sales."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (20:45)

> "You have to replace successful account executives, you have to replace successful people, just because very soon you'll need something absolutely different."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (21:31)

> "We have to raise the floor of the team, raise the floor of the type of customers we bring on, and raise the floor of what's acceptable at this company."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 71 (22:52)

> "Even if you think you shouldn't be aware of the regulator — well, you should, because the regulator thinks about you."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (28:28)

> "Just follow the VCs. Look at where they're putting their capital, and follow the funds focused on the seed and pre-seed stage — they give you clear visibility on what's going to be the next big thing."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (37:11)

> "The smartest money on the market is VC money. It's the cheapest signal you can get as a revenue leader — it almost costs you nothing, and it gives you clear visibility on the next big thing in two or three years."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (39:20)

> "You may have inspired a new part of our own offering. I've been doing RevOps for over a decade and never thought about using that as a signal — it's staring you right in the face."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 71 (41:26)

> "I had a strong need I was ready to pay for, but I didn't have the right solution. So I started to vibe-code it myself, and within five evenings I built a product that works perfectly. I spent 200 bucks using Cursor."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (46:56)

> "If you need something, first try to find whether somebody already built it. If it's too expensive, or you simply can't find it at all, build it by yourself — build it by your own hands."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (48:34)

> "If a person can now do 10x the production, that doesn't mean you need to fire 90% of the workforce. It means now you can just 10x what you're producing."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 71 (53:10)

> "This is the second most important technology that ever existed. The first was the idea of taking something into your hand; the second is AI."
>
> — Alex Loktev, The LeanScale Podcast Ep. 71 (54:49)

> "The second things start feeling easy, expect commoditization to happen. Be ready to build that next horizon of product and growth so you can keep the momentum moving."
>
> — Anthony Enrico, The LeanScale Podcast Ep. 71 (57:14)


## Practical advice by role

### Founders

- Map where each of your products sits on the educational curve and harvest the high-margin early phase deliberately — but treat market education as the countdown to commoditization, not a permanent moat.
- When business hits the 'golden era,' start building the next high-margin product immediately; your current core is about to become a low-margin entry wedge.
- Run a fractal portfolio: use the commoditizing core as a customer wedge and continuously replicate or acquire higher-margin products still early on the curve.
- Allocate real budget to a GTM R&D function that tracks venture flows and startups; in a fast-moving market it's non-optional and now nearly free with AI agents.

### Revenue Executives

- Instrument the business around 'who controls the client, the revenue, and the margin' — and treat a change in the answer as a whole-GTM trigger (team, brand, materials, motion).
- Watch for control migrating to intermediaries and then regulators; a channel or regulatory shift can quietly become 80% of revenue and demands a different seller profile.
- Rebuild the team at each phase, including replacing people succeeding today who can't retool — and raise the floor across team, customers, and standards.
- Frame AI as abundance: if output goes 10x, produce 10x more and hire more people who can operate at that level, rather than cutting headcount.

### RevOps Leaders

- Own GTM R&D: maintain a segmented, regularly reported map of where seed and pre-seed capital is flowing in your industry as a two-to-three-year early-warning system.
- Use VC-flow intelligence to surface acquisition targets and emerging competitors before they show up in your pipeline.
- Orchestrate agents to do the trend-watching cheaply — replace the manual Crunchbase scan with an agent that reports the shifts, keeping the function the same.
- Make your first hires build the intelligence muscle; Alex's very first hire was a RevOps lead precisely because reading the market is a revenue-ops job.

### Sales Leaders

- Match the seller profile to the phase: technology enthusiasts to educate, practical AEs to scale, and relationship-led reps for commodity and pricing wars where product excellence is only hygiene.
- Rewrite sales materials, messaging, and highlights for each phase rather than carrying old positioning into a more educated, more competitive market.
- Arm the whole team with AI — Alex requires reps to use a tone-of-voice adapter for first-touch global outreach and gives everyone AI tooling to build their own aids.


## AI takeaways

**Thesis:** AI is the second tool in the human hand — a productivity and abundance multiplier, not a headcount-reduction lever. The AI-native response is to arm everyone (technical or not) with agents, build what you can't affordably buy, and reinvest 10x output into 10x production and more hiring.

- **Build, don't wait** — When a needed tool doesn't exist or is too expensive, vibe-code it. Alex built a secure, polished sales-prep tool in five evenings for $200 using Cursor despite being non-technical.
- **Democratize AI across the org** — P2P runs company-wide hackathons where more than half of participants are non-technical (finance, legal, sales); LeanScale gave everyone Claude Code accounts and ran two-hour personal onboarding sessions. Non-technical builders often ship the highest-leverage tools.
- **Agents for market intelligence** — GTM R&D — tracking VC flows and startups on Crunchbase — is now orchestrated by agents rather than manual scanning, keeping the function while collapsing its cost to near zero.
- **AI-native GTM stack** — Run an internal LLM, use Clay and Apollo, and test AI-native CRMs — while accepting CRM migration is the hardest switch even when a better option exists.
- **Abundance, not layoffs** — If output goes 10x, produce 10x more and hire more people who can operate at that level. There's no limit to human curiosity or an organization's appetite to create — commoditized moats fall and the best ideas prevail.

**Agent & automation ideas**

- A GTM-R&D agent that monitors Crunchbase and VC seed/pre-seed rounds, categorizes them by segment, and reports monthly on shifting market trends, acquisition targets, and emerging competitors.
- A pre-call challenger agent that interrogates reps with the tough questions a prospect might ask, so they walk in prepared rather than losing credibility live.
- A tone-of-voice adapter that rewrites a rep's first-touch outreach for the target region and buyer, enforced by default for SDR and first-contact communication.


## Operations takeaways

### Revenue operations

- **RevOps owns GTM R&D.** Alex's first hire was a RevOps lead, and a core RevOps mandate is scanning the market and overviewing trends — market intelligence belongs in revenue ops.
- **VC flow is the cheapest signal.** Track where seed/pre-seed capital lands, categorized by segment, for two-to-three-year visibility into the next big thing, acquisition targets, and future competition.
- **Instrument around control.** Watch who controls the client, revenue, and margin; a change in the answer is the real trigger to rebuild the GTM.
- **Read the awareness ratio.** Measure the share of first calls where buyers already understand the technology; crossing ~50% is a signal to accelerate the motion before the market shifts.
- **Agent-orchestrate the ops.** Replace manual trend-watching with agents; the function stays the same while cost collapses to near zero.


## Metrics mentioned

| Value | Metric | Context |
| --- | --- | --- |
| $500M → $10B | P2P.org assets scaled | Assets under management scaled roughly 20x over four years while the GTM was rebuilt four times. |
| 130+ | Institutional clients | The worldwide network of institutional clients P2P manages staked assets for. |
| 5 in 4 years | GTM pivots | The business model has changed four times in four years, with a fifth pivot underway. |
| 80% | Partner channel share of revenue | After control of the client shifted to intermediaries, the channel/partner motion became 80% of P2P's revenue. |
| 50% | Awareness threshold to pivot | When the proportion of first calls with buyers who already understood the technology hit 50%, it signaled the market was changing and the motion had to speed up. |
| ~200 | P2P headcount | Nearly 200 people, with an R&D team split between the main org and a smaller unit allocated specifically to the GTM/revenue function. |
| $200 · 5 evenings | Self-built tool cost/time | Alex vibe-coded a working, secure, polished sales-prep tool in five evenings for $200 using Cursor as a non-technical builder. |
| $4M → $40–45M · ~$500M exit | Emailage trajectory | Anthony's prior company, where the channel organically grew to 45% of revenue and set up the exit to LexisNexis. |
| -75% over 4 years | Emailage price erosion | The price the company could demand dropped about 75% over four years as competitors entered and the product commoditized. |
| 4 | Regional sales teams | Alex runs four regional sales teams, driving the requirement for a tone-of-voice adapter app for cross-region first-touch communication. |


## Entities mentioned

- **P2P.org** (company) — Alex's company; he is CRO of one of the largest institutional staking-infrastructure providers, managing $10B+ in staked assets for 130+ institutional clients and running an internal LLM as an AI-native firm. It grew from $500M to $10B while pivoting its GTM four times in four years (now a fifth). · https://leanscale-knowledge-hub.netlify.app/company/p2p-org/
- **Yandex** (company) — Where Alex spent roughly half his career — described as Russia's Google, Uber, Amazon, and Spotify combined — working in the digital-advertising business selling marketing tools and inventory, which shaped his view that the regulator ultimately controls advertising and B2B markets. · https://leanscale-knowledge-hub.netlify.app/company/yandex/
- **BlackRock** (company) — Cited as the archetype of the world's largest financial institutions now accepting staking products as a default part of their product portfolio — evidence of how far and fast P2P's market moved up the educational curve. · https://leanscale-knowledge-hub.netlify.app/company/blackrock/
- **Emailage** (company) — Anthony's prior company: he joined at $4M, scaled it to $40–45M, and exited to LexisNexis for roughly half a billion. His parallel story — the channel organically creeping up until it became 45% of revenue and set the stage for the acquisition. · https://leanscale-knowledge-hub.netlify.app/company/emailage/
- **LexisNexis Risk Solutions** (company) — Acquired Emailage for about half a billion dollars; Anthony's exit case that surfaced during the discussion of channel becoming the controlling revenue path. · https://leanscale-knowledge-hub.netlify.app/company/lexisnexis/
- **Alex Loktev** (person, guest) — CRO of P2P.org; scaled it from $500M to $10B in staked assets through five GTM pivots. Ex-Yandex ad-sales leader turned AI-native revenue operator. · https://leanscale-knowledge-hub.netlify.app/guest/alex-loktev/
- **Anthony Enrico** (person, host) — Co-founder of LeanScale and host of The LeanScale Podcast. · https://leanscale-knowledge-hub.netlify.app/guest/anthony-enrico/
- **Clay** (tool, GTM Data / Enrichment) — Named by Alex as an extremely good, one of the most useful sales-related tools in the market — part of P2P's stack of ready-made AI-native GTM solutions.
- **Apollo.io** (tool, Sales Intelligence / Engagement) — Named alongside Clay in P2P's sales stack; Alex is also testing AI-native CRMs, noting CRM migration is the hardest to switch even when a better option appears.
- **ChatGPT** (tool, AI Assistant) — The 'aha moment' tool: after its release, P2P built simple internal apps on it — including a required tone-of-voice adapter that reps use for first-touch global outreach.
- **Cursor** (tool, AI Dev Tool) — Alex — a non-technical sales lifer — used it to vibe-code a secure, polished sales-prep tool in five evenings for $200, the moment that shifted his whole paradigm on building versus buying.
- **Crunchbase** (tool, Company / Funding Data) — The startup/funding database P2P's RevOps team monitors (now via agents) to track where VC money flows and detect the next big thing early.
- **Claude Code** (tool, AI Dev Tool) — Referenced as 'cloud code'/'Claude license': Anthony plans to jump into it right after the call to build the VC-signal tool, and both companies bought company-wide licenses and ran onboarding so everyone can build their own tools.


## FAQ

**Q: What is the number one question a CRO should ask when the market keeps changing?**

A: Alex Loktev's master question is: who controls the client, who controls the revenue, and who controls the margin? At P2P.org, control moved from the company (educating a market that barely existed), to intermediaries like custodians, banks, and exchanges (forcing a pivot to channel sales, now 80% of revenue), to the regulator. Each change in the answer forced a full rebuild of product strategy, sales team, brand, and materials.

**Q: What is the 'Golden Era' trap in go-to-market?**

A: The Golden Era is the phase with strong demand, high margin, low competition, and finally-educated buyers — and it feels like earned success. The trap is treating it as a reward. It is actually the starting point of commoditization: VCs are funding the segment and enterprises are entering, so price pressure is coming. The moment business feels easy, you should already be building the next high-margin product.

**Q: Why does surviving GTM pivots mean replacing successful salespeople?**

A: Each phase of a maturing market needs a different seller — technology enthusiasts to educate the market, practical account executives to scale, then relationship-led reps for commodity and pricing wars where product excellence is only table stakes. The hardest part is that people succeeding in the current phase often can't retool for the next one, so you have to replace performers who are still closing deals but no longer fit what's needed.

**Q: How can you use venture capital investment as a market signal?**

A: Track where VC funds — especially at the seed and pre-seed stage — are allocating capital, categorized by segment in a regularly updated report. Because seed money flows when a startup first hits product-market fit, it gives near-free, two-to-three-year visibility into the next big thing, which products to replicate or acquire, and where competition will emerge. Even a failed individual investment still validates the segment. It's the smartest and cheapest signal available to a revenue leader.

**Q: Where should market-intelligence / GTM R&D sit in an org?**

A: Alex places it under RevOps. His very first hire was a RevOps lead, and a core part of the RevOps mandate is scanning startups and VC flows to overview trends. In a fast-moving market you should allocate budget to this R&D function; it is now nearly free to run because AI agents can do the trend-watching that a person used to do manually on Crunchbase.

**Q: What does it mean to be an 'AI-native' revenue organization?**

A: For P2P.org it means running an internal LLM, using tools like Clay and Apollo, testing AI-native CRMs, requiring reps to use AI aids like a tone-of-voice adapter, and running company-wide hackathons where over half the participants are non-technical. The core mindset: if you need a tool, first check whether it exists; if it's too expensive or doesn't exist, build it yourself with AI — Alex built a working sales-prep tool in five evenings for $200 using Cursor.

**Q: Does AI reduce the size of a GTM or revenue team?**

A: Both Alex and Anthony argue no. If a person can now produce 10x, the right response is to produce 10x more and hire more people who can operate at that level, not to fire 90% of the team. There's no ceiling on human curiosity or an organization's appetite to create; AI lowers the cost of building niche products and lets the best ideas win, which grows output and headcount rather than cutting it.

**Q: How do you build a product portfolio in a commoditizing market?**

A: Run a fractal portfolio. Keep a core product that generates thinning margin but stays a sticky entry wedge for customers, and continuously find smaller players sitting earlier on the educational curve with higher margins — products you replicate in-house or acquire. Repeating this at every level thickens each customer relationship and keeps blended margin up as any single product commoditizes.


## Timeline

- **00:00** — Meet Alex Loktev: scaling P2P.org from $500M to $10B
- **01:32** — Five business-model pivots in four years
- **04:23** — Who controls the client, the revenue, and the margin
- **05:13** — The educational curve: hardest to sell, highest margin
- **06:59** — Reading the shift and hiring a new sales profile
- **10:30** — The signals: 50% awareness and who controls the client
- **11:35** — When intermediaries take over: pivot to channel sales
- **13:25** — Anthony's Emailage parallel: the channel signal
- **14:54** — The Golden Era trap and coming commoditization
- **19:04** — The hardest part: replacing successful people
- **22:14** — Raising the floor (The Science of Scaling)
- **24:21** — When the regulator controls the client
- **31:45** — The process: product strategy at the core
- **32:30** — The fractal product portfolio
- **35:37** — Where the awareness comes from: GTM R&D
- **37:11** — Follow the VC money as a market signal
- **41:26** — Putting market intelligence under RevOps
- **43:04** — AI in the GTM: tone-of-voice apps, Clay, Apollo
- **46:05** — Vibe-coding his own sales-prep tool in five evenings
- **49:26** — LeanScale's parallel: Claude Code for everyone
- **52:22** — Abundance, not layoffs: AI and human curiosity
- **54:49** — AI as the second most important technology ever
- **56:30** — Closing reflections


## Related episodes

- **Ep. 95: Why AI Means More RevOps Hires, Not Fewer** (Jimmy O'Halloran) — The same abundance thesis Alex and Anthony land on — a productivity gain should grow the team and its output, not shrink headcount. · https://leanscale-knowledge-hub.netlify.app/podcast/jimmy-ohalloran-new-relic-revops-consumption-revenue/
- **Ep. 85: Why AI + GTM Engineers Can't Replace RevOps** (Tessa Whittaker) — Complements Alex's build-your-own-tools story: AI and agents execute judgment but don't replace the operator strategy behind the GTM. · https://leanscale-knowledge-hub.netlify.app/podcast/tessa-whittaker-ai-gtm-engineers-revops/
- **Ep. 88: Why AI Won't Close Your Biggest Deals** (Michael Kiernan) — A CRO's view on AI inside the revenue motion — pairs with Alex's human-curiosity-and-relationships framing of AI. · https://leanscale-knowledge-hub.netlify.app/podcast/michael-kiernan-nextdoor-ai-wont-close-deals/
- **Ep. 91: Why Outcome-Based Pricing Is a Trap for Most AI Companies** (Roee Hartuv) — Pricing and commoditization counterpart to Alex's educational-curve and Golden Era margin discussion. · https://leanscale-knowledge-hub.netlify.app/podcast/roee-hartuv-outcome-based-pricing-trap/


## Full transcript

_Machine-transcribed and not diarized; speaker attribution is inferred._  
_Transcript only, as a separate file: https://leanscale-knowledge-hub.netlify.app/podcast/alex-loktev-cro-playbook-reinvention/transcript.md_

### 00:00 — Meet Alex Loktev: scaling P2P.org from $500M to $10B

**[0:00]** Today, I'm sitting with Alexander Lakhdev, the CRO at p2p.org, one of the largest institutional staking infrastructure providers. They manage over 10 billion instaked assets for 130-plus institutional clients. But what makes this conversation unique is the pace of change Alex operates in. He told me his business model has changed 4 times in just 4 years. He went from Yandex, Russia's version of Google, Amazon, and Uber combined to building a revenue function in an industry that barely existed when he started. We're going to get into how you build GTM when the market reinvents itself every 6 months and what it's like to build

**[0:43]** your own AI tools as a CRO. Thank you, Anthony. Great to be here. Thanks for having me. That gets sold out. Thank you for being here. I'm stoked to dive into this because I think this is something that a lot of the CROs that we're working with are challenged with. We're working with B2B tech companies where things are changing every day, especially now with so much of the infrastructure changing with AI capabilities. I think one thing that really, really stuck out to me is you told me your business model has changed 4 times in 4 years. How do you even approach building a GTM function from scratch with that level of agility and velocity of pivoting?

### 01:32 — Five business-model pivots in four years

**[1:32]** Yeah, sure. We spoke about that before we started recording. The funny thing is that even right now, we're going through the fifth pivot in our business model, so it has continued changing. Let me give you a short context so our audience will get a better understanding of what we're doing for. For that lens, then we'll follow to the logic of these GTM changes and how we are managing these pivots. In very simple words, our business model based on operating the transactions in the blockchain ecosystem. Every time when any transaction happening in the ecosystem, someone must verify its accuracy, validate this transaction and

**[2:30]** add it to the block and then add this block into the chain. That's how the block of chain works. We are that someone. Our business based on earning a very fractional commission of each action, of each transaction we are validating, but we perform millions of these validations every day. To scale the volume of our operations, we can validate based on the network rules. We must increase our skin in the game. It means we must lock up a capital. That's why our business model is to attract capital from asset holders to validate transactions on their behalf and return these earned commissions to them, minus our performance fee. That's

**[3:26]** simply our business model. Following this model within the last four years, we came from $500 million of dollars to $10 billion, which we have mentioned today. We expand significantly our worldwide network of institutional clients, but through that process, what was the most important thing and what was the source of all these changes that we caused from the moment when four years ago, our sales force, we have to educate the market, explain to the people what we're doing for, explain to customers the basic value of our products to a current point where worldwide largest financial institutions, the BlackRock, already

### 04:23 — Who controls the client, the revenue, and the margin

**[4:23]** accept these products as a default part of their product portfolio. We run through this educational curve very fast, and the pace of moving through this curve was incredible. I think that what leads all these changes, because it depends on where we are in this curve. Your GTM have to be very, very different, and your business model have to be different. The most important things on which we keep a look on for that period were who controls the client, who controls the revenue, and who controls the margin. It depends on that changes we adopted our GTM. In this case, were you realizing or recognizing

### 05:13 — The educational curve: hardest to sell, highest margin

**[5:13]** new opportunities that you wanted to capture or pivoting to get better product market fit, or were there foundational changes happening in the market that you had to keep up with that forced these GTM changes? I will say both. Let me give you an example. In the early beginning, when we just started to educate the market, and I think it works absolutely same on any industry, wherever you are working on. This early phase, on one side, looks very difficult, because you have to struggle literally on every meeting you are running for with your customer. You are struggling with explaining what literally

**[6:10]** you are trying to sell, what is the value of your product. At the same time, it's like this is probably the easiest time in your business where your level of competition is the lowest. You are just competing with the same level of startups, where your margin is the highest, because clients don't have a clue. What is the fair price? There is no pressure on the price at all. I would say that at the same time, moving ahead, the more clients know about the product failure, the more they are starting to ask for the more competitors coming to joining this game, the closer you come into the next phase where

### 06:59 — Reading the shift and hiring a new sales profile

**[6:59]** competition will be increased, where price pressure will release, and it means that in one hand, we pushed that process of change by ourselves, just organically educating the market. We knew what we would do, and looking back to this time period, I remember that six months after, just for the context, when I joined the company, I was second higher on the sales side, so it was literally like the market just started to exist. I remember that six months after we started to build the GTM, when we made the first institutional customer development sessions, closed literally the first deals with institutions, we started

**[7:54]** to prepare for the next phase. We started to hire a new type of the people to our sales team. In the beginning, in the initial phase, we hired more technical people and technology enthusiasts. That was the main approach for our recruitment team. We tried to hire somebody who knows how everything works and who will get a passion about technology, who will be able to share this passion with our customers, but half a year after, we realized that, "All right, we're coming to the point very soon where these customers will know how that works, and they will start to add this type of the product to their product portfolio they're

**[8:50]** using for, so it will be needed." A completely different profile of the salespeople, of account executives will be needed to build a different type of approach. We started to plan replacement or reducation for Salesforce, so we started to prepare another type of sales materials with the different workings, with the different highlights. We started to move from this early era of people who are just passionate and enthusiastic about technology, to early adopters, to first customers who already get a clue how that works and who started to see the value of this product. Answering to your question, yes, from one side we were pushed by the market

**[9:47]** just because markets grew up rapidly, but at the same time we were the people, we were the company who made this push, who rolled this wheel forward. What type of market signals were you taking a look at that gave you the confidence that, "Okay, it's time to shift from this technical enthusiast profile, knowing we're going to have to invest heavily in education to knowing that the market was more educated and prepared for a more scaled GTM approach?" Was it listening to sales calls? Was it seeing the content that those companies are putting out? What gave you that confidence to start shifting the motion?

### 10:30 — The signals: 50% awareness and who controls the client

**[10:30]** Yeah, so it was two particular marks. First, we analyzed sales calls and checked a percentage of the first initial calls with the stakeholders. We made a calculation of how many of them, what is the proportion of people and how this proportion changes within a time of people who have no idea how that works versus people who already heard something. And at the moment when this proportion just hit a 50% bar, we realized that, "All right, all right, things speed it up. We have to speed ourselves up either because very soon market will be changed." So that was the first thing, just a percentage of people who were aware about technology,

### 11:35 — When intermediaries take over: pivot to channel sales

**[11:35]** who were aware about the value. And the second, and second probably is the most important one. So until the current time, we were always extremely careful, extremely careful looking to who controls the client. If you ask me what is the main thing, what is the main changing factor, I will say that this is the main changing factor. Who controls the client, who owns the client. Because within, again, moving on this educational curve, the control shape changed and this was the main change factor which push our GTM change either. Like again, I'll give you an example. On the first days, we were the people who controls the client

**[12:34]** decision making process. Client just hold their assets, they have no idea how they can utilize that, how they can get a leverage of it. We came with the value and we control their decision making process. But closer to the end of the first year of our operations, another players, another segment of players joined this game. It were partners for ourselves looking forwards, custodians, banks, wallets, exchanges. So the new category of clients intermediaries came to the game and they started to provide a bigger value to the same clients and we realized that, all right, this is going to be a counterparty which will control these

### 13:25 — Anthony's Emailage parallel: the channel signal

**[13:25]** clients in the future. And we have to change our mind, change our product strategy, business strategy, GTM strategy, change everything and shifted it from direct access to an intermediary to a channel sales approach. That's super interesting. And I think before starting LeanScale, I was at a company called Emailage. I got there 4 million scaled to 40 to 45 and then we exited to Lexus Nexus for half a billion. And we had a similar realization, maybe when the company was around the 8 million mark, we started to see the percentage of our business organically creep up through

**[14:11]** the channel without really investing a lot of time in it. And as soon as we shifted resources and invested into the channel, it quickly became 45% of our revenue. And I know this isn't everybody's goal, but it also set the stage for the acquisition as well. So that was 100% a signal, like, hey, organically, I love the way you phrase it, who controls the client and who controls the experience. And as soon as we had that organic shift happening, we knew it was time, okay, let's go invest, double down. This is a channel that we have to press hard on. Yeah, exactly. Yeah, I think it's probably work same in many industries. I'm curious

### 14:54 — The Golden Era trap and coming commoditization

**[14:54]** how it works in your past because in between of this first phase where we directly controls the client and the third phase where intermediaries started to control them, it was the second one. And I call him that's a real gold golden era, when clients were already acknowledged, they get what they need. Intermediaries partners started to grow, but they still didn't get the full control. And large players, enterprise players, also they did, they started to move on to this market, but they just didn't get enough time to be prepared for that. And it was kind of a year when you've got extremely strong demand, high margin, still low competition.

**[15:51]** But also, probably, that's gonna be one of my advice for an audience for whom that relevant. Also when you're going through this golden era, golden age, at least that how it works in our case, you have to know that it will be ended very soon. And you have to recognize that, all right, if right now you're in this golden era, this is a starting point of the future commoditization. So that's when commoditization of your products starting on. Because it's a clear, strong signal for the enterprise, for competitions. VC started to put their money to this market segment. Very, very soon, the competition layer will be incredibly high

**[16:46]** and price pressure will come to the field. And you have to start preparing for the commoditization, which means you need to start to work on another product on which you will really get the money in the future. Because you wouldn't be able to get the same amount of, probably you will be able to get the same amount of revenue, but not the margin from this product, which is the core of your product portfolio today. And if that's the type of the market where partners and partnership channel would be the main source of revenue, in our case right now it's already hit 80% of our revenue. So if that's the case, it means that your current

**[17:33]** core product will be just an entry product in the future. And if you wouldn't be able to find the side products with a high margin, you'll just go from this market because revenue and margin will be commoditized. So that was the clear signal for ourselves. I think it takes a rare set of experience, vision and skills to recognize when that moment is happening because during that golden era, it's an exciting time, right? It's easy to close business. Everything seems to be clicking. It feels like, oh, we've earned this success and now it's time to go reap the rewards of it. But I love the way you frame it. As soon

**[18:19]** as things start getting easy, expect others to come and you better be working on the next thing or else. And I saw this at that company as well. The price that we were demanding dropped by about 75% over the course of a four year period. So we had a competition come in, we had people offering something similar. And in order to keep up, we had to keep bringing the price down. And then we had to have second wave of products coming out. But yeah, unless you've been through that and felt it and seen it, it's pretty tough to be that proactive, which I think is the reason why a lot of startups end up just dying.

### 19:04 — The hardest part: replacing successful people

**[19:04]** Well, probably it was. The hardest part was that one of the main factors of success when you're moving through that period is that you have to make a very tough decision of replacing team members again and rebuilding them because it starts with the team. So again, preparing from enthusiastic people, coming to more practical, account executive type of personalities. Then again, you have to rebuild the team approach because you have to prepare your team for commodity wars, pricing wars. You have to hire the people or educate your people. You have to hire those who get experience on this commodity type of the businesses

**[19:58]** because your business model, your sales and GTM practices shifting from product value to relationships value. So yet another factor of commoditization is that the largest players of the segment started to be able to give to your customer not just the same product, but same good product, same excellent product. The level of excellence is growing up. And then at some point you'll find a customer who will be able to just blindly choose any of top three, top five market players. And he'll be confident that he'll get more or less same good product from them. So you need to hire the people and rebuild a team with a relationship based approach. It's like

**[20:45]** a product excellency beginning to be just a hygiene layer of your sales. So you need to be more focused, more proactive on the service part, on relationships part and you need to hire the people who know how to move through that. And yeah, so that was always the hardest part of rebuilding the team at the right moment of time, because you're absolutely right. Again, coming back to this golden era, it's very hard to not just to praise yourself and get you know, a benefit so that time, but it's even harder to replace people who are successful, who are closing the deals, who are making the money. And if they're not by any reason

**[21:31]** able to change their approach to re-educate and be prepared for the next phase, you have to change them. So you have to replace successful account executives, you have to replace successful people just because very soon you'll be needed absolutely different. Even you'll be needed to people with a different mindset, you know, and with a very, very different experience. So yeah, that was the hardest part. And it still is the hardest part. It's always been the hardest part for me too, especially in that scenario where they are successful in the old context, but not prepared for the new. And I just finished Science of

### 22:14 — Raising the floor (The Science of Scaling)

**[22:14]** Scaling. I think it's a, I think it's a really good book for anyone who's kind of going through these foundational shifts. And one of the major sections is raising your floor. And you know, what is your team like? Not what potential do they have, because I think that ends up, you end up holding on to people longer than you should, but how is that person on their worst day? Just like a professional athlete, like the greats are amazing on their worst days, not showing flashes of excellence and then, you know, being average on Sundays. So I think as you're going through these phases and you're getting to that next level, understanding,

**[22:52]** Hey, we have to raise the floor of the team. We have to raise the floor of the type of customers we bring on. And we have to raise the floor of what's acceptable at this company. Um, it's a very difficult thing to do. And quickly you'll realize there's far too many people on the team who are not meeting the floor standard. That's going to be necessary to make it to that next stage. Um, and it's a challenge, especially in the CRO world. That's, that's one where you're going to have to cycle through this quite a few times. As you mentioned, you're on your fifth round right now. Yeah. Yeah. That's, yeah, that's true. And well,

**[23:29]** if we'll continue this logic and, um, kind of following where we are right now and what was the next phase after this come to decision, cause so on this commodity, but, uh, for history, we just rebuilt the GTM. We changed the business model. We came from direct type of the revenue when we just charged the client. So a revenue split first model, right? When you have to think about not how to sell your product, but how to help your partner to better sell your product to his customers. Uh, and it's kind of, um, pushed you to a rear of thinking about the revenue share first about the revenue for yourself. But then we probably came to

### 24:21 — When the regulator controls the client

**[24:21]** the most challenging to the most interesting path of this journey. And again, thinking about who's controlling the client. Uh, nowadays came to the point where regulator started to be this actor who's controlling the client. And interesting thing is that, you know, I came from, as you mentioned, I've come from Yandex, uh, Yandex aggregates multiple different businesses. It's kind of Google kind of Uber kind of Amazon kind of Spotify kind of everything. Uh, I was a part of, um, Google type of Yandex business. Uh, so I spent kind of like half of my professional career, uh, selling digital marketing tools, inventories. So I worked

**[25:16]** in the advertisement business, which is now a day, you'll think about that business is absolutely controlled by regulator. So look to in Europe, uh, when you're thinking about commercials, you're thinking about digital marketing. First thing you started to think about is, uh, how does it, your tool, your approach correlates with GDPR rules. And those players who adopts better to regulator requirements, they're winning the market. So Facebook, Instagram, uh, buy beats with the tick tock, they adopt better than anybody else in the world to regulator requirements. And they're getting profits on that same in many other industries. If you'll

**[26:06]** think who's really staying behind the sense, who's control, who controlling this market, who controls how this, uh, the clients, especially on the B to B segment, how clients making their decisions, it, uh, I mean, always would be regulator in some extents. So, and that point when you're, when we started to work with partners, when we started to be focused on the partners, that was a, uh, last shift in our GTM. When we recognize that, and when we seen the clear triggers and signals from the market that, you know, just, um, using your AI agent, which, uh, shares in use updates, uh, daily with you, the more you see a regulator

**[26:52]** name on the headline of this news, the more confident you have to be that very, very soon. And now it will be changed again. And again, we've made changes on our GTM. Again, we started to rebuild the sales team, uh, the people who know how to work with the government, uh, how to sell, uh, on these highly regulated, regulated by government in our case environment. We changed approach. We changed a brand style of the company. We changed the sales materials. We completely changed like everything related to the GTM. Again, following this logic of who controls the market, who controls the client, who make control on how decision-making

**[27:40]** on, on this market? Yeah. And that, that's a scary time when you need to start worrying about regulators and, and government and making sure that you're catering to those regulations as well. So that that's a, um, yeah, very mature GTM organization when you need to navigate those murky waters, I would say. I'd say that, uh, but if you remember this movie, um, um, the devil wears Prada. It was a beautiful, that was a beautiful phrase, uh, about how the fashion works. So she said that even if you don't give any shit about the fashion fashion, give it a shit about you. So it works. It works. Same. Even

**[28:28]** if you think that you're not, you shouldn't be aware about the regulator. Well, you should because regulator thinks about you. And that's what I see right now around the AI industry. Most of the folks thinks that regulator is not a part of the game, but it is already. And very soon it's going to be more and more and more regulated. And while my prediction is that, uh, this customer, um, this kind of startups who's building a customer products, B2C products, B2B, wherever else products could operate on the AI market. They have to be very, very, very cautious and careful with what's, you know, with what is the current

**[29:18]** regulator landscape is because there's going to be the main, uh, factor of adopting your GTM, adopting your product strategy. And if you will be the most adopted for the regulator requirements company in your segment, you will get the biggest, the largest profits. In your experience at P2P, have you started to get regulatory pressure? Is it at that stage where you need to be working at that level? We started to get signals, uh, like a year and a half ago. In that moment when this channel partner started to be the main one at the same time, you know, cause the, how it works, your partners, your channel

**[30:07]** partners, they're always, at least in our case, they're much larger than their kind of counterpart is. So every partner of us is bigger ecosystem player than we are. And they got, um, they're heavy weighted. They got more attention from regulator and when, and they got a larger gravity on the market, uh, because of this gravity, they consolidate capital, they consolidate power. And at some point regulator started to keep a look on them and started to work with them first. And in that moment, so it started to happen in our, um, in regards of our, uh, segment had started to be case like year and a half

**[30:57]** ago. And it was a clear signal for ourselves that, all right, very, very soon our markets, our market segment will be regulated. At some point, at some form, it will be regulated. And nowadays we come in very, very, very close, uh, to this point where the first regulation will became, I think we are one, two, probably three, uh, months of that. So yeah, we are, we are regulated. One thing I was hoping you could dive a little bit deeper on, and it sounds like you're going through this currently with your fifth iteration of the GTM infrastructure. What, what is the approach you take, the process you take, what areas of the business do you evaluate and

### 31:45 — The process: product strategy at the core

**[31:45]** how do you come to the conclusion of what needs to change? And then how do you execute it? Because I'm thinking when you have to look across the entire GTM lifecycle, the sales team, customer success team, the marketing, the messaging, the partnerships and the channels, how do you approach what needs to be changed and then make it a reality? Well, it started with the product, uh, but in, in the center, in the core of these decision making processes, always, um, product strategy. What are the products we are focusing on? And the framework we are using for, if I'll try to simplify how it works, I'll say that

### 32:30 — The fractal product portfolio

**[32:30]** that our core product in the center, uh, we generate less and less and less margin within 20 years, but it's still a significant part of our revenue. We're using it as an entry tool for the customer, uh, for the customers or for even customer segments. But we always, uh, we have to keep look around of us and see, all right, if we are working with a larger institutional players, uh, who is smaller, who is smaller than we are, who's like operating, you know, in the next layer after us, who's got the best profits, who's got the higher case margin, because it gives us clear signals on the products, which we have to either replicate

**[33:26]** by our own, uh, hands or as you mentioned, it's, um, an M&A market always. It gives us signals on the companies on the start tops, which you can acquire. So, and that works, you know, as a fractal, um, uh, as a fractal based decision where you have a bigger product with a higher revenue, less margin, then you got multiple smaller ones, which just staying behind in this educational curve and still keeps higher margin. Then you have even smaller ones which staying again way behind in the same curve. And you always can find these type of the new products, which would be relevant, which will be commodity the next five years.

**[34:12]** But right now they just staying in the early phase of this educational curve and you can replicate it and add to your portfolio. And that's how you're scaling the overall product portfolio of your organization. That's how you're increasing the thickness with your customer, because you're giving him more and more and more value in different directions. You're starting to operate with different departments of your team. Like in our case, when we started with the simple staking solution and right now we are working, we are providing to our customers and data services and infrastructural services, RPC services, taking services, different

**[34:51]** type of the yield services. So it's like huge, uh, portfolio of different products. Uh, so, but the logic is very simple. We always looking on the products, uh, which stays in the early phase of this educational curve. Yeah. And I think having that anticipation and knowing what's coming next and having the awareness, as you mentioned, even, Hey, we launched something new. Hey, five years, that's going to be commoditized. So let's not bank on it too much. Um, knowing that we're going to have to go through these phases of GTM for this product. I think just having that awareness, a lot of, a lot of teams just simply don't have it. How, uh,

### 35:37 — Where the awareness comes from: GTM R&D

**[35:37]** where did that come from? Did that come from experience that where you've seen a failure happen at that point? Um, did you have a mentor walk you through that? Where did you get this level of awareness of knowing that you're going to have to go through those phases? It's, it's came from organizational structure. It's came from organizational structure. When you build in your company budget, uh, and well, if you are a part of extremely fast moving, um, market segment, uh, there are several on the, uh, uh, on the current age in the market. So if you're a part of this fast moving market segment, you definitely

**[36:17]** have to allocate a part of your budget to a RNG function always. So you just have to get the people in the inside of your company whose day by day job is to look on the trends, look with the startups, uh, you shouldn't be part of investment or VC game, but you have to be in the context. So we, uh, got, um, two, uh, and P2P right now, um, in the P2P right now, there are like almost 200 folks working on. And we have a two parts of our R&D team split between the main organization organization and another part, smaller one allocated specifically to GTM function. So inside of our GTM revenue team, who's looking

### 37:11 — Follow the VC money as a market signal

**[37:11]** to the market trends, who's, uh, mentoring crunch base and looking, uh, to this first seed rounds, uh, like they're overviewing the trends where the VC money going on. It's one of the best signals you can find on the market. Just follow the VCs. You know, look, look to VCs where they're putting their capital and follow the VCs which are focusing on the seed stage, pre-seed stage. So they're giving you a clear visibility on what's going to be the next big thing. Yeah. That's an, that's an interesting way to think about it because obviously the stakes for them are the highest possible. And they're trying to get as much

**[37:51]** return as possible for their LPs and themselves. And that's an interesting role though. I, I have interviewed hundreds of CROs and we've worked with dozens and dozens of companies and I haven't seen somebody invest in GTM R&D. Can you, can you tell me more about sure that role, who it is, how'd you find them, what their experiences and the type of projects they're working on? Sure. All right. Well, when I was hired to the company, that was my first hire I've made. It was RevOps lead. Number one. RevOps lead. Number one. Okay. When I hired the first account executive, uh, I've heard RevOps lead. It was a single

**[38:35]** person due to that time. Then the team size, uh, RevOps team size increased and a very large part of RevOps team, uh, job was to keep a look on the market and overview the trends. It's very, it's an extremely cheap right now. It's even cheaper with AI agents. You don't need, yeah. So you need a person who will orchestrate agents within your organization. So you don't need any more somebody who will manually, um, look to the crunch base day by day, but the function is same. So it's, it's very cheap and it gives you the best level of understanding where the trends going on because the smartest money on the market

**[39:20]** are VC money. And while you're right, so PC trying to get the highest upside, but yeah. Uh, even if some particular VC fund fails with a particular investment, it still gives you clear visibility on the segment. So you don't need to be, you don't need to follow, you know, the exact company, exact startup they're investing for. You have to look on this segment. So we have a spreadsheet where we categorize in the investments of the startups. Uh, and we categorizing them by the segments and I have like monthly based reports, which represents clearly like with the how within the last almost four years, the market trends

**[40:10]** changing on within our industry. And when we see that VC started to invest in some new type of the startups in our industry, it gives us a signal that all right, that's going to be the next big thing. And it's the cheapest, cheapest signal you can, uh, you can get as a revenue leader. It almost cost you again today. It's almost cost you nothing. And it gives you a clear visibility on what are going to be the next big thing in two and three years. What, which product you have to replicate probably which company you have to acquire in the early stage. If you've got an

**[40:44]** expertise, what you can build by your own hands because the fact that VC started to allocate their capital to the startups means that first startups, a raise in the money could hit a market fit because VC started to put this money, especially seed and a type of the capital in the moment when these startups hitting the market feet first time and they're ready to scale. So it's not even more hypothesis there. It's a, it is a market proof. That is so interesting. And you put this under your rev ops org. Yeah. So your rev ops org is responsible for this intelligence. Yeah.

### 41:26 — Putting market intelligence under RevOps

**[41:26]** You may have inspired a new, uh, part of our own offering and product. So I appreciate you sharing that because I've been doing rev ops for over a decade and never thought about using that as a signal. It's like staring at you right in the face, but I've never really used it that way, not in the manner that you're talking about it. And especially thinking about, Hey, what are potential acquisition targets we might need to make and where's potential competition bubbling up as well? I think that's, that's a phenomenal way of, of thinking about that. Yeah. And, and that's almost free knowledge. The, yeah, the cheapest data insights you can get

**[42:13]** right now. Yeah. Yeah. I'm going to be hopping in a cloud code right after this call and just setting it up for ourselves so we can start taking a look. All right.

**[42:24]** Exactly. We'll give you some equity stake and make it worth your while. Um, on, on that note, I think, I think that's an interesting application of AI on the research and intelligence component. Um, what else have you been seeing? What are some applications of AI that have been really, really effective for your GTM work? Um, because there's so much that's changing right now and there, there's so many new ways you can approach things right now, especially I feel like this last quarter was just absolutely game changer with the new models, the new, we deployed open claw fully internally.

### 43:04 — AI in the GTM: tone-of-voice apps, Clay, Apollo

**[43:04]** I mean, every day it feels like there's some new foundational change, but specifically, where are you seeing AI being effective for you? Yeah, sure. Well, uh, I may say that as a whole organization and as a revenue function of, uh, the P2P, we are AI native firm. So we, uh, run an LLM internally for our own needs, uh, but specifically on the GTM function.

**[43:38]** But when the AI aha moment just happened when two and a half years ago, when the chat GPG thought version was released, we started to use it in a very simple way in a very simple format. Like for instance, we've built an apps, uh, which helps our, uh, sales reps to adopt their tone of voice operating globally. I have four regional sales teams. And even if you're kind of sitting in New York and your native speaker, but you have to interact with the customer from Bay Area, you better, you better to adopt your tone of voice, right? And it started to be a strict requirement for everybody who's working in the sales team. So they, by default,

**[44:28]** when they're communicating with the customer, especially the first time, and they have to just, you know, uh, broke that broken eyes, uh, especially for SDR function, uh, they were, and they are still obliged to use this tone of voice adapter app, but that was a simple one. So right now, uh, we are using a couple of ready to make solutions like clay. It's an extremely good example of, uh, one of the most useful, uh, sales related tools in the market. Apollo, of course, we are testing, uh, a couple of, uh, AI native CRMs, but with CRM it's still much harder to make immigration, uh, from one to another one.

**[45:19]** Even if the new one would be better, uh, but what was the pivoting moment for myself? And it just happened very recently, uh, like a month ago, I've tried to find on the market, uh, some tools solution, which will help on my sales reps to prepare better for sales calls. You know how that works usually, uh, you know, as a sales rep, you're failing your call, not because you kind of don't know nothing, uh, something, but because your client asking a tough question and getting this feeling that you're not prepared for this question. So you're losing your trustability, your credibility immediately.

### 46:05 — Vibe-coding his own sales-prep tool in five evenings

**[46:05]** And I tried to find some tool which will help us to prepare for these tough calls, you know, not just to, um, go through the typical sales pitch, not just, um, practice sales pitch, but something which will help us to, which will help me to challenge sales reps before, you know, in advance before they go to the sales calls. And I didn't, I simply didn't. So I've tried a couple different ones. Maybe I doesn't phone, but nevertheless, I came to the point that, all right, I have a strong need for which I'm ready to pay, but I don't have a right solution. And I've started to wipe coat that by myself. I, I'm not a technician person.

**[46:56]** I'm a sales, I spent all my career on sales. I have practiced to wipe coding for the years, but still I'm not a technician person. And within the next five evenings, I built a product which works perfectly, looks great. UI is excellent. Your X is amazing. And it's fully secure and it's completely solved my problem. And I just spent, spent 200 bags using cursor and getting five evenings. And that was complete shift of the whole paradigm, you know, of thinking that, all right, right. Nowadays, if I need something, I just can, you know, build it by my own hand. That was probably the source of this, you know, SaaS apocalypse on the market,

**[47:51]** on the stock market, which we've seen just recently, but that's where we are. And that's what we have to accept as managers. And right now, literally on these particular days, we are running AI hackathon inside of the company. And things which inspire me, that I look into a split of participants, I see that more than a half of the people who participate in this hackathon are not technician. There are faults from financial team, you know, from finance, from legal, my fault from the sales team, everybody coming with the ideas, with the solutions, which they came to build on. So answering the question, what we are using for

**[48:34]** mainly right now, I will say that that is the main kind of approach we are implementing in the company in this mindset that, all right, if you need something first, try to find probably somebody already build it. If you find it too expensive, or you simply doesn't find it at all, build it by yourself, build it by your own hands. So we just chased a cloud called license for the whole company for everybody who's working in the organization. We are implementing educational program again for everybody, because it's obvious how useful it is for technical part of the firm. But it's even probably more useful, you get the higher leverage for non-technical.

### 49:26 — LeanScale's parallel: Claude Code for everyone

**[49:26]** We've absolutely seen the same thing. December of last year, we had our first AI hackathon. And after that, it was the moment we made the same decision. Everybody at LeanScale is getting a max account on cloud code. And we sat down, our head of education sat down and did a personal two hour session with every single person in the company, where he, hey, we're putting VS code on your computer, get it connected to your API key this way, I'm going to run you through some tests so you can see the type of things that you can build. Let's get you connected to our GitHub repo. I'm going to make sure you know exactly what to do and how to use it.

**[50:11]** And the results we have seen have been outstanding. The things that people in the company are building blowing me away and saying, we have a mix. We have half the company is more of like project manager consultant type of profile. The other half is engineering. Ironically, we're getting more tools, platforms, things that our customers are using from the consulting side than even the engineering side. Because I think everyone over here is just so excited. It's like the first time they've been able to build something without being held back. And they also really, really understand

**[50:51]** the use cases and the problems that need to be solved. And now that there's not this barrier of technical development, it's incredible to see what people can build. Yeah, absolutely. They're not afraid that something wouldn't work. They don't know that something is impossible to build on. So they just go straight to the point and trying to build it. And accidentally they're building it. Yeah, that's an incredible level of changes. And even in some things which often are hidden under the surface of your operations, like how people interact with the documents,

**[51:35]** how people interact with the spreadsheets. When you're implementing this educational progress, when you align in all of your organization, and when you're as a manager, keeping everybody to some basic bar of AI knowledge, you see that everything just started to move smoother, faster, leaner. Yeah, and I think I don't know where it's going to go. But I think we have to just keep staying vigilant and staying on top of it and making sure our team's enabled and leveraging. And I think that's the most anybody can do right now. But I'm excited. I'm excited because I think

### 52:22 — Abundance, not layoffs: AI and human curiosity

**[52:22]** I think there are arbitrary and artificial moats that were built around these companies before, where now that those don't exist, really the best ideas can prevail. We can get more niche with our products as well, because it's not so expensive to build 10 different versions of something. Now, we can spin it up quickly and we can solve even more specific problems. And I think a lot of people are worried, "Oh, AI is going to reduce workforce and reduce..." I don't think so. I think there's no limit to human curiosity. And I don't think there's a limit to the amount of production an organization wants to create. If a person can now do 10x the

**[53:10]** production, then that doesn't mean you need to fire 90% of the workforce. It means now you can just 10x what you're producing. And then why not hire even more people if you can produce at that level consistently? So I think we're going to enter into an age of just remarkable abundance and knowledge work, where I don't think we're even prepared. One of the things I compared to is, if you were to ask somebody pre-industrial revolution why you would need a factory to create millions of articles of clothing, that wouldn't even make sense to them. But then looking at the buying habits of society now, of course we need that level of production.

**[53:53]** So we still can't even keep up with our insatiability of consumption. So I don't think it's going to reduce anything. I just think there's going to be massive abundance and knowledge work. I agree. I will even raise the bar even higher for the changes, because I believe that really nobody right now understands where we are heading on. I don't know what's your favorite movie. Mine favorite is Odyssey by Stanley Kubrick. You watch this one. Stanley used a very simple and simply great analogy between this moment when the first human, the monkey, took the first time born under the hand and get a leverage to the muscle power where we

### 54:49 — AI as the second most important technology ever

**[54:49]** came from that point as a humanity. These changes are insane. We are here in this point. So the difference between the human until we get this muscle leverage and right now it's absolutely incredible. I believe it wouldn't be possible to find a monkey which will be able to predict where we're heading on due to that days. And right now we are getting a chance to be in the days when humanity getting a leverage to bring power to intelligence. So that's why from my end I truly believe that this is the second most important technology ever exists. So first was this idea of taking something to your hand. And second is AI. And that's why the difference on

**[55:44]** humanity from that point when we already almost invent an AI, when we'll invent an AGI, it just will boost humanity so far away that nobody can imagine where we will be. It would be absolutely different type of society, humanity, the people, but it definitely will be reflected in the growth, not in the dropping and losing the value. So yeah, that's insane. It's just absolutely insane to get a luck of being a part of this journey, this moment, and drive.

### 56:30 — Closing reflections

**[56:30]** I know. We're very lucky to be working really at the tip of the spear of new technologies, new approaches, new things, and then being surrounded by people that have that level of optimism and creativity. I think it's a very, very special place to be. Well, Alex, this has been fantastic. I can't thank you enough. It's very, very impressive what you've built and what you've done at P2P, going through five different GTM evolutions and some of them probably revolutions of what you're doing. I really appreciate you sharing the framework too of higher educating the market, understanding

**[57:14]** the signals that start to creep up when it's time to make those changes. I think it's something that a lot of people lack the awareness of knowing that that golden age isn't going to last forever. The second you start feeling that golden age, the second things start feeling easy, expect commoditization to happen. Be ready to build that next horizon of product and growth so that way you can keep the momentum moving. I also really appreciate all the practical use cases of AI that you are using as a CRO and giving to your team and empowering your team to leverage

**[57:50]** cloud code, build their own applications, build their own tools so that way they can be as productive as possible. Alex, thank you so much. I appreciate it. I can't wait to see what you and P2P do in the future. Thank you. Thank you Anthony for having me. That was that was a great absolutely powerful session. Absolutely happy to chat with you. Wish you best in your journey. Thank you. Thank you.


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