The Sales Function has Collapsed
GTM Engineering is the future of the sales function.
In late 2023, I wrote a post that aimed to predict the talent stack for the next ten years. Clay officially collapsed the sales function one year later by coining “GTM Engineer.” This new role encapsulates one of the examples I proposed on the sales function collapsing into efficiency.
How Did We Get Here?
Quoting Ernest Hemingway, “It happened slowly, then all at once”. The sales function as we knew it in tech started in the late 1990s, peaked in the 2010s, and started its downfall after COVID-19. With the rise of Gen-AI in late 2022 and mainstream adoption in 2023, the sales function as we knew it collapsed.
The Genesis Years: 1990s - 2009 — Pioneered by tech juggernauts like Salesforce, Oracle, and Dell, who transitioned from field sales to tech-enables sales leveraging phone calls and emails
The Golden Years: 2010 - 2019 — Perfected by new entrants like HubSpot, Salesloft, Outreach, and ZoomInfo, who leveraged CRM and automation to scale inbound and outbound motions
The Dying years: 2020 - 2023 — Declining cold email success and over-reliance on “spray & pray” and inbox saturation on email and LinkedIn, and the birth of LLMs
The GTM Engineering years: 2023 - ongoing — AI-first, automation, and product-led-growth enabling the rise of GTM Engineering by scaleups and startups like Clay, Cargo, Pocus, and Mutiny
Seeing the Evolution From the Trenches
My product management career has focused on building product surfaces for internal teams. Some of those products were built in actual code, while others were powered by no-code and workflow automation. My “clients” have included ops teams, sales teams, marketing teams, company executives, and even founders who needed better tooling for fundraising or time management.
In many ways, I was a GTM Engineer before the concept was even understood, let alone coined. During 2022-2023 at MarketerHire, I built the infrastructure for a new business line with an initial ARR of $200k and helped scale it to $2M ARR. I was effectively the “engineer” for the sales team, piping website leads to the CRM and beyond throughout the sales cycle. Below is the tech stack and steps a lead traveled through from inbound prospect to becoming a client***:
Mutiny: A/B testing copy and landing pages
Segment*: sending website and lead traffic data to CRM
HubSpot: managing leads with 100+ workflows and fully automated to minimize AE data input
Clearbit: enriching capture leads to avoid form churn and keeping the form short
Webflow**: hosting forms and scoring leads before sending to Chili Piper
Typeform: lead capturing on the website
Chili Piper: lead routing depending on scores, geo, and other parameters
Airtable: matching demand requirements with supply (contractors)
PandaDoc: automating contract creation
Make: connecting and managing automation when not available natively in tools
I’ve seen firsthand how GTM Engineering has been the missing piece in the GTM strategy for startups. Building the infrastructure above for MarketerHire took more time aligning stakeholders and getting the green light than the actual buildout. Team leaders can be incredibly siloed and not know how intertwined their tech and operations are. While running user interviews, one of the sales leaders told me they hadn’t talked to a product person in over a year. That’s how disconnected sales and engineering teams can be! GTM Engineering is the glue merging the technical and non-technical efforts of startups.
*A former engineer had integrated Segment to HubSpot and it was never refactored, but this step would’ve been “cleaner” passing lead parameters straight to HubSpot without going through Segment
**Similar to the above, a former engineer wrote JS code to do lead routing on the front-end (not needed) when it should’ve been done in Typeform.
***One major thing missing from this workflow was giving high-score leads a chance to talk to a sales team member immediately. The leadership had little appetite for experimentation, and this was a missed opportunity. Nobody wants to wait days to talk to someone when interested in a product!
Implications for Startups
Collapsing the talent stack for any function is a good outcome for startups. The obvious benefit is a reduction in workforce. Whereas the original inside sales playbook required SDRs, AEs, and Sales Engineers, the modern sales stack led by a GTM Engineer requires one person owning those three functions.
Another benefit for startups comes through the breakdown of silos. Whereas inside sales required a lot of data transfer between all the people involved in a sale, a GTM Engineer will hold all the necessary knowledge about who the lead is, where it came from, and how to engage in running a demo or onboarding them into the product.
Finding and managing GTM engineers is a challenge for startups. This function is less than three months old. Technical people rarely want to get involved with sales, and salespeople rarely have the patience or skills to build software. Managing GTM Engineers will also pose a challenge to startups. Who should they report to? Should they report directly to Ops, Sales, or the founders? Should they manage a team and own P&L?
Implications for Talent
The significant implication for talent is rising to the occasion. As the sales function evolves, individuals in each role will see pressure to grow and learn adjacent roles. Not everyone will be able to level up to becoming a GTM Engineer, but below is a roadmap for those who are ambitious and want to bet on this function:
SDRs/BDRs:
Master AI-driven prospecting tools like Apollo, Clay, and LLMs (ChatGPT, Anthropic, etc.)
Leverage predictive analytics and intent data like Koala and RB2B to engage with warm leads
Get comfortable with video and async selling tools like Loom and Vidyard to stand out in a crowded prospect inbox
Account Executives
Automate data entry and lead cycle management with native AI capabilities of existing CRMs
Leverage lead insights and predictive data to engage with warm leads
Get comfortable with technical lingo and be a power user of the product you’re selling
Sales Engineers
Automate demo creation and workflows
Leverage LLMs to draft custom responses and even mitigate live pushback
Get comfortable with RevOps data to prioritize high-impact demos and work with product to lean into PLG motions