Blog Posts:
The Evolution of Lead Scoring, and Why the Next Version Stops Guessing
By: The Marketing Operations Leader
What if lead scoring stopped guessing what a buyer wants and just asked them? Darrell Alfonso traces lead scoring from the email era through the web and model eras, and argues the next version scores stated intent instead of inferred behavior.
What you'll find inside
- Where scoring has been: email opens, then web and pricing-page visits, then model-based scores built on hundreds of signals, none of which reliably predicted readiness to buy.
- The shift to stated intent: capturing what a buyer actually says they need, such as seat count or a deadline, instead of inferring it from clicks.
- A five-step build: add stated-intent fields, give buyers more places to say what they want, extract intent already sitting in transcripts and emails, route on stated intent first, and compare stated versus inferred signals over time.
The piece hands marketing and RevOps teams a concrete way to rebuild lead scoring around what buyers actually say, rather than another round of tuning a black-box model.
Read the full breakdown here for more perspective on where model-based scoring falls short, plus more input on building stated-intent fields into the funnel.
GTM AI Foundations (Cliff @ Polaris Ops)
What happens after a GTM engineering build ships? Cliff Simon, CEO of Polaris Ops, has advised more than 20 go-to-market organizations in 14 months, and he says maintenance eats a third of the team's time.
What you'll find inside
- A build-versus-buy rule: build only when it moves qualified pipeline and the team can own it long-term, buy everything else.
- A caution on inherited technical debt, including one client whose legacy AI workflows took a full quarter to clean up.
- How to find signals competitors can't buy off a vendor list, illustrated through a supply business that moved the conversation from product pain points to succession planning.
- A DevOps-style structure for RevOps, with GTM engineers centralized under a product owner instead of reporting informally into sales.
The piece leaves you with a practical filter for deciding what a GTM team should build in-house, and a warning about the maintenance cost nobody budgets for.
Read the full article here for more perspective on legacy AI cleanup, plus more input on structuring a RevOps organization around GTM engineering.
The 2027 Territory Planning Guide
By: Uncharted Territory by Gradient Works
What does territory planning look like when it stops being a once-a-year spreadsheet exercise? Hayes Davis lays out a step-by-step guide built for B2B SaaS sales teams heading into 2027 planning season.
What you'll find inside
The guide walks through five stages: aligning on the big strategic questions before touching any data, wrangling the data and analysis that will feed the design, building the initial territory design, gathering feedback and iterating on it with the field, and going live with ongoing support once territories ship. It also covers the geographic, vertical, named-account and hybrid models teams choose between, and how to handle whitespace, account overlap and rep capacity during the build.
You come away with a structured planning sequence to follow instead of starting from a blank spreadsheet, plus a feedback loop for keeping territories current after go-live.
Get the complete guide here for more perspective on the strategic questions to align on first, and more input on gathering field feedback without reopening the whole design.
Podcast Episodes:
Building the AI-Native RevOps Stack with Steve Dinner, VP of RevOps at Owner.com
What changes when a RevOps team builds for AI from the ground up instead of bolting it onto existing workflows? Steve Dinner, VP of Revenue Operations at Owner.com, walks through governing LLM access to Salesforce and treating each workflow as its own small service rather than one monolithic automation.
What you'll hear
- Governing which parts of Salesforce an LLM can touch, and why.
- Building workflows as independent, single-purpose services instead of large automations.
- Adapting sprint planning and managing token spend across the team.
- Preventing reps from quietly building duplicate workflows.
- Using AI to gamify BDR performance without losing the human element.
Listeners come away with a concrete architecture for AI-native RevOps, built around small, governed pieces instead of one large system to maintain.
Listen to the full episode here for more perspective on governing LLM access safely, plus more input on managing token spend at scale.
How to design RevOps before things break. With Arriel Balogun
"RevOps teams take the blame when the data misses a problem, then spend their weeks fighting the same fires." Arriel Balogun, who built her RevOps background at Twilio and LeanData and now consults through Infinity Elevated, makes the case for designing systems before they fail rather than patching them after.
What you'll hear
Balogun focuses on proactive system architecture over reactive firefighting, covering how to build processes that hold up under growth instead of breaking every quarter. The conversation gets into where data reliability tends to fail first, how to catch design gaps before they turn into recurring fires, and what it takes to shift a RevOps team from constantly patching issues to preventing them.
The episode gives a framework for designing RevOps systems proactively, so fewer fires reach the team's desk in the first place.
Hear the full conversation here for more perspective on catching design gaps early, plus more input on building data reliability into the system from the start.
How to Turn Around Stalled Growth with Lou Shipley
By: GTM Science - A show for GTM and RevOps leaders
What actually causes go-to-market growth to stall, and what does it take to reverse it? Lou Shipley, a three-time CEO and senior lecturer at Harvard Business School, tells host Rachael Bueckert how he rebuilt Black Duck's sales operations and scaled the company from $20 million to $90 million in four years.
What you'll hear
- Diagnosing whether a slowdown is a product-market fit problem or an execution problem.
- The "founder trap," where a CEO's role evolves but their responsibilities do not.
- Fixing SQL definitions and pipeline integrity before touching forecasting.
- The "plane model" for developing talent and building distributed leadership at scale.
Discover the full episode here for more perspective on separating product from execution problems, plus more input on fixing SQL definitions before forecasting.
Webinars:
When RevOps AI Agents Break: How to Improve Accuracy Over Time
Webinar with Nooks and Vapi | Tuesday, October 6, 2026, 1:00 PM ET | Speakers: Alex Avila (Nooks), Gerard Martelly (Vapi)
Shipping an AI agent is the easy part. What happens after it starts getting things wrong in production?
What you'll see
- System architecture, fallback logic and output parsing that go beyond prompting.
- Frameworks for deciding when an agent runs autonomously versus with a human in the loop.
- What to measure: accuracy, latency, adoption and performance drift over time.
- Real production failures and the system changes that followed.
Register for the full session here for more perspective on balancing accuracy against speed, plus more input on turning agent failures into fixes.
What to Build, Buy, and Integrate in the Age of AI
Webinar with Airspeed | Wednesday, October 14, 2026, 12:00 PM ET / 9:00 AM PT | Free | Speakers: Tom Andrews and Chad Boersma, Airspeed
When most vendors ship AI features and development costs keep falling, how should a revenue team decide what to build versus buy?
What you'll see
The session covers how AI is changing vendor evaluation beyond the standard features checklist and RFP, what tips the build-versus-buy decision one way or the other today, and why integration matters more once agents need context spread across multiple systems. It also addresses when a self-serve AI tool adds real value versus just adding another tool to manage.
Save your seat for the full session here for more perspective on evaluating vendors beyond feature lists, plus more input on avoiding tool proliferation.
5 Bold Predictions for GTM in 2027 That Will Blow Your Mind
By: RevGenius
Keynote with Goldcast | Thursday, October 15, 2026, 12:00 PM ET / 9:00 AM PT | Free | Speaker: Sangram Vajre, CEO and Co-Founder, GTM Partners
Is product differentiation really shrinking, and does that make go-to-market execution the real competitive edge in 2027?
What you'll see
- AI tool sprawl following the same fragment-then-consolidate path MarTech took.
- Net Revenue Retention becoming the primary growth driver, not just a retention metric.
- Token consumption turning into its own cost-management discipline.
- Product innovation coming from market gaps rather than a predetermined AI roadmap.
The keynote leaves attendees with five specific bets on where GTM is headed by 2027, and a case for treating execution itself as the defensible advantage.
Join the keynote here for more perspective on where AI spend is headed, plus more input on why NRR is becoming the primary growth metric.
