Best of LinkedIn: Go-to-Market CW 20/ 21

There is a clear shift in Go-to-Market from isolated AI experiments to structured, governed, system-led execution. The strongest themes are agentic GTM, stack simplification, outbound reinvention, new GTM engineering roles, and a sharper focus on commercial discipline. The market is moving from “more tools” to better architecture, cleaner data flows, and human-controlled automation.

Date

May 28, 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 20/ 21:

Agentic GTM Moves into Production

AI agents are increasingly positioned as operational infrastructure rather than experimentation tools
Use cases include pre-call preparation, outbound execution, deal research, enrichment, forecasting, and customer advocacy
MCP and Claude Code appear as practical integration layers across Gmail, Drive, Apollo, HubSpot, Salesforce, LinkedIn, and adjacent GTM systems
The most credible agentic workflows have defined inputs, controlled actions, and clear commercial outputs
Human checkpoints remain essential for forecast governance, outbound approvals, data handling, and decision quality

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GTM Stack Simplification Becomes a Strategic Priority

Tool volume is increasingly framed as a liability when system logic is weak
Leading GTM teams are prioritizing data quality, routing logic, CRM structure, workflow orchestration, and feedback loops
Stack maturity is defined by whether tools exchange context and improve decisions, not by the number of applications deployed
Autodesk stands out as a concrete example of reducing sales app complexity while strengthening the Salesforce backbone
Backbase highlights the value of challenging legacy stack complexity and rebuilding around pipeline impact

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Outbound GTM Is Rebuilt Around Intelligence

Outbound is moving from activity volume toward account research, enrichment, and buying-signal detection
Clay, Apollo, Sales Navigator Advanced, Exa, Landbase, Deepline, and Claude Code are positioned as key components of modern outbound architecture
Corporate research, buyer committee mapping, intent signal capture, account scraping, and waterfall enrichment are becoming core workflow elements
Bond v2 reinforces the emergence of AI GTM engineers that plan and execute outbound campaigns
Default’s funding highlights continued market conviction around agent-led commercial execution

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ABM Regains Strategic Relevance

Account-based GTM is becoming more important as generic outbound becomes easier to automate
Stronger ABM motions are built around best-customer patterns, account intelligence, intent data, and competitor context
Modern ABM is shifting from campaign targeting toward always-on account systems
Community Qualified Leads introduce a broader view of intent, capturing public discussions and community signals before form-fill conversion
The core GTM advantage is moving toward relevance, timing, and account-specific context

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GTM Engineering Becomes a Core Operating Model

GTM Engineering is emerging as a visible function across sales, marketing, RevOps, product, and AI
The role focuses on infrastructure, workflow automation, CRM logic, signal orchestration, and practical AI deployment
Related role concepts include Agentic GTM, Marketing Engineer, Applied AI Engineer, and Field Deployment Engineer
The content points to a growing need for builders who understand both commercial motion and technical execution
GTM is shifting from campaign-led growth toward engineered revenue systems

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Governance and Commercial Discipline Move to the Center

AI agents are expected to expose weak forecasts, unclear ownership, and poor data hygiene
Governance topics include permissioning, security, PII controls, auditability, cost management, and human approval
Token costs and agent maintenance are becoming part of the total-cost discussion
Clay’s pricing change reinforces the need to use enrichment selectively and design more resilient data architectures
CFO-oriented AI cases are increasingly framed around EBITDA impact, CAC reduction, cycle-time improvement, and avoided cost

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Buyer Journey Alignment Remains a Major Gap

Buyer journey alignment is highlighted as a persistent weakness in GTM execution
Content needs to answer concrete buyer questions across awareness, consideration, decision, value realization, and advocacy
The strongest GTM content logic is stage-specific, not volume-driven
HBR-linked insights show a gap between ambition to align around buyers and actual understanding of buyer movement
Customer advocacy is also being redesigned through AI-native workflows, with Zapier showing how intake and story discovery can be systematized

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Segment and Market Specificity Gain Importance

GTM in Asia is positioned as requiring market-by-market relevance rather than broad regional messaging
Cybersecurity GTM is framed as structurally different from generic SaaS due to regulation, trust, and accountability
SMB and mid-market buyers require tailored partner enablement, lifecycle support, and faster execution models
Cisco’s SMB and Mid-Market Partner Program stands out as a partnership-driven GTM development
GTM systems need to adapt by segment, region, maturity stage, and buying context

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Strategic Planning Becomes More Structured

GTM planning is increasingly supported by frameworks, templates, blueprints, board-deck logic, and stage-based rules
Miro’s GTM Strategy Blueprint reflects demand for structured planning assets from ICP through KPI tracking
Stage-based GTM rules emphasize that what works at early revenue stages can break at later stages
Lean Startup thinking is challenged by the view that distribution must be designed earlier
GTM planning is shifting from static documentation toward operating architecture

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New Products, Partnerships, and Market Moves

Bond v2 launched as an AI GTM engineer for planning and running outbound campaigns
Default raised capital to build agents for go-to-market execution
Deepline brought waterfall enrichment into Claude Code for natural-language sourcing and agentic research
Extruct launched a data RevOps service for industrial-vertical enrichment, hierarchy mapping, and CRM agents
Cisco introduced an SMB and Mid-Market Partner Program for partner-led pipeline and lifecycle support
GTM AI Academy moved to Substack with free and paid content tiers
GTM as Code released video recordings focused on building GTM systems
GTMLens released analysis on email deliverability and AI SDR workflow performance

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