Best of LinkedIn: Go-to-Market CW 18/ 19

Over the selected two-week period, Go-to-market discussions shifted from tool adoption to operating model redesign. The strongest signals point to AI-native infrastructure, cleaner data, technical GTM roles, and more disciplined outbound built around buying signals, orchestration, and human judgment.

Date

May 14, 2026

Go-to-Market

Methodology: Every two weeks we collect most relevant posts on LinkedIn for selected topics and create an overall summary only based on these posts. If you´re interested in the single posts behind, you can find them here: https://linktr.ee/thomasallgeyer. Have a great read!

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Listen to our podcast

If you prefer listening, check out our podcast summarizing the most relevant insights from Go-to-Market CW 08/ 09:

AI Native GTM Stack

GTM stacks are moving from SaaS-heavy toolchains toward AI-controlled operating systems
Claude Code is positioned as the central execution layer across research, enrichment, outreach, reporting, and workflow orchestration
Agent-friendly tools gain relevance when they can be triggered, controlled, and coordinated by AI without manual switching
The market focus shifts from buying more tools to connecting existing tools through APIs, MCPs, and workflow engines
Cost compression becomes a core narrative, with lean AI stacks replacing expensive combinations of software seats and manual RevOps work

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GTM Engineering

GTM Engineering is emerging as the bridge between strategy, RevOps, sales, marketing, data, and technical automation
The role is framed as infrastructure ownership, not just faster outbound or workflow automation
Strong GTM Engineers combine business context, technical fluency, systems thinking, and clear communication
Demand for technical GTM talent is rising as companies move from isolated AI plays to reusable operating systems
Marketing leaders are expected to own cross-functional GTM systems or risk losing control of core revenue infrastructure

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Outbound and ABM

Outbound is being rebuilt around segmentation, signal quality, account context, and timing
Generic prospecting is losing credibility as teams prioritize ICP contacts with fresh buying signals
Warm outbound, closed-lost monitoring, event-triggered outreach, and stakeholder mapping are positioned as higher-value plays
ABM and demand generation are converging into unified account investment strategies across the funnel
Enterprise ABM prioritizes focused account selection, tailored buying experiences, and decision-maker engagement

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Data and Governance

AI impact is constrained by CRM hygiene, workflow documentation, lead traceability, and source quality
Dirty data is treated as a primary blocker because agents amplify flawed inputs rather than fixing them
Proprietary data is positioned as more defensible than rented orchestration layers
AI governance enters GTM through registry, identity, observability, attribution, and system ownership
Clean infrastructure is framed as a stronger advantage than adding more headcount or more disconnected tools

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Product Highlights

Salesforce Headless 360 MCP signals a shift toward browserless Salesforce interaction, but security and capability gaps remain relevant
GetSales MCP introduces chat-based control for client setup, campaign execution, and analytics
Hermes Agent replaces OpenClaw with reusable, self-improving skills for GTM research and outreach
GPT-5.5 is positioned as a token-efficient model for automating recurring GTM reporting and operational workflows
Cresta gains visibility as part of the AI-first GTM stack, with emphasis on live AI agent deployments and enterprise adoption

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Partnerships and Ecosystem Signals

Airscale with Clay stands out as a tactical pairing for lower-cost enrichment workflows
Cresta’s Battery Ventures visibility reinforces the importance of AI-first GTM stack narratives
Capchase appears through a completed growth-support engagement and planned write-up
ElevenLabs appears through operational excellence content connected to fast-scaling company building
Ecosystem value is increasingly created through tool combinations rather than isolated product usage

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Human Role in AI-Led GTM

AI is framed as a replacement for manual GTM work, not for strategic GTM ownership
Human advantage remains strongest in positioning, trust, closing, relationship building, and decision logic
SDRs using AI are positioned as stronger than traditional SDRs or standalone AI SDR replacements
Build-versus-buy decisions become more strategic as agentic coding increases maintenance and security responsibilities
The winning profile combines commercial judgment with the ability to translate strategy into technical workflows

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Capability Building

GTM education is shifting toward prompts, playbooks, MCP libraries, tool stacks, and workflow blueprints
Clay is positioned as powerful only when paired with domain expertise and strong prompt logic
Curated GTM communities, newsletters, and expert lists show rising demand for structured learning in AI-native GTM
The capability agenda moves from software selection to operating system design
The strongest teams are codifying repeatable workflows instead of relying on one-off experiments

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