The problem in SaaS isn't bad reps, bad tools, or bad leads, it's latency.
Every SaaS company fights the same invisible tax: revenue latency, the time it takes for data, insight, or process to reach the person who needs it.
It's 10:12 a.m:
An AE is on LinkedIn, finds a perfect prospect, and… opens five tabs: Salesforce, Outreach, ZoomInfo, Notion, Slack.
Ten minutes later, they're still chasing phone numbers, searching old notes, while the deal they should be working on sits idle.
By the time they sync the contact, write a semi-custom email, engage on LinkedIn, and make two dials? 25 minutes are gone. For one lead.
Multiply that by 60–100 activities/day — the math doesn't work unless reps have 30 hours in a day.
That's the reality: every day, sales teams burn hours chasing context across tabs and tools while deals stall and competitors get there first.
Not because reps are bad. Not because tools are missing.
It's because the information, signals, and workflows they need don't reach them fast enough.
This delay compounds across every deal, every day — an invisible tax on pipeline speed and execution. We call it revenue latency. And this latency kills revenue velocity.
The Old Models: Centralized vs. Autonomous
Most SaaS orgs have swung between two pipeline models. Both have clear upsides — and both create latency.
Model A: Centralized Growth Ops
This first model is what you see at companies like Gorgias, Pigment and Rippling, where all non-selling work is handled by the growth ops team, providing reps with qualified pipeline programmatically.
Ops owns the whole pipeline machine: identify → enrich → verify → qualify → route. Manage signals stored in custom objects in the CRM.
The benefit: reps sell, period.
Tier 3 leads or secondary personas? Auto-engaged by Growth. Tier 1 accounts? Routed to reps fully enriched and qualified.
Example: At Augment, reps manage key stakeholders for a given targeted account (CTO, Head of Data Engineering, VP engineering) while every end-user (software engineers) are engaged automatically via campaigns run by the growth team. We can see similar setups at Pigment, known for the sophistication of their GTM.
The trade-off? Ops latency & dependency
If a rep wants to act on their own, they're back to medieval ages: fully manual processes, no email or phone validation, missing data and manual entry into an outreach tool (often bypassing the CRM), creating inconsistent records hygiene or data siloes.
If they don't go manual, they wait, for lists, for stakeholder mapping, for CRM fixes, before they can move.
And if enablement is missing? (read: Unleashing sales potential) — Reps are handed leads they don't even understand.
Model B: Autonomous Reps
Now, the other extreme: give reps a ZoomInfo seat and a Chrome extension stack.
Let them hunt.
The upside: no waiting. Pure autonomy.
The hidden cost: context latency and admin overload.
Reps bounce between Sales Nav → company page → enrichment tools → CRM → sequencing platform.
The hidden cost is even bigger: duplicates in your CRM, messy hygiene, fragmented stack, and so much manual admin that selling becomes only a fraction of their job.
By the time you've synced, written a semi-custom email, engaged on LinkedIn, and made a couple of dials?
25 minutes gone. For one lead.
I've seen reps expected to hit 100 activities/day. The math doesn't work unless they have 30 hours in a day.
What you gain in speed, you lose in execution quality.
Both models solve one latency, but introduce another. We think the point isn't to choose one. With the capacities of LLM, RAG, and automation, there's now a best of both worlds, a system that removes every form of latency, end-to-end.
The Evolution: Centralized Logic, Distributed Execution
The top 1% of teams aren't choosing between models. They're building a third path whereby RevOps build processes and tools upstream but the reps retain sufficient leverage to deploy them on-demand downstream.
RevOps encodes process once: ICP rules, enrichment logic, routing conditions, then distributes it everywhere reps work: Slack Agents, CRM buttons, browser extension.
Reps trigger it on demand, and then receive the output they request with a guaranteed level of quality, without having to wait.
Concrete examples
Deal-Risk Agent
Sitting on top of your pipeline, it flags accounts likely to churn or stall and provide next best actions
Stakeholder Finder Button
Pulls the right contacts instantly. No more "Yeah but our persona changes from one company to another, it picks the best contact for any given company". A second common use case of button is generating an account research from first and third-party data.
Meeting Prep Agent
Surfaces qualification gaps (vs your sales methodology: BANT, MEDDIC), launch lead research on any new stakeholders in the meeting, and brief the reps with full context, in 30 seconds instead of 20 minutes
No tickets. No "I'll get back to you." No excuses. Just leverage, in the flow of work.
From Sales Velocity → Revenue Velocity
Classic sales velocity tracks how fast opportunities turn into revenue (deals × ACV × win rate ÷ sales cycle). Useful—but it starts too late. In 2025, the edge is revenue velocity: the speed your system moves from signal → insight → action across the whole GTM.
Every minute between knowing and doing is compounding friction. Centralized logic + distributed execution compresses that gap, so the entire GTM runs faster, not just the sales stage.
Why Now
Three forces have collided:
Tool sprawl created friction
The GTM stack exploded, but every insight lives in its own silo. Ops spends more time on tickets than on system design.
AI has made orchestration cheap and smart
ICP rules, stakeholder mapping, even deal qualification frameworks can now be encoded into lightweight agents in a week.
Pipeline pressure is brutal
Boards won't fund more headcount. Growth expectations keep rising. Reps need to sell more with less.
Latency went from being an annoying inefficiency to an existential threat. The teams that survive the next cycle will be the ones that engineer revenue velocity into their operating system, and across the funnel.
The New Edge: The GTM Brain
The GTM Brain is simple:
Context layer: All GTM data, first-party, third-party, product, marketing, unified in one governed hub.
Agentic layer: AI agents layered on top, ready to answer any pipeline, account, or deal question.
Packaged insights: Every insight paired with an action, executable instantly, inside the same interface.
AEs: Walk into meetings with the right people and zero blind spots.
CSMs: Spot renewal risks in real time, know the best upsell path.
Marketing: See exactly which campaigns convert to SQLs — and double down instantly.
SDRs: No admin, no guesswork: just high-fit, high-intent accounts with context.
RevOps: Build once, deploy everywhere — Slack, CRM, browser — and get perfect execution without chasing adoption.
Start Small, Scale Fast
Don't boil the ocean. Start with one play your reps run every week. Put it in a button or agent. Let them trigger it on demand. That's your first GTM Brain cell.
In the next generation of GTM, revenue velocity will encapsulate the speed of sales execution, the quality of system orchestration and the latency between a data point or an insight being generated, and an action.
Teams that compress the gap between data, decision, and delivery will compound faster than anyone else. Revenue velocity won't just be a KPI, it'll be the architecture your business runs on.
MaxOct 13, 2025
