Best of LinkedIn: Go-to-Market CW 30/ 31

00:00:00: provided by Thomas Allgaier and Frannis, based on the most relevant LinkedIn posts about GoToMarket in calendar weeks thirty-and-thirty one.

00:00:09: Freeness is a B to B market research partner helping ICT and tech providers identify niche channel partners.

00:00:15: by compressing the full journey from identification to qualified for his meeting into four or five weeks you find more info description.

00:00:25: so welcome this deep dive.

00:00:27: today we are looking at the absolute top go-to market trends that are just sweeping across LinkedIn right now.

00:00:33: Yeah, and look we are moving entirely away from that fluffy theory today where you're getting into hard execution.

00:00:38: Exactly imagine paying four hundred thousand dollars a year for a top tier engineer And their very first order of business is completely forbidding your brand new AI From sending a single email.

00:00:48: Right

00:00:48: which sounds crazy but it's happening.

00:00:50: We are going to pull apart the actual mechanics Of what Is working based directly on The feed from operators who Are actually in the trenches.

00:00:56: Yet

00:00:56: no high level fluff Today

00:00:58: None.

00:00:58: We are looking at the architecture, talent and AI agents And well... The underlying data layers you absolutely need to understand to compete right

00:01:07: now.

00:01:07: Okay let's unpack this because if we're moving from isolated campaigns To interconnected systems You have build the architecture first.

00:01:15: That brings us to what is probably most misunderstood role in market Right Now Which Is the GTM Engineer?

00:01:20: Oh, a hundred percent.

00:01:21: Because before you can run complex plays someone has to lay the plumbing.

00:01:25: The center of gravity has totally shifted from just running campaigns To building actual systems And the order of operations.

00:01:31: here is where so many founders are quietly bleeding cash.

00:01:36: Mateo Flop pointed out a really fundamental fatal flaw in how teams build outbound emotions.

00:01:42: Let me guess, they just hire someone to make calls?

00:01:44: Exactly!

00:01:45: A founder decides that they need pipelines so their default reflex is to just hire a sales development rep.

00:01:50: Right because the assumption is an SDR equals instant phone calls and emails.

00:01:55: But honestly it's like hiring pilot before you've actually built the airplane.

00:02:00: You're basically paying someone to sit on the Carmack and read manuals.

00:02:04: That is a perfect way to look at it because this system doesn't exist yet, right?

00:02:08: So that new SDR spends their first three months desperately trying to build infrastructure Which

00:02:13: they aren't trained for.

00:02:14: no not all.

00:02:15: They are trying to set up scraping tools verify domains And you know stitched together sequences.

00:02:21: there aren't selling acting as a junior completely unqualified systems architect.

00:02:27: And then what happens?

00:02:28: They burn out

00:02:29: exactly eventually their pipeline is zero they burnout, they churn and the founder has to start all over again.

00:02:35: Mateo says you must hire the GTM engineer first to build the ICP model The signal tracking an all-the automation.

00:02:42: so when the SDR finally arrives they step into a machine that Is already warm and generating signals.

00:02:47: yes Exactly

00:02:49: but how do you actually higher?

00:02:50: for that?

00:02:50: I mean, Petra Hagell noted that companies are failing right out of the gate at the job description stage.

00:02:55: Yeah they're screening for wrong things entirely

00:02:58: Right!

00:02:59: They screened for tool fluency... ...they want to know if a candidate can like click around in clay or NNN or HubSpot.

00:03:07: But tool knowledge is the shallowest layer of their jobs.

00:03:12: Half today's tech stack will be obsolete in eighteen months anyway Which

00:03:15: why you need to screen judgment, not just software familiarity.

00:03:19: Heijal suggests this brilliant interview tactic.

00:03:22: she says don't just do a neat resume walkthrough...

00:03:25: Oh those are the worst!

00:03:26: Right instead present the candidate with.

00:03:31: Give them a scenario where an automation is touching live customer data and one wrong step means irreversible damage to the brand.

00:03:38: Wow,

00:03:39: so real high stakes test?

00:03:40: Exactly you have to test if they can sit in the crossfire of sales marketing and operations because They will all be demanding Confleshing things and see if this person can still build something structurally sound.

00:03:51: And

00:03:51: even when you do find someone with that judgment The default onboarding process usually breaks them.

00:03:55: anyway Like David Turavitz warns against handing a new GTM engineer the keys to your entire CRM on day one and just saying, you know fix our data.

00:04:05: Because you cannot diagnose a complex architecture code it's impossible!

00:04:09: Exactly he says The most successful hires run A very narrow repeating CRM audit On Just One Specific Customer Segment.

00:04:18: Over Their First Thirty Days They Maped The System By Looking At Actual real world reply data.

00:04:24: Right, they have to prove the loop holds together end-to-end before ever try and scale it.

00:04:28: It's a totally evidence based approach

00:04:30: But finding professional who blends that technical rigor with actual commercial intuition That is incredibly difficult.

00:04:37: It's nearly impossible.

00:04:38: Noemi J ran the numbers on sales navigator, and The Talent Pool is shockingly small.

00:04:43: How

00:04:43: small are we talking?

00:04:44: We're talking about roughly two hundred thirty four GTM engineers in all of New York And maybe two hundred fifty in San Francisco.

00:04:50: Wait

00:04:51: really just a few hundred

00:04:52: Yeah.

00:04:53: So when A talent pool Is that tiny you can't Just throw three different recruitment agencies at the problem.

00:04:57: They will All Spam the exact same Two Hundred People.

00:05:00: That Makes sense.

00:05:00: Sourcing Requires Deep Trusted Network Relationships.

00:05:04: Then

00:05:04: Exactly, which explains why we're seeing initiatives like the quota referral network launching in Europe.

00:05:09: Henri Beckeris pointed out that they are sourcing strictly through vetted operator referrals now

00:05:15: because scarcity drives price and Joe Rue noted that Anthropic is currently offering somewhere between three hundred twenty thousand and four hundred five thousand dollars in base salary for a staff engineer to own their lead-to-cash architecture.

00:05:28: it Is wild money

00:05:30: but I have to push back on this a little bit though.

00:05:32: Is a GTM engineer really fundamentally new discipline?

00:05:37: Or is it just a RevOps person with fancier title and bigger ego.

00:05:40: What's fascinating here, the capability map moving significantly faster than the organizational chart.

00:05:46: Okay what do you mean by that?

00:05:47: Well traditional revops are largely reactive its mostly building dashboards.

00:05:51: to report on whats happened last month.

00:05:53: right but GTM engineering is proactive software level system-building.

00:05:58: I see

00:05:58: And Maja Voje highlighted that the title has actually already fractured into two distinct profiles.

00:06:04: There's a technical track where engineers are building on heavy data infrastructure like Snowflake and Databricks, right?

00:06:10: Then there is a commercial track orchestrating the motion through tools like Adio Gong and HubSpot.

00:06:16: So it was same job title but to entirely different functional skill sets depending upon company maturity.

00:06:21: Exactly

00:06:23: you know, if a company is paying upwards of four hundred thousand dollars for these engineers.

00:06:27: what are they actually building?

00:06:28: Well the answer of course is AI and agents.

00:06:31: Right!

00:06:32: The reality of what it's driving revenue looks very different from the wild unsupervised automation that gets hyped up on social media all day.

00:06:41: Oh...the contrast between internet hype in enterprise-reality.

00:06:46: Henry Hund analyzed the best GTM agent builds in the market and he found a universal rule among the most effective ones.

00:06:53: Let me guess, they are heavily restricted?

00:06:55: Yes!

00:06:55: They're strictly forbidden to send... The guardrails or feature.

00:07:00: So just prep things

00:07:01: Exactly.

00:07:02: These agents draft, research, read intense signals And suggest responses But never ever hit.

00:07:10: publish without human in loop

00:07:12: which makes sense because if an AI hallucinates and promises like a crazy eighty percent discount to an enterprise buyer, you can't just unsend that email.

00:07:21: No!

00:07:22: You can't.

00:07:22: And...that governance issue is the real bottleneck right now.

00:07:26: Jeremy Gondiallam pointed out most agents are currently stuck running locally on one person's laptop

00:07:31: Which is terrifying If think about mechanics there.

00:07:34: It really is.

00:07:35: By the way, listeners having an AI agent on your laptop without governance is like letting a super smart intern run your corporate bank account from their personal phone.

00:07:43: It's a massive single point of failure!

00:07:45: Absolutely also quick side note if you want to stay ahead of these rapidly shifting AI trends make sure to subscribe so you catch our future deep dives.

00:07:53: yes definitely do that.

00:07:55: but back to the laptop issue.

00:07:56: You need the same robust controls for an AI moving at deal stage and machine speed.

00:08:02: So tools like Block's Buzz are starting to treat AI agents, like actual corporate team members.

00:08:08: They give them scope permissions audit trails and strict operating hours.

00:08:12: But there is another layer of why AI fails in sales right?

00:08:16: Ian Matthews nailed it when he talked about context.

00:08:19: Oh this such a good point.

00:08:20: Yeah

00:08:21: because human sellers get continuous enablement.

00:08:23: they get weekly coaching new battle cards market updates They adapt.

00:08:27: But AI usually just runs on a single paragraph prompt that someone wrote six months ago and nobody ever bothers to update it?

00:08:34: Exactly, the market shifts competitors drop new features but The AI is still selling.

00:08:39: based On last year's context

00:08:40: And That lack of continuous Shifting Context Is the primary reason.

00:08:45: AI Assisted Selling underperforms.

00:08:47: in complex B-to-B environments.

00:08:50: It Just suffers from Prompt Decay!

00:08:52: But when you get the context In the guardrails right...the results are undeniable.

00:08:56: Look at the real-world wins.

00:08:57: Johnny Barrett shared what's happening.

00:08:59: It's striped right now.

00:09:00: Oh,

00:09:00: yeah those numbers are crazy.

00:09:02: They built a custom AI tool for their account executives called Kai and it literally removed twenty five thousand hours of administrative work

00:09:10: Twenty five thousand ours Right?

00:09:11: And the result is that those human AEs Are generating twenty six percent more revenue opportunities in closing thirty nine percent more deals.

00:09:20: That is the benchmark right there.

00:09:22: The AI doesn't replace the rep.

00:09:24: It integrates seamlessly into their workflow to strip away all that immense friction of enterprise admin.

00:09:30: But you have to contrast That enterprise success with the noise at the bottom of the market.

00:09:35: like Kieran Hooper-Warren brought up the current hype cycle around this terminal based GTM tooling.

00:09:41: Right, The CLI Hype?

00:09:42: Yeah for those who might not be deep in the dev world This is where you run your entire sales motion by typing raw code into a black command line interface rather than clicking buttons on normal visual dashboard.

00:09:53: And

00:09:53: look it looks incredibly slick if you are technical operator.

00:09:56: But the typical B to B buyer You know founder.

00:09:59: with their hair on fire trying to run a lean business They have zero desire To learn terminal commands.

00:10:03: just send an email sequence.

00:10:05: Exactly

00:10:06: Right now, the builders of these headless tools are largely just selling to other service agencies.

00:10:11: Yeah!

00:10:11: The ones who have the luxury of tinkering in a coffee shop for two hours.

00:10:16: It's a fascinating echo chamber But it is not a scalable B-to-B product category yet

00:10:22: Which brings up critical friction point.

00:10:24: This raises an important question.

00:10:26: If everyone eventually figures out guardrails And every team deploys highly capable AI agents To scale their outreach What happens to human trust?

00:10:36: That's

00:10:36: the million dollar question.

00:10:37: Right,

00:10:38: Marcos Stu and Sebastian Don both touched on this.

00:10:41: Inboxes are already flooding with perfectly written highly personalized emails that were never touched by humans.

00:10:47: So when perfection scales infinitely The written word basically loses its premium.

00:10:52: Exactly!

00:10:53: If I know an AI wrote a five hundred-word analysis of my business Why should i spend my human time reading it?

00:10:58: You

00:10:58: shouldn't.

00:10:59: The teams that win over the next three years will let agents handle the volume of research, data routing and prep.

00:11:04: But humans show up purely where real-time conversation itself is value In person.

00:11:10: human to human interaction become absolute most expensive and valuable pipeline channel available.

00:11:16: Here's what gets really interesting.

00:11:18: With our infrastructure built and AI properly governed so it doesn't just wreck a brand How do we deploy this into market?

00:11:25: because single-channel strategies are totally dead.

00:11:28: Exactly, and architecture is everything!

00:11:31: Faiz Syad introduces this concept called the all bound architecture.

00:11:35: Right All Bound.

00:11:36: Instead of saying we're going to do outbound or inbound teams run six motions simultaneously on a priority list.

00:11:44: just five hundred accounts an outbound as hard capped at twenty account per SDR per week Triggered only by signals from the other motions.

00:11:53: Right, which sounds intense!

00:11:54: Running six motions simultaneously sounds like a recipe for total burnout.

00:11:59: How does a lean marketing team actually pull that off without dropping the ball?

00:12:02: Well

00:12:03: it requires deep orchestration not just brute effort.

00:12:06: Like Poonam L provided a brilliant lens on regional GTM planning.

00:12:10: That applies here.

00:12:11: She says strategy is NOT about geographical coverage.

00:12:14: It's not about being everywhere.

00:12:16: No It's not about having a localized play for every country just because they exist.

00:12:21: True strategy is making hard choices about where you have an actual right to win, and deliberately choosing where you will under-invest.

00:12:30: So you concentrate your resources when the revenue friction is lowest?

00:12:34: And that totally aligns with Yann Brockvich.

00:12:36: research on demand flywheel.

00:12:37: Oh!

00:12:37: The eighty companies he looked at

00:12:39: Right He noted over eighty BtoB companies had outbound running completely alone And when it runs in a silo, It fails.

00:12:48: Always!

00:12:49: Accounts only compound When outbound is treated as just one stage inside of six-stage.

00:12:53: demand flywheel Right

00:12:54: which goes traffic, lead capture, nurturing conversion qualification and retention.

00:12:59: Exactly Every single stage passes data to the next But even with deep focus You have ensure that human reps actually follow system you built.

00:13:08: That's the hard part.

00:13:10: Dow esters shared a great insight about systematizing behavior.

00:13:13: He was working with the founder who is super frustrated because their reps kept cherry picking bad fit accounts

00:13:18: and The Founder just kept trying to coach them out of it, right?

00:13:20: Yes But Wester pointed out that the CRM Was currently built in a way That actually rewarded the cherry-picking.

00:13:27: see if you want To change human behavior more coaching rarely works.

00:13:32: You have to redesign this system so that good behaviors easy And bad behaviors hard.

00:13:37: You force the software to enforce this strategy.

00:13:39: You auto-assign the highly scored ICT leads, and you visually hide the rest in

00:13:44: system.".

00:13:45: And making that transition from gut instinct into a scalable system is usually the hardest hurdle... Britt Bowman shared a crazy story of the founder whose first half-million dollar sales hire completely failed.

00:13:57: Oh, because the founder led motion was never stigmatized?

00:14:00: Exactly!

00:14:00: The founders' initial success was built on their own charisma and personal network.

00:14:05: They never translated that motion into process.

00:14:07: anyone else could actually run.

00:14:09: You just can't scale instinct

00:14:10: And you cannot scale vanity metrics either.

00:14:13: Saul W. Mark has pointed out a glaring issue in healthcare GTM but honestly it applies everywhere.

00:14:18: The trade show problem.

00:14:19: Yes Teams will drop half a million dollars on a massive conference booth, scan hundreds of badges and generate absolutely zero pipeline.

00:14:27: Because they rely on vanity badge scans?

00:14:29: Right

00:14:30: Marquez says the ROI event does not happen in the show floor.

00:14:34: It comes from booking accounts eight weeks out and treating post-event follow up as rigorous campaign Not just quick.

00:14:41: nice to meet you email

00:14:42: And every motion requires that intentional architecture.

00:14:46: Thomas Harrison noted the exact same dynamic with multi-partner GTM plays.

00:14:50: Oh, The Line Up of Logos!

00:14:52: Exactly they usually fail because companies treat them as just a line up of logos on a webinar slide.

00:14:58: but to actually drive revenue They need a single shared story explaining why none of the partners can solve the problem alone.

00:15:05: But let's look at the reality underneath all of this...the All Bound architecture, the Multi Partner plays, the signal tracking.

00:15:11: it is all beautiful in theory

00:15:14: But it relies on an underlying data layer.

00:15:16: Right, and the overwhelming consensus from the sources we're looking at is that right now underneath all this shiny new AI tech The revops in data problems We thought we solved years ago

00:15:26: are

00:15:26: actively breaking the system.

00:15:28: It's like trying to run a modern bullet train On wooden tracks...the foundation is buckling.

00:15:34: Dr.

00:15:34: Renia Kay shared A brilliant example of what she calls the context gap.

00:15:39: This is such a good example.

00:15:41: Imagine your CRM flags and antitrize account, twelve people from that company just visited you pricing page.

00:15:47: four of them viewed your security documentation.

00:15:50: someone downloaded an integration guide at midnight.

00:15:53: so your system scores that as massive intent it routes to best AE.

00:15:58: immediately the

00:15:59: system fires perfectly.

00:16:01: The AE launches highly personalized sequence but six weeks later You find out It was just procurement, collecting market benchmarks to renegotiate with a competitor.

00:16:10: Wow!

00:16:10: So the data is one hundred percent accurate but the interpretation and context were entirely wrong?

00:16:15: Exactly And that's what Anita Tomar calls expensive looking guesses.

00:16:19: Yes

00:16:20: We have these polished AI dashboards which look highly strategic But because of underlying study infrastructure is fragmented outdated or biased.

00:16:27: The AIs are producing those expensive guesses

00:16:30: Because the problem is rooted in the database architecture itself.

00:16:33: Juga LaSha notes that traditional CRM data models were built for human dashboards,

00:16:38: just rows and columns

00:16:40: right but these are breaking under autonomous AI agents that consume massive context windows.

00:16:46: Sha argues we have to transition to event driven semantic architectures

00:16:50: because if you don't make that shift You end up trapped in disconnected silos.

00:16:55: Joshua Feinberg pointed out that for many digital infrastructure firms, their entire GTM strategy is just an expensive guess because data is trapped in these silos.

00:17:04: Which leads to a reliance on vanity metrics rather than shaping actual purchase criteria.

00:17:10: And honestly the ecosystem of data itself is getting murky.

00:17:13: Spencer Tahill warned about erosion trust.

00:17:17: He exposed a WhatsApp group of over twenty people operating as an undisclosed engagement pod.

00:17:22: Just coordinating fake-engagement on LinkedIn posts?

00:17:24: Exactly, so if the CRM is breaking and our signals are getting misread what does a strategic BDB marking professional actually DO tomorrow morning to fix their data?

00:17:33: If we connect this to The Bigger Picture We need an independent platform agnostic execution layer.

00:17:40: Sturman O'Connor brought this up.

00:17:41: Okay something that sits above the CRRM

00:17:43: exactly.

00:17:44: You pair that execution layer with what Hilary Terrell calls intelligent orchestration.

00:17:49: you have to connect every single signal To the right action.

00:17:52: rather than just letting leads sit untouched in a broken database,

00:17:56: you connect The signal directly to the action Right?

00:17:59: That is the future of revenue architecture.

00:18:02: We have covered the engineering talent required to build it the guardrails AI needs all-bound motions and the semantic data layers.

00:18:09: But I want to deliver one final thought for you to mull over from Hilla Lauterbach.

00:18:14: What's her take?

00:18:15: She

00:18:15: points out that AI just erased the one-moat companies thought they had, which was building the product.

00:18:20: Technology is no longer the moat because AI made buildings fast and cheap.

00:18:25: So what's left

00:18:25: for the GTM professionals listening?

00:18:27: your new defensible mote is simply validation speed.

00:18:31: It is how fast your GTM engine can turn buyer signals into repeatable revenue before competitors

00:18:56: copy.