Introduction

Artificial intelligence isn’t just eating the software ecosystem — it’s rewriting the rules for how tech companies scale, sell, and serve customers. On the latest episode of The Science of Scaling, host Mark Roberge sat down with Andy Shorkey, Chief Revenue Officer at Writer, to dive into how Writer’s go-to-market motion is evolving in the age of AI, and what it means for modern revenue leaders. 

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From Technical Depth to Go-to-Market Excellence

Andy’s journey at Writer began with a fateful introduction to May Habib (Co-Founder & CEO), a “force of nature” with both deep technical chops and the rare ability to sell and connect. Alongside co-founder Waseem AlShikh, the team saw Writer’s early momentum as an inflection point — a chance to build a platform purpose-built for enterprises, rather than targeting just consumers or single-department use cases.

Why does this matter? Because as Andy points out, today’s CIOs and heads of AI are facing massive demand and overwhelming backlogs. They’re under pressure to scale AI-driven transformation faster than ever, and Writer’s approach is to “abstract away the technical complexity” so organizations can deploy AI agents at scale without spending months (or years) building in-house.

The Enterprise Pivot — and the Secret to Writer’s Success

Early on, Writer’s tools focused heavily on marketing and content teams — think brand voice consistency and compliance. But as the platform matured, the company executed what Mark calls a “zoom out pivot”: expanding beyond narrow initial use cases to support a wide range of enterprise needs, from content supply chains to legal review, financial services, and beyond.

The secret sauce? Deep customer success and a relentless focus on ROI. As Andy puts it, Writer gravitates toward mission-critical use cases where they can “defend the ROI and the value that’s being delivered.” The result: happy customers who “scream from the rooftops” about the outcomes they’re achieving, making it easier to build a moat in a crowded market — even as foundational AI models and incumbents look for ways to catch up.

Building for Complex Decision Cycles

One challenge that comes up repeatedly: as deals move up-market, you’re selling not just to one champion, but to a deeply complex decision-making unit (DMU) that spans line-of-business leaders and technical executives like CIOs. Andy highlights a recurring tension — between, say, CMOs (who hold budgets and want speed) and the centralized IT organizations (who need to standardize, manage risk, and ensure compliance).

To win these deals, the sales playbook must evolve. Writer’s approach: “everyone demos” the product, and new hires — regardless of role — get deeply hands-on from day one. Sellers need versatility, the ability to evangelize, and enough technical fluency to inspire trust in both business and technical stakeholders.

AI Inside the Go-to-Market Motion

Of course, Writer doesn’t just build AI — they use it to reinvent their own sales process. Andy details how everything from prospect prioritization to account planning and legal reviews are now powered by AI agents inside Writer’s platform:

• ICP Targeting: AI surfaces the most promising accounts and decision-makers, using warm signals and real-time data from LinkedIn and elsewhere.
• Meeting Prep: Reps use AI assistants to build out tailored points of view, solution maps, discovery questions, and executive scripts — fully customized for each account.
• Contracting and Legal: AI agents handle the lion’s share of NDA processing and contract review, dramatically shortening sales cycles and freeing up legal teams for more strategic work.

Key Takeaways for Scaling in the Post-AI Era

Whether you’re in sales, marketing, or operations, the lessons from Andy and the Writer team are clear:

• Get technical: even if you’re not an engineer, go play with the tools, experiment, and carve out time to automate your own work.
• Start narrow, then zoom out: land with strong use cases and happy customers, then expand to broader enterprise needs.
• Adapt your sales motion: selling to complex enterprises means evolving your hiring, enablement, and product fluency.
• Leverage AI internally: if you’re building AI for customers, you better be using it to drive your own growth, too.

As Mark puts it, the ultimate moat in the AI era is the ability to drive real, repeatable business value at scale — especially in messy, highly regulated enterprise environments. If you can pull that off, you’re not just riding the AI wave — you’re helping to steer it.

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Note: The insights shared in this podcast were initially distilled through advanced AI summarization technologies, with subsequent refinements made by the writer and our editorial team to ensure clarity and engagement.

About "The Science of Scaling" Podcast

Every week during a season, host Mark Roberge—co-founder and Managing Director at Stage 2 Capital and a senior lecturer at the Harvard Business School—interviews some of the tech industry's most successful and renowned leaders and managers in the areas of sales growth and Go-to-Market strategy. This is a HubSpot for Startups original podcast, and part of HubSpot's Podcast network. It's available on Apple, Spotify, and anywhere you get podcasts.