The go-to-market stack of the future

The legacy GTM stack is collapsing under the weight of AI. Buyers no longer fill out forms, they launch their journeys in ChatGPT, Perplexity, or Google AI Overview, then casually click through to your website. Yet your CRM, your marketing automation, and your form builder see nothing. Those anonymous, high-intent visitors slip through the cracks, never entering your pipeline, never receiving your outreach.

The traditional sales funnel assumed a linear journey: awareness, consideration, decision. But AI has shattered this model. Today's buyers conduct research across multiple AI platforms, consume synthesized information, and arrive at your website already educated about your solution. By the time they're ready to engage, they've completed 70% of their buying process in invisible channels your current stack can't monitor.

This creates three fundamental breakdowns in the modern GTM motion: attribution gaps, data staleness, and engagement delays. Each represents a massive revenue leak that compounds as AI adoption accelerates.

The attribution black hole

Your prospects are finding you through AI-powered search, but your analytics see nothing. When someone searches "AI sales prospecting tools" in ChatGPT, gets a summary mentioning your company, and clicks through to your site, Google Analytics labels them as "direct traffic." The attribution chain is completely severed.

This isn't just a measurement problem; it's a strategic blindness. You're optimizing content for AI engines without knowing which pieces drive actual traffic. You're investing in thought leadership without seeing which topics generate qualified visitors. You're running dark, making decisions with incomplete data.

Split.dev solves this by providing attribution infrastructure specifically built for AI-powered search. It tracks the complete journey from AI citation to website conversion, revealing the invisible funnel that traditional analytics miss. For AEO and GEO teams, it's the difference between shooting in the dark and precision targeting.

The data decay problem

Static data is dead data. Your CRM is filled with point-in-time snapshots that grow staler by the day. While you're still cold-emailing someone based on their job title from six months ago, they've been promoted, changed companies, or launched a new initiative that makes them an even better prospect.

Traditional enrichment tools offer one-time data appends. They're useful for cleaning up your database, but useless for staying current with the rapid pace of business change. What you need is living data that updates itself based on real-world signals.

Origami Agents provides continuous intelligence through autonomous research agents that monitor SEC filings, press releases, LinkedIn updates, and company announcements. When a prospect's startup announces a funding round, gets acquired, or hires a head of sales, your CRM updates automatically with context about why now is the perfect time to reach out.

This transforms your pipeline from a static list into a live intelligence feed where every record includes the latest "why now" insights that make outreach relevant and timely.

The engagement lag

Speed matters in sales, but most GTM stacks introduce delays at every stage. A high-intent visitor converts on your website, creates a ticket in your CRM, gets assigned to an SDR, waits for manual qualification, and finally receives outreach. Often this happens days later when their interest has cooled.

AI eliminates these delays through real-time qualification and instant engagement. The moment an ICP-matched visitor converts, they're automatically enrolled in personalized nurture sequences. AI SDRs handle initial qualification through chat and voice, working around the clock to book meetings and pass qualified opportunities to human reps with full context.

This compression of the sales cycle, from days to minutes, is what separates AI-first companies from those still running legacy processes.

The integrated AI-first stack

The future GTM stack isn't about replacing everything at once. It's about connecting AI-powered tools that work together seamlessly:

Attribution infrastructure captures and tracks visitors from AI search engines, providing visibility into channels that traditional analytics can't monitor.

Continuous intelligence keeps your data fresh through autonomous research agents that monitor buying signals and trigger updates in real-time.

Instant qualification uses AI SDRs to engage prospects immediately, qualify leads through natural conversation, and book meetings automatically.

Dynamic personalization delivers contextual experiences based on how prospects arrived, what they've consumed, and where they are in their buying journey.

Each component amplifies the others. Better attribution improves targeting. Fresher data enables more relevant outreach. Faster qualification increases conversion rates. The compound effect creates an unfair advantage that widens over time.

The strategic transformation

This isn't just about adopting new tools. It's about fundamentally rewiring how revenue teams operate:

Sales reps evolve from hunters to closers. Instead of prospecting and qualifying, they focus entirely on advancing qualified opportunities. AI handles the research, qualification, and scheduling.

Marketing becomes an intelligence operation. Every visitor generates data, every interaction reveals intent, and every signal informs strategy. Marketing teams shift from lead generation to revenue intelligence.

RevOps becomes systems orchestration. Rather than managing data flows between disconnected tools, RevOps focuses on optimizing the integrated AI ecosystem for maximum revenue efficiency.

Companies that make this transition don't just improve their existing processes; they operate at a fundamentally different level. They see opportunities others miss, engage prospects others can't reach, and close deals others don't even know exist.

Making the transition

The AI-first GTM stack isn't a future concept. It's available today. The question isn't whether to adopt these tools, but how quickly you can implement them before your competitors do.

Start with visibility. Deploy attribution infrastructure to see who's finding you through AI search engines. Then add intelligence through autonomous research agents that keep your data current. Finally, implement AI qualification to compress your sales cycle and improve conversion rates.

The companies that move first will build an insurmountable advantage. While their competitors are still running on legacy infrastructure, they'll be operating at AI speed: seeing more opportunities, engaging faster, and closing more deals.

Your buyers have already shifted to AI-powered research and decision-making. The only question is whether your GTM stack will keep up or fall behind.