GTM engineering for early- and growth-stage B2B software companies.
Stretched revenue teams and messy data are the top two reasons AI GTM initiatives stall. Start with an agent your data can support today, then build the foundations one workflow at a time.
AI has accelerated engineering and support. GTM is next.
Engineering ships code with AI every day, and support resolves tickets with it at scale. Go-to-market teams are mostly still waiting. Ask RevOps leaders what's holding them back and two answers top the list.
Messy data
56.9%of RevOps leaders name fragmented or messy data as the top barrier to AI in GTM.Stretched teams
40.4%say AI competes with keeping the business running.Source: GTM Council, Build vs. Buy report, 2026, a survey of RevOps leaders.
“The future is already here. It’s just not evenly distributed.”
William Gibson
The survey found two. From running these teams, I'd add a third and a fourth.
The skill gap
Anyone can build an agent now. Building one a revenue team can rely on, with the context it needs, review gates, and tests, is a different job, and most teams have nobody whose job it is.
The coordination gap
Nobody owns the data model, the definitions, or the build queue. So reps build their own agents instead of selling, teams build the same thing twice, and what gets built leaves with whoever built it.
Built by an operator, not an agency
Aaron Altamura.
Over a decade running revenue operations and finance inside B2B SaaS companies; now building the agents and the data layer under them, start to finish.
More about AaronAn agent for every stage of the bowtie
Hundreds of GTM tasks still run by hand, or don't run at all. Each one can become an agent that reads your systems and then decides, coordinates, writes, or records, with a person approving its work until it has earned the right to run on its own.
- AwarenessLead
- EducationMarketing qualified lead
- SelectionSales qualified lead
- CommitWin
- OnboardingOnboarded
- AdoptionRetained
- ExpansionExpanded
What the agents run on: clean CRM and data model, written context, enrichment and signals, conversations captured, governed access, review gates and tests, measurement.
- Customer acquisition: Research, Inbound, Signal, Scoring, and Data-entry agents
- Implementation: Handoff agent, Onboarding watcher
- Service: Account health, QBR, and Coaching agents
- Renewals: Renewal agent, Churn watcher
- Expansions: Expansion and Advocacy agents
Customer acquisition
- Research agent: briefs every account first
- Inbound agent: answers new leads in minutes
- Signal agent: funding and job changes trigger plays
- Scoring agent: ranks accounts against your ICP
- Data-entry agent: logs calls and emails into the CRM
Implementation
- Handoff agent: carries the details from sale to kickoff
- Onboarding watcher: flags stalls early
Service
- Account health agent: routes usage and calls to a play
- QBR agent: drafts the review from usage
- Coaching agent: scores calls against your playbook
Renewals
- Renewal agent: drafts the value story 90 days out
- Churn watcher: scans weekly, queues risks for review
Expansions
- Expansion agent: usage spikes to upsell
- Advocacy agent: mines calls for references
Built like engineering, owned by your team
Diagnosis first, then build
The bowtie above shows where growth stalls, and the build list follows from that. A baseline comes first, so every build after it is measured against something real.
Agentic infrastructure
Fix, skip, or move off legacy point tools and admin seats. In their place goes the data infrastructure the agents need, plus a written data model, definitions, and playbooks that every agent reads.
Systems your team owns
A lot of outside help does the list, the research, or the QBR for you, and you buy it again next month. You get the agentic system that does it, with evals and learning loops, so your team can keep improving it after the engagement ends.
Two ways to start
Fixed-scope project
Starts at $5,000. One workflow, shipped and tested, with your team trained on it. The aim is a first working output within a month of kickoff. It's a way to start small and see it work.
Retainer
Starts at $7,500 a month. A build queue worked one workflow at a time, documented in your systems as it ships, and your team keeps what’s built. It's the right fit when there's more than one workflow to ship.