Something interesting is happening in B2B go-to-market right now. A role that barely existed two years ago has become one of the fastest-growing jobs in tech. LinkedIn listed over 3,000 open GTM Engineer positions in January 2026, and it is now one of the fastest-growing roles in the industry.
The GTM Engineer builds and maintains the automated systems that power modern revenue teams: data enrichment pipelines, multi-channel outreach workflows, CRM integrations, lead scoring models, and the connective tissue between an ever-growing stack of tools.
The rise of the GTM Engineer tells us something important about where B2B go-to-market stands today. It tells us that the tools have become powerful enough to automate almost anything, but complex enough that you need a dedicated technical person just to make them work together.
And that creates a real problem for most B2B teams.
The GTM complexity tax
The average B2B software company now runs several core GTM channels, with more channel experiments layered on top. Each channel typically requires its own tools, its own data sources, and its own execution logic. A single outbound motion might involve a prospecting tool, an enrichment provider, an email platform, a LinkedIn automation tool, a CRM, and some form of intent data. That is six tools for one channel alone, each with its own login and its own data that needs to stay in sync.
For well-funded companies that can hire a GTM Engineer (or a team of them), this works. They have the technical talent to stitch everything together, maintain the integrations, and build custom workflows that turn strategy into execution.
But most B2B teams are not in that position.
The majority of startups, small growth teams, agencies, and independent consultants do not have a dedicated GTM Engineer. They do not have the budget for one either. The infrastructure tools this role depends on, platforms like Clay, have become widely adopted, especially among agencies, but they require real technical skill to use effectively. Users report steep learning curves, complex workflow logic, and ongoing maintenance that demands dedicated attention.
The result is a growing divide. On one side, well-resourced teams with GTM Engineers are building sophisticated automated revenue systems. On the other side, many teams are spending more time managing their tools than actually selling.
AI is accelerating everything, including the complexity
AI has made GTM capabilities dramatically more accessible in some ways. Tools like Claude Code allow a single operator to build outreach scripts, enrich data through APIs, and automate multi-step workflows through natural language. General-purpose AI tools like ChatGPT are now nearly universal among GTM leaders, and a meaningful share have started adopting AI agents.
But the results are mixed. Many GTM leaders report seeing little or no impact from AI on their go-to-market efforts. We hear the same experience again and again: a team runs an AI SDR for months and struggles to turn it into a single real opportunity.
The pattern shows up in retention too. AI SDR tools have struggled with high churn, and fully hands-off AI outreach has a habit of booking more meetings while producing less real revenue than approaches that keep a human in the loop.
The issue is not that AI does not work. It clearly does, for specific tasks, in the right context. The issue is that AI is being layered on top of already-fragmented systems without solving the underlying problem: there is no single place where the strategy, the execution, and the visibility come together.
Adding a powerful AI tool to a disconnected stack does not make the stack less disconnected.
The gap between strategy and execution
Across all the research and conversations we have had over the past two years, one pattern comes up more than any other: most teams have a GTM strategy. What they lack is a reliable way to execute it consistently and see whether it is working.
Our conversations bear this out. Leadership tends to believe sales and marketing are aligned, while the people actually doing the work agree far less often. Genuine, strong alignment between the two functions is rare, and the cost of that gap, in wasted effort, unused work, and lost pipeline, is real and large.
And the visibility problem is real. Sales teams often have little insight into what marketing is actually doing. Handoffs break, so a large share of marketing-engaged prospects never get a proper follow-up, and much of the content marketing produces goes unused by sales entirely.
These are not strategy problems. The strategy may be sound. The ICP may be well-defined. The messaging may be on point. But somewhere between the plan and the execution, gaps appear. And without end-to-end visibility into the full motion, it is hard to pinpoint exactly where or why.
What we are building at SimpliQ
We are solving the gap between having a GTM strategy and being able to execute it consistently, with full visibility, without needing a dedicated GTM Engineer.
SimpliQ is an AI-native GTM platform. It is designed for teams that do not have a GTM Engineer, do not want to stitch together six tools, and do not want to hand their outbound to a black box they cannot see into.
Here is how it works:
You start with the stack you already have. Connect your CRM or a data source, then describe your goal in your own words. Something like: "Reach out to SaaS product leaders at companies that recently raised funding." No complex setup. No technical configuration. Just your GTM objective.
AI builds the complete workflow. SimpliQ generates the execution plan: audience targeting rules, data enrichment, personalized message templates, and timing. Outreach runs on email at launch, with more channels arriving through connectors. You see the entire strategy laid out visually before anything runs. You can review it, adjust it, and launch it when you are confident.
It executes with full visibility. Once you launch, the workflow runs on your terms. Approvals can be on or off, per workflow: review every send, or set the rules and let approved workflows run. You see every step: which prospects are engaged, which messages are performing, where bottlenecks are forming, and which meetings are getting booked. You can optimize in real time based on what the data shows.
The strategy comes from you. AI handles the buildout and orchestration. And you can see everything that is happening at every step.
Where we are today
We are early. SimpliQ is in active development, and we are building it against real workflows and real prospects so it holds up in the situations teams actually face.
We are opening a waitlist for teams that want to help shape what this becomes and be first in line when we open access. That includes founders, growth teams, agencies, and anyone who has felt the gap between having a GTM strategy and being able to execute it consistently.
If you have experienced that gap, or if any of the patterns described in this post feel familiar, we would genuinely love to hear from you. We are not pretending to have all the answers. We are building in the open, learning from every conversation, and shaping the product around what real teams tell us they need.
Join the waitlist
SimpliQ is the AI-native GTM platform that enriches every contact, finds your next buyers, and executes the outreach, with full visibility and control. Join the waitlist to help shape it, and to be first in line when we open access.
A note on this article: We used AI to research the topic, organize the structure, and help draft this post. But the perspective, the direction, and the refinements came from multiple rounds of back-and-forth where we pushed back on angles that did not feel right and shaped it into something we would stand behind. That process, AI doing the heavy lifting while we stayed in control of the thinking, is exactly the approach we are building into SimpliQ.