The harder question is: Who should you invest in next?

That question sits at the center of my conversation with Kenneth Fox, CTO and founder of ChannelScaler. Kenneth has spent his career in channels and partnerships, and his perspective combines the technology side of partner management with the practical realities of running partner programs.

We talked about AI, co-selling, technology alliances, partner journeys, measurement, and why human relationships remain essential even as more of the partner experience becomes automated.

One idea came through repeatedly: technology is most valuable when it helps partner teams focus their limited resources on the activities and relationships most likely to produce results.

The Channel Has Become a Complex Ecosystem

Traditional partner program fundamentals aren’t going away. Kenneth still sees incentives, marketing, tiering, rebates, deal registration, portals, and content management as table stakes.

What has changed is the environment around them.

Partner ecosystems now involve many different types of partners and increasingly complex sales motions. A single enterprise opportunity might involve a vendor, a reseller, a services partner, and potentially others.

That makes co-selling much more than simply sharing an opportunity.

“The channel has become a very complex ecosystem of partners.”

Kenneth described the challenge of coordinating multi-partner deals where each participant may be operating from a different CRM and even using different names for the same end customer.

The critical questions become remarkably operational: Who owns which part of the deal? What’s the next step? Who owns that step? When is it due? And what can the vendor do to move the opportunity forward?

For partner leaders, that level of visibility becomes increasingly important as ecosystems expand.

AI Should Make Partnering Easier

Kenneth divides ChannelScaler’s application of AI into three broad areas: reducing friction and improving ease of doing business, removing operational obstacles through automation, and generating better insights.

The first two can address some very practical problems.

An AI agent can help determine whether a deal being registered may already exist. It can surface relevant content during deal registration. It can automate elements of MDF claims and flag transactions that require human review.

The objective isn’t simply to add AI to a partner platform. It’s to remove work.

Kenneth sees that eventually changing the partner experience itself.

“It will become an agentic-led experience for partners and vendors.”

Instead of requiring partners to navigate through a portal looking for what matters, an agent can potentially surface what needs attention: an open deal, an expiring fund request, a rebate claim, or a certification required to maintain status.

That connects directly to one of Kenneth’s core principles:

“Ease of doing business is the single biggest pain point in the channel.”

And his conclusion is equally direct:

“If you are the vendor that is easiest to work with, you will be the vendor that wins.”

Build What Differentiates You - Partner for the Rest

As CTO, Kenneth also has to make a decision familiar to many technology companies: What should we build ourselves, and where should we partner?

His framework starts with knowing what the company is actually good at.

“We know what we’re good at, and we stick to, you know, our lane.”

ChannelScaler uses technology alliance partners where capabilities fall outside that lane. Kenneth cited XTRM for payments, Structured for TCMA, and PartnerTap for identifying ecosystem whitespace. The goal is to integrate complementary capabilities rather than recreate technology that another company already does well.

In other cases, such as co-sell functionality, Kenneth believes the capability sits directly within ChannelScaler’s core area of expertise, making internal development the faster route.

There isn’t one universal build-versus-partner rule.

Each capability has to be evaluated on its own merits.

Find the Next 10 Partners

Perhaps the most interesting application of AI in our conversation was partner prioritization.

Most channel leaders can identify the partners generating the majority of their revenue. Kenneth argues that AI can help answer a more valuable forward-looking question: Who are the next 10, 20, or 30 partners worth investing in?

ChannelScaler looks across attributes including revenue, deal volume and value, certifications, participation in programs, end customers, geographies, training, and other signals.

“I look at the attribution of my best partner or my best 100 partners, and now I can use AI to scrub that against the next thousand to figure out actually who’s the next best 10 I should focus on.”

Once those partners are identified, Kenneth recommends putting them on a targeted partner journey.

And importantly, a journey isn’t synonymous with onboarding.

It might be designed for a brand-new partner, a mature strategic partner, or a group of high-potential partners. One example Kenneth described was a revenue journey where the vendor and partner establish specific growth objectives, net-new-logo targets, leads, marketing investments, and next steps.

That’s a fundamentally different approach from giving every partner essentially the same program experience.

Measure Engagement, Not Just Enrollment

Kenneth also challenges one of the most common partner-program vanity metrics: total partner count.

“You have 500 partners. Well, guess what? You don’t really have 500 partners.”

If only 110 of those partners have actually engaged, the other 390 shouldn’t automatically be treated as productive members of the ecosystem.

Measurement should instead reveal what partners are doing, how programs are performing, where processes are slowing down, and which behaviors correlate with success.

Kenneth’s principle is simple:

“You can only manage what you measure.”

The bigger opportunity is to connect measurement to action. Identify the attributes of successful partners. Find other partners with similar potential. Put them on a deliberate journey. Track the commitments on both sides. Then continuously adjust.

AI Doesn’t Replace the Relationship

For all the discussion about AI and automation, Kenneth was unequivocal about what technology doesn’t replace.

“It’s not a human relationship. And certainly when you move into the enterprise and you’re doing big deals... people buy off people.”

That may be the most important distinction for partner leaders.

The opportunity isn’t to automate partnering.

It’s to automate enough of the administrative burden, analysis, and process friction that partner professionals can spend more of their time doing what technology still can’t do for them: building the relationships that move the business forward.

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One of the clearest themes from the conversation was this: finance leaders are not resisting AI. They simply want transparency, accountability, and confidence in the outputs.

For partner leaders, ISVs, and ecosystem builders, that creates a very different opportunity than the generic “AI transformation” messaging dominating the market right now.

Dan framed it around trust.

“What finance and operations professionals really want is confidence in the tools that they’re deploying are doing exactly what they are expected to do.”

That requirement shapes how Sage is building both its AI capabilities and its broader partner ecosystem.

AI Adoption in Finance Requires Transparency

Dan pushed back on the idea that finance organizations are inherently resistant to innovation.

Instead, he described a customer base that is willing to experiment with AI - as long as the systems remain explainable.

“It’s not that they don’t want to experiment. It’s that they want to know when they experiment, there’s going to be a good result.”

That distinction matters.

Sage is positioning its AI capabilities around visibility into how outputs are generated, rather than treating AI as a black box. Dan described how Sage customers can inspect the reasoning behind cash flow predictions, financial close recommendations, and other AI-generated outputs.

“It’s not a black box. It’s actually transparent. You can see into how the steps were determined.”

That transparency extends into Sage’s Copilot capabilities, where users can interrogate how the system arrived at a recommendation or prediction.

For CFOs and finance teams, that creates auditability and confidence. For partners, it creates an environment where AI adoption becomes easier to operationalize with customers.

The Partner Opportunity Around AI Enablement

One of the more interesting parts of the conversation was how Sage views AI through the lens of partner enablement, not just customer productivity.

Dan talked about how Sage is helping partners accelerate implementations and reduce deployment friction.

“One of the most important things for a partner is to have a pipeline of new business being delivered.”

He connected that directly to Sage’s recent acquisition focused on accelerating Intacct migrations from systems like QuickBooks.

The idea is straightforward: if Sage and its partners can reduce migration complexity and implementation timelines, partners can onboard more recurring revenue customers faster.

That’s an important point for ecosystem leaders.

AI is not only being positioned as a feature set for end customers. It is increasingly becoming an operational multiplier for partners themselves.

Why Open Ecosystems Still Matter

Dan was also very clear that Sage does not believe a single company can build every workflow or every vertical solution customers need.

That philosophy continues to shape Sage’s ISV strategy.

“We believe at our very core that we need to be open. We know there’s no possible way that we could invent every piece of technology that solves for every vertical, every micro vertical, every workflow.”

Instead, Sage is leaning heavily into ecosystem extensibility.

The company works with a broad range of ISVs integrating into Sage platforms, while also creating tighter strategic relationships in priority verticals like nonprofit, healthcare, manufacturing, distribution, and financial services.

In some cases, that means co-development. In others, it means packaging and selling integrated solutions together.

The more interesting extension of this strategy is how Sage is now applying the same thinking to AI agents.

AI Agents Become the Next Ecosystem Layer

Dan described Sage’s new AI developer program and marketplace as the next evolution of the platform ecosystem.

The goal is to allow developers and partners to build highly specialized agent workflows directly into the Sage experience.

That includes micro-vertical use cases where partners may have unique expertise, proprietary workflows, or integrations that only exist within a narrow industry segment.

“Agents are going to be a new mode of delivery of capability.”

Rather than treating AI agents as external tools, Sage is embedding them directly into the ERP workflow and user experience.

Partners can build agents that appear inside the same Copilot interface Sage users already interact with.

Just as importantly, those agents inherit Sage’s authentication and security framework.

“Those agent capabilities are protected by the same kind of authentication capabilities and controls that we do for our users.”

That creates a potentially important differentiator for enterprise AI adoption.

Instead of customers stitching together disconnected AI tools with inconsistent governance, Sage is positioning AI agents inside an existing operational and security framework.

The Bigger Ecosystem Signal

One of the broader signals from this conversation is how platform companies are evolving their ecosystem strategies in the AI era.

Historically, ERP ecosystems were largely built around integrations and workflow extensions.

Now, they are increasingly becoming marketplaces for intelligent workflows, embedded agents, and verticalized AI expertise.

That creates new opportunities for ISVs, SIs, and developers that deeply understand a particular industry process or operational workflow.

The winners may not simply be the companies with the largest models or most generic AI capabilities.

They may be the ecosystem partners that can combine trusted data access, workflow expertise, and operational context into highly specific business outcomes.

And as Dan emphasized throughout the conversation, trust remains central to that equation.

“We provide those controls, those guardrails, those are in place, which provides real value for customers because they know that they’re protected by that same set of standards that we hold ourselves accountable to.”

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The conversation focused on operational execution - how to help partners scale faster, create industry-specific customer outcomes, and build durable businesses together.

One theme came through consistently: Sage is designing its ecosystem strategy around partner growth, not just partner participation.

Building a Partner Business

Sperry framed Sage’s approach around a simple idea: if partners grow, Sage grows alongside them.

“How do we remove the barriers to growth for the partner? That’s an incredible kind of focus.”

Rather than viewing partnerships strictly through pipeline contribution or resale metrics, Sage appears to be thinking more holistically about partner economics and operational scalability.

Sperry described investments in tooling, acquisitions, AI capabilities, and co-sell motions as intentionally designed to help partners execute faster.

“All of it is designed to be executed through the lens of partner.”

That philosophy extends into how Sage structures its go-to-market organization. According to Sperry, Sage’s North American partner organization works closely alongside partner sales teams in the field, helping partners add sales capacity, industry expertise, and execution support.

Co-Sell as Staff Augmentation

One of the more interesting operational models discussed was Sage’s approach to co-selling.

Sperry explained that Sage account executives can effectively operate as an extension of partner sales teams.

“What that does is it actually gives partners some additional sales capacity.”

For smaller or growing partners, this becomes a meaningful scaling mechanism. Instead of waiting until they can independently fund new headcount, partners can leverage Sage resources to accelerate pipeline development and industry expansion.

Sperry described this as a practical way to help partners grow faster while reducing operational friction.

“If they want to go into a particular industry, we can add a little bit of industry knowledge.”

That support can include:

• Additional sales coverage

• Industry specialization

• Mentorship for new partner reps

• Joint customer engagement

• Pipeline acceleration

Importantly, she framed this as a shared investment model.

“We’re investing together.”

That alignment matters because many partners are balancing hiring decisions, utilization targets, and services capacity while simultaneously trying to grow recurring revenue practices.

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The Power of Micro-Vertical Expertise

Another major theme was Sage’s focus on industry depth.

Sperry explained that while Sage serves many broad industries, partners often go even deeper into highly specialized micro-verticals.

“We have over 50 micro verticals that we can kind of talk about.”

This is where the ecosystem becomes a force multiplier.

Partners combine:

• Sage technology

• Industry expertise

• Specialized services

• ISV integrations

• Workflow customization

The result is highly tailored customer experiences that are difficult for generalized providers to replicate.

Sperry also highlighted how partners frequently overlap across multiple ecosystem motions simultaneously. A reseller may also build proprietary technology. An outsourcing partner may also operate as an ISV.

That flexibility creates broader customer coverage and more specialized outcomes.

“One partner may not solve that challenge exactly the same way.”

For partner leaders, that observation matters. Ecosystems increasingly win through combinations of expertise rather than through single-vendor standardization.

Trusted AI Requires Trusted Partners

AI was a central topic throughout Sage FUTURE, particularly around trusted AI for finance and accounting workflows.

Sperry emphasized that Sage’s long history in accounting gives the company a strong foundation for responsible AI adoption.

“We get to build on the foundation of not just strong strength in accounting, but also bringing forward that trusted AI.”

She also made an important point about the role partners play in AI adoption.

For many customers, the partner is the first trusted advisor they turn to when evaluating how AI should be applied to their business.

That’s why Sage is involving partners directly in AI development initiatives, including its agentic AI developer program.

“They’re building AI with us.”

Sperry referenced partners already building agents and AI-driven solutions on top of Sage capabilities.

This reflects a broader ecosystem trend: hyperscalers and platform companies increasingly need partners not just to sell AI, but to operationalize it within specific workflows and industries.

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Partners are still at the center of how businesses win.

“The channel is one of the most important things because our partners are the ones that have the deepest industry expertise and are closest to customers that can really solve their unique, unique business challenges.”

AI may accelerate execution, but it doesn’t replace the need for domain expertise, customer proximity, and trusted advisory. In fact, it amplifies it.

Cutting Through AI Noise with Real Value

One of the biggest challenges partners face today is separating signal from noise.

There’s hype everywhere - startups, tools, promises of automation. But Sage is pushing partners toward something more grounded: delivering real, measurable value to customers.

“There’s a lot of hype on AI, there’s a lot of startups, there’s a lot of noise in the market. And so how do we help our partners sort of cut through that noise? Delivering real value with AI to our customers.”

For SMB customers in particular, the bar is high. These are financial systems. Accuracy and trust are non-negotiable.

“AI has to be right a hundred percent of the time in this space and SMBs shouldn’t expect anything less.”

That requirement fundamentally shapes how partners need to approach AI - not as experimentation, but as production-grade capability tied directly to business outcomes.

The AWS + Sage Strategy: Enabling the Ecosystem

A major announcement at the event was Sage’s strategic collaboration with AWS. But this wasn’t framed as just a technology partnership - it’s an ecosystem play.

The goal is to enable partners to build, extend, and monetize solutions on top of Sage’s platform using modern AI infrastructure.

Three priorities stand out:

• Enable ISVs and builders to create extensions via an agentic marketplace

• Remove friction from customer migration to modern cloud environments

• Deepen co-sell collaboration across Sage, AWS, and partners

The intent is clear: reduce barriers, accelerate adoption, and create new revenue opportunities for partners.

“We want to remove the complexity. We want to remove the financial risk… and help our partners make that move with our customers faster.”

This is less about incremental improvement and more about unlocking a new phase of ecosystem-driven growth.

A Defining Moment for Partners

O’Hara was explicit about timing. This is not a “wait and see” moment.

“The time is now. The time is to really focus on making sure that you’re bringing the best delivery, the best service, the best advisory to your customers.”

The partners who commit early - especially in areas like agentic AI and modern finance workflows - will have a structural advantage.

At the same time, Sage is signaling that it intends to bring the entire ecosystem along, not just a subset of leading partners.

PwC and the Shift in the SI Business Model

One of the most important signals came from Sage’s announcement with PwC.

The core idea: use AI to dramatically reduce implementation timelines - from months down to a fraction of that - and shift value toward higher-level services.

“Reduce implementation time… and shift the value of the dollars that customers are spending, not on the time it takes for the implementation, but the value we’re going to get on these integrated workflows.”

This represents a fundamental shift in how system integrators operate.

Historically, revenue was tied heavily to implementation effort. But in an AI-driven world, that model starts to break down.

“Why am I paying these billable hours for something that should be easy to run and go and help me?”

Instead, partners move up the stack:

• Advisory services

• Solution design

• AI-driven innovation

• Ongoing optimization

“My billable hours aren’t going to go away… but the value I’m bringing to customers is so much higher.”

For partners willing to evolve, this is not a threat - it’s an expansion of opportunity.

From Implementation to Lifetime Value

Another key shift is how partners think about customer relationships.

In a cloud and AI-driven world, success isn’t defined by implementation - it’s defined by ongoing adoption, usage, and impact.

“You are now a strategic advisor in that business… you’re going to stay, you’re going to retain, you’re going to grow that customer.”

This changes the economic model:

• Less focus on one-time projects

• More focus on lifetime customer value

• Greater emphasis on retention and expansion

Partners who lean into this transition can build more durable, scalable businesses.

The Unique Strength of the Sage Ecosystem

After six months in the role, O’Hara highlighted something she sees as distinctive about Sage.

“Partners are our strategy. It’s not afterthought, it’s not an add on, it is the ecosystem of how we’re going to make this future win together.”

That level of commitment shapes everything - from product direction to GTM strategy.

It also creates a foundation for long-term trust and collaboration, including multi-generational partner relationships.

But even within that strong foundation, partners are asking for clarity.

How do we win in this next phase?

How do we monetize AI?

How do we evolve our business models?

Those are the questions Sage is now focused on helping answer.

Final Thought

The biggest takeaway from this conversation is not about AI itself.

It’s about the role of partners in an AI-driven market.

AI will change how solutions are built, delivered, and monetized.

But the partners who understand customer needs, bring industry expertise, and deliver real outcomes will only become more important.

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Rajiv Batra challenges that assumption directly.

“A lot of times when we work with GSIs… there is a notion that it’s more focused on process consulting… I will say that’s not fully true.”

Instead, GSIs are increasingly central to building differentiated, industry-specific solutions. The real value is not just delivery - it is co-creation.

Start with Industry, Not Technology

One of the most important shifts Rajiv describes is where solution building begins.

Not with products. Not with features.

But with industry patterns.

“Pick an industry… focus on what exactly are the common patterns which we are seeing… the challenges our customers are facing.”

GSIs bring decades of domain expertise across healthcare, financial services, manufacturing, and beyond. That knowledge becomes the foundation for building solutions that actually resonate.

Google Cloud and ISV partners brings the platform and technology.

GSI Partners bring the context.

Together, they build something neither could deliver alone.

The Blurring of ISV and SI Roles

One of the most interesting dynamics in the conversation is how traditional categories are breaking down.

“The lines are blurred now.”

GSIs are no longer just implementers. They are building IP, assembling multi-vendor solutions, and packaging repeatable offerings.

At the same time, platforms like Google Cloud are leaning heavily into ecosystem orchestration.

The result is a more connected, interdependent model where:

• ISVs contribute product innovation

• GSIs contribute industry solutions

• Platforms enable scale and distribution

The differentiation comes from how well these pieces are integrated.

AI Is Changing How Partnerships Operate

Rajiv makes a clear distinction when talking about AI.

The real transformation is not about automation. It is about moving from data to insight to value.

“The real power… is not about the capture of data… that’s the starting of the journey.”

This shows up in two critical areas.

1. Internal Productivity and Decision Making

Rajiv describes using AI as a “chief of staff” to prioritize work, summarize information, and guide daily execution.

“Gone are the days where I start my day with a cluttered inbox… today, I start my day talking to my AI chief of staff.”

This is not just efficiency - it is focus.

2. Transforming Core GTM Motions

More importantly, AI is reshaping how partners plan and execute together.

Traditional joint business planning relied heavily on:

• Account mapping

• Territory alignment

• Historical relationships

That model is being replaced.

“We have moved away from spending time on data gathering to alignment on scalable and joint solutions.”

Instead of asking “where do we sell?”, the question becomes:

“What solutions can we scale together?”

From Pitch Decks to Live Demos

Another major shift is how partners engage customers.

The old model centered on presentations.

The new model is experiential.

“No more are the days where I’m basically getting into a meeting… nowadays, it’s not PPT… we run through the demo.”

This is a meaningful change.

Rather than describing value, teams are showing it in real time.

And increasingly, those demos are generated dynamically using AI - tailored to specific industries, use cases, and customer challenges.

Co-Sell Is Not a Standard Playbook

One of the most important takeaways is how Rajiv frames co-sell with GSIs.

“CoSell with GSI partners… is a very unique, tailored motion.”

Why?

Because GSIs are not operating at the transactional level. They are embedded with customer leadership, helping shape long-term transformation.

That changes everything about how co-sell works.

The motion starts with:

• Deep industry segmentation

• Specific problem definition

• Pre-built or demo-ready solutions

From there, execution becomes a three-way alignment:

• Partner

• Platform seller

• Partner ecosystem team

“There is nothing called… partner source, Google source… it’s truly about co selling to the end customer together.”

Measuring What Actually Matters

Measurement is another area where Rajiv pushes beyond conventional thinking.

Yes, traditional metrics still matter:

• Influenced revenue

• Bookings

• Certifications

But they are not enough.

“Looking at either of these in silos is actually… a wrong approach.”

Instead, Google evaluates partners holistically across two dimensions:

1. Current Performance

Revenue impact, pipeline, and capability

2. Future Potential

Executive alignment, joint planning, and co-build initiatives

The combination of both determines true partner value.

The Role of Leadership in Scaling Partnerships

Finally, Rajiv shares a simple but powerful philosophy for leading partner teams.

“You run your business… partnership as your core business.”

His focus is:

• Providing data and insights

• Acting as an unblocker

• Helping prioritize what matters

In a fast-moving environment - where partners, products, and customers are all evolving simultaneously - clarity becomes a competitive advantage.

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It’s intelligence embedded directly into partner teams’ workflows.

In this episode of Inside Partnering, I spoke with Abhisheikh Lahoti, Director, AWS Marketplace and Partner Services and Jessica Rudy, Partner Experience Leader at AWS.

Jessica and Lahoti help unpack what AWS is building with Partner Central Agents - and why it has the potential to fundamentally change how partners operate, sell, and scale.

The Core Problem: Fragmentation Slows Everything Down

For years, partners have faced a familiar challenge:

• Fragmented data across systems

• Siloed expertise across teams

• Manual coordination across organizations

As Lahoti puts it:

“If you’re working across organization boundaries… fragmented data, siloed expertise, just the manual coordination… slows things down.”

The result?

Slower deals.

Missed opportunities.

And a heavy reliance on a small group of “AWS experts” inside partner organizations.

From Bottlenecks to “Expertise on Demand”

The shift AWS is making is simple in concept, but powerful in execution:

Move intelligence from centralized teams into the hands of every seller.

“Partners get guidance when they need… imagine you’re getting recommendations on when AWS will give you incentives.”

Instead of relying on:

• Deal desks

• Partner ops teams

• Internal experts

Sales reps can now access:

• Funding recommendations

• Sales plays

• Next-step guidance

Directly inside their workflow.

Whole Org Activation - Not Just Alliance Teams

One of the most important ideas in the conversation is what Jessica calls “whole org activation.”

Historically, partnerships have been concentrated in a small group:

• Alliance leaders

• Partner managers

• Specialists

Everyone else?

They rely on second-hand knowledge.

“People need the information at the moment that they need it… expecting everybody to absorb all of this… is a little untenable.”

This leads to a predictable pattern:

• Create enablement programs

• Build internal processes

• Add operational layers

But those layers become bottlenecks.

Agentic workflows change that by pushing intelligence directly to:

• Field sellers

• Account teams

• Customer-facing roles

  ---

Deal Velocity Becomes the North Star

At the center of all of this is one metric:

Deal velocity.

AWS is using agents to compress what used to take weeks into minutes.

“You’re actually showing up in front of customers in a much better prepared fashion… now this is possible in minutes.”

That preparation includes:

• Customer context and industry insights

• Objection handling

• Co-sell strategy

• Validation criteria

And it doesn’t stop there.

From Static CRM Updates to Continuous Intelligence

One of the more transformative capabilities discussed is how agents interact with live deal activity.

“You just need to… upload that recording… it’ll automatically… add next steps… and you don’t need to go into the CRM again.”

This represents a major shift:

From manual CRM updates → to automated deal progression

Instead of:

• Logging notes

• Updating stages

• Coordinating internally

The system:

• Analyzes conversations

• Identifies risks and blockers

• Recommends next actions

All in real time.

Simplifying Complexity Without Losing Flexibility

Funding programs are a great example of the tradeoff AWS is trying to solve:

• Simplicity vs flexibility

• Standardization vs innovation

“We want it to be really simple, but… we don’t want to stop finding opportunities to fund a new strategic engagement.”

Agents allow AWS to:

• Maintain a complex, evolving system

• While presenting a simple interface to partners

That’s a critical unlock.

The Bigger Vision: Expanding Beyond the Deal

While much of the focus today is on pipeline and deal execution, the roadmap goes further:

• Top-of-funnel campaign generation

• Account planning

• Personalized sales plays per lead

• Partner upskilling and validation

• Migration acceleration

The goal?

End-to-end lifecycle support.

“We wanna move more upstream… account planning and driving top of funnel campaigns… at scale through agents.”

Lowering the Barrier for New Partners

One of the most overlooked implications is how this impacts early-stage partners.

“We’re really trying to accelerate that time to activation… so that partners see value… right out of the gate.”

Historically, success with AWS required:

• Relationships

• Experience

• Institutional knowledge

Now, much of that can be:

• Guided

• Accelerated

• Embedded

A Shift in How We Think About Partnerships

Stepping back, this is about a shift in operating model and really transforming the partner engagement model when working with AWS.

“Everything we’re trying to do is allow that convergence to happen… and make the most of that convergence.”

Jessica describes this as convergence - bringing together:

• Data

• Teams

• Systems

• Workflows

Without requiring rigid standardization.

Final Thought

For partner leaders, the takeaway is clear.

AWS is delivering intelligence embedded in execution.

And the organizations that adapt fastest to this model will have a significant advantage.

Leave a comment

🎙️ Inside Partnering is a podcast for ecosystem builders, alliance leaders, and the people shaping the future of partnerships.

Let’s build the future of partnering - together.

📌 If you found this post helpful, would you please consider restacking it and sharing it with your audience? This spreads the word and keeps me interviewing and sharing content that will help you grow your partnership business and career.

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Partnerships are foundational to how modern cloud platforms deliver value to customers.

In this episode of Inside Partnering, Shankar shares how Google Cloud approaches ISV partnerships - from joint business planning and co-sell execution to the role of marketplace and AI in shaping the next generation of ecosystems.

Her message is clear. Partnerships are evolving from opportunistic relationships to deeply integrated go-to-market motions.

From “Partners, Who?” to Embedded in Every Account Plan

Shankar joined Google Cloud about eight years ago after spending a decade working in the Cisco ecosystem.

At the time, cloud partnerships were still early.

“I remember talking to sales teams and we were like, partners, who? It was so early at that time for cloud to be thinking about partners.”

Today, the picture is very different.

Partners are now embedded in Google Cloud’s sales and account planning processes.

“Partners are absolutely ingrained in every single account plan and business plan that our direct sellers have.”

That shift required more than enthusiasm for partnerships. It required structure.

Partner programs, incentives, and enablement have become the mechanism that transforms the intent to partner into a repeatable system.

The Three Pillars of a Successful ISV Partnership

Shankar describes Google Cloud’s ISV partnerships through three core motions.

• Co-build

• Co-marketing

• Co-sell

Each ISV partnership includes a joint business plan that outlines how those three pillars will work together.

“There has to be the co build, there has to be the co marketing, and there has to be a co sell.”

The goal is to create solutions that neither company could deliver alone.

“We’re always with ISVs chasing that better together story. What is that 1 plus 1 equals 3?”

When the partnership works, the combined solution solves a customer problem more effectively than either product independently.

That outcome becomes the North Star for the partnership.

Quality Over Quantity in the Partner Ecosystem

One of the challenges of ecosystem strategy is deciding how broadly to expand the partner base.

Shankar says Google Cloud has become more selective.

“Our core focus is going deeper with a more select group of partners where we can have a material impact.”

That does not mean ignoring innovation.

In fast-moving areas like AI, new partners are constantly emerging. The strategy is to balance structure with agility.

Google Cloud supports established partners while remaining ready to identify emerging companies that may become key ecosystem players.

Marketplace as a Strategic Differentiator

One of the most interesting shifts Shankar describes is how Google Cloud thinks about marketplace.

Marketplace is no longer viewed simply as a transaction layer.

“We don’t want marketplace to be a transaction vehicle anymore. We want it to be a strategic differentiator.”

That shift changes how partnerships are structured.

Joint business plans increasingly focus on how Google Cloud can help partners:

• accelerate deals

• increase deal size

• source new opportunities

Shankar’s team now has compensation tied to generating opportunities for ISV partners.

“My team’s compensation has a component where they have a target to source opportunity for our ISVs.”

In other words, the hyperscaler is expected to actively help drive partner revenue.

The Evolution of the Partner Sales Role

One of the biggest changes in Google Cloud’s ISV organization is how the partner sales team is built.

Early on, the team hired primarily for alliance experience.

That has evolved.

“Our hiring has evolved significantly. Hire for folks with direct sales acumen and individuals who have that hunter mentality.”

The reason is simple. Co-selling effectively requires understanding how sales leaders think.

Shankar believes partner specialists should operate almost like embedded members of the ISV sales organization.

“The CRO of the ISV should tap into the specialist on my team as someone who works for their company with a google.com domain.”

That level of alignment requires people who understand pipeline generation, deal cycles, and revenue goals.

Measuring Partner Success

Revenue remains a critical metric, but Shankar emphasizes that partner success must be measured across the entire lifecycle.

Google Cloud tracks both leading and lagging indicators.

Examples include:

• marketplace revenue

• Google-sourced opportunities

• pipeline generation

• account mapping and engagement

• marketing activity

• joint demos and specializations

Pipeline health is especially important.

“We definitely think about having the 3x pipeline at a minimum for ISVs.”

Quality matters just as much as quantity.

Pipeline must reflect real opportunities where the joint value proposition resonates with customers.

The Impact of AI on the Ecosystem

AI is accelerating both innovation and partnership.

In many cases, hyperscalers and ISVs may overlap in capabilities.

But Shankar sees that dynamic as a natural part of modern ecosystems.

“Sometimes we compete and sometimes we complement, but regardless… gone are the days for us to think about one solution from one company can solve all of customers.”

The reality of AI is that no single vendor can solve every problem.

Partnership becomes the mechanism for delivering integrated solutions.

The Era of Deep Partnerships

Shankar believes the industry has entered a new phase.

Partnerships are no longer optional go-to-market experiments.

They are central to how technology companies succeed.

“We are in the era of deep, authentic partnerships. It’s not just a strategy anymore. It is a fundamental necessity for success.”

For partner leaders building ecosystems today, that may be the most important takeaway.

The future of technology innovation will not be built by single companies.

It will be built by ecosystems.

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Erica has lived this from multiple angles - advising partners inside the Microsoft ecosystem, running Maven Collective Marketing, and even founding her own ISV.

“It really depends on what stage in your journey as a company you are.”

For mature companies introducing a new product or service line, Erica recommends a controlled, pilot-style approach. A small number of well-chosen partners, deeply enabled, can tell you whether the model works before you scale it.

Startups face a very different reality.

“From my perspective as a founder where we came with no partners and bootstrapped funding, it was the name of the game was how many partners can we get?”

In that scenario, partners also function as marketing, air cover, and credibility. Volume matters early, with refinement coming later once patterns emerge.

Why the Second Deal Matters More Than the First

A recurring insight in this episode is that partner success is not defined by the first transaction. First deals can be accidental. Repeatability is what signals a real motion.

“Getting that first sale is great but can be a fluke. It’s getting to that second sale that really means, okay, now we’re cooking.”

That second deal proves several things at once - that sellers understand what they are selling, that incentives are aligned, and that the partner sees ongoing value. Without that, partner programs stall quietly, even if the pipeline looks healthy on paper.

This is where enablement, compensation, and internal support intersect. Technical certification alone is not enough if sellers are neither confident nor motivated.

“You could have someone technically trained inside of these partner organizations, but if the sellers don’t know what they’re selling and they’re not incentivized to sell, you’re going to have technically trained individuals and nobody’s selling.”

Co-Sell Only Works When You Align to the Platform

When the conversation turns to Microsoft co-sell, Erica emphasizes alignment over tactics. Partners that perform well are not guessing at Microsoft priorities - they are mapping directly to them.

“It’s really just aligning year after year with what are Microsoft’s priorities, how are we aligning our solution playbook with their solution playbook.”

Marketplace has become central to this alignment, especially as Microsoft increasingly expects transactions and quota retirement to happen there.

“There’s no doubt in anyone’s mind that Microsoft wants to be a marketplace.”

What has changed is not just visibility, but incentives. Field sellers can now retire quota through marketplace transactions, which fundamentally alters behavior.

“The fact that they can retire quota in marketplace is a game changer.”

For partners, this raises the bar on readiness. Listings, co-sell materials, customer stories, and transactability are no longer optional hygiene - they are how partners get discovered when a seller does not already know them.

Making It Easy for the Field to Choose You

Microsoft sellers are overloaded. Erica is blunt about what cuts through the noise.

“Sellers are going to pay attention to the things that help them retire quota.”

The partners who earn repeat introductions are the ones who reduce risk for the field. That means clear proof points, repeat wins, and disciplined communication.

“If we have partners that are continually showing us they’re winning in this industry or they’re winning in this workload, we as leaders will share that out to our team.”

Win wires, case studies, and consistent updates are not busywork - they are signals of reliability. The goal is simple: make it easy for a seller to say yes without fear of a bad introduction.

Incentives Matter - But Only If You Understand Them

Microsoft incentives evolve constantly, and Erica acknowledges how difficult they are to track.

“They’re novels.”

Still, she is clear that partners who invest in understanding incentives outperform those who ignore them. Whether it is AI readiness, marketplace transactability, or workload-specific funding, incentives shape behavior across sellers, partners, and customers.

The challenge is operational. Partner Center is complex, and many organizations under-resource it.

“It’s worthwhile to invest in someone that can navigate you through that because there’s plenty of incentives, plenty of funding that’s happening.”

Measurement That Drives the Right Behavior

Finally, Erica returns to measurement - not as a reporting exercise, but as a lever for growth.

Marketplace performance, listing decay, and engagement metrics now require ongoing attention as the platform evolves. But one metric stands out above the rest.

“What’s the opportunity to land and expand?”

Tracking how partners and customers move from one workload to the next creates a clear expansion roadmap. When sales teams understand how that expansion translates into revenue, behavior follows.

“If they can translate that product or that service into, ‘Hey, this makes you more money,’ generally the sales team is right on board.”

Partner programs succeed when strategy, incentives, enablement, and measurement reinforce each other. This episode offers a grounded look at what that actually requires.

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In this episode of Inside Partnering, Jen Dawson, Founder and CEO of SaaSNova, explains why. After years working inside AWS and supporting nearly a hundred ISVs, she has seen the same pattern repeat itself.

Strong products. Serious ambition.

But no clear path to predictable GTM.

“What I kept seeing across founders is they had strong products, but they didn’t have a very clear path to predictable GTM.”

That realization is what led Jen to start SaaSNova - not as a strategy consultancy, but as an execution-focused operating model for AWS Marketplace and co-sell.

AWS Is an Amplification Engine, Not a Safety Net

One of the most important reframes Jen offers is how founders should think about AWS itself.

Many assume AWS will generate demand if they simply onboard correctly. In reality, the relationship works very differently.

“AWS is not the lead gen engine. It’s an amplification engine.”

AWS sellers lean in when ISVs show momentum. Clear ICP. Clear value. Active deals. Without those signals, even well-built offerings struggle to gain field attention.

This is especially true given the scale of AWS.

“AWS is massive. Thousands of sellers. Lots of moving parts.”

For ISVs, that scale means simplicity and clarity matter far more than depth or volume.

Why the Better Together Story Comes First

Jen repeatedly comes back to the importance of joint messaging - not as a marketing exercise, but as the foundation of execution.

“The better together messaging becomes the foundation of all GTM programs.”

She breaks this into layers:

• First, the ISV’s own product story

• Second, how that story maps to AWS priorities

• Third, how channel or services partners fit into the motion

Each layer builds on the previous one. Without that structure, campaigns, pitches, and field enablement break down.

The key question every version of the message must answer is the same:

Who is this for, and why does it matter right now?

Marketplace Is the Route Sellers Prefer

From the field’s perspective, AWS Marketplace simplifies everything. Procurement. Alignment. Incentives.

“AWS sellers love marketplace because it removes procurement friction for their customers.”

Jen emphasizes starting small. Early private offers create momentum and internal proof. Over time, those deals expand into broader CPPO and co-sell motions.

Marketplace also plays a critical role for cross-border ISVs trying to establish credibility in the US market.

“Making sure you have a marketplace-ready offer so the AWS teams can really lean in.”

What Actually Gets Field Attention

AWS sellers are not persuaded by long decks or generic positioning. They respond to clarity and quantified impact.

“AWS teams are very data driven.”

ISVs that can articulate outcomes in concrete terms - time saved, cost reduced, migration accelerated - are far easier for sellers to champion.

Jen also points out that products which drive AWS consumption or workload stickiness naturally rise in priority.

“If the ISV really increases compute, storage, or keeps workloads on AWS, they become strategically important.”

Channel Partners as a Force Multiplier

For ISVs focused on scale, channel partners are not optional.

“The channel partner adds the acceleration. They add the scale.”

Resellers and consulting partners bring reach, relationships, and field capacity that ISVs rarely have on their own. When aligned correctly with AWS motions like CPPO, they significantly extend an ISV’s effective footprint.

The Metrics That Signal Seriousness

Jen outlines four categories of KPIs that matter most when building credibility with AWS:

“Marketplace KPIs. Co-sell KPIs. Adoption and consumption KPIs. Partner program KPIs.”

These metrics show not just activity, but execution readiness. They tell AWS that the ISV is aligned, disciplined, and capable of scaling.

The Reality of Strategic Collaboration Agreements

SCAs are often viewed as the end goal. Jen offers a grounded perspective.

“The SCA only works when both sides agree on revenue targets, pipeline targets, and execution.”

SCAs require real commitment, executive alignment, and the ability to execute against a joint business plan. They are rare for a reason.

“When the ISV shows up with clarity and readiness, that’s when AWS shows up with scale.”

Closing Thought

This conversation reinforces a simple truth: partner-led growth does not fail because of partnerships. It fails because execution lags intent.

“Make it easy for AWS to help you.”

For experienced partner leaders, that advice is not simplistic - it is operational.

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Grant framed the problem clearly. Enterprises need to use real customer data internally for development, testing, analytics, and increasingly AI. But regulation and security controls make that data difficult to use safely.

“Organizations need to leverage their customer data for their own internal purposes… but because of the regulation and security privacy around some of their most important data, they actually really struggle to leverage it internally.”

DataMasque was created to solve that tension by enabling what Grant calls high-fidelity synthetic data - data that is de-identified, but still behaves exactly like production data across systems.

Why Usability Matters More Than Perfect Security

A recurring theme in the conversation was that many existing solutions over-index on security at the expense of usefulness. According to Grant, that tradeoff creates downstream problems.

“While they will remove the sensitivity of the data, they’re actually effectively trashing the usability.”

Engineering and product teams need messy, imperfect data to test real-world edge cases. When lower environments are populated with overly clean or unrealistic data, systems often pass through test and QA, but fail in production.

“The messiness of production has to be replicated into these lower environments… otherwise you roll it into production and everything breaks.”

DataMasque’s approach focuses on masking at the field level while preserving relationships across systems, ensuring consistency even in complex, multi-application environments.

The Hidden Risk of Non-Production Environments

Grant highlighted a risk that many organizations underestimate - the size and exposure of non-production data.

“Seventy to eighty percent of an organization’s data footprint can be non-production.”

These environments often have weaker governance and broader access, making them a frequent source of breaches. For DataMasque, this reinforced the need to secure data where it is most widely used, not just where it originates.

Choosing AWS Marketplace as a Core GTM Strategy

Based in New Zealand, DataMasque faced a structural challenge. Their ideal customers were global enterprises, but building a traditional overseas sales presence was cost-prohibitive.

AWS Marketplace became the answer - initially almost by accident.

“I came out of the meeting going, I assume this is what everyone’s buying off Marketplace.”

The early days were slow, but momentum built through a combination of co-build, co-marketing, and co-selling motions. A customer case study and an AWS-authored blog post marked the inflection point.

“Suddenly it was like we had the co-build, then the co-marketing started to happen… and the flywheel started to turn.”

Marketplace enabled DataMasque to transact globally without a US entity or local bank accounts, dramatically lowering the cost of international expansion.

“We could actually do this all from here and done it in an extremely cost effective manner.”

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Charlie has been at Granite for more than two decades, including building the channel organization from scratch. What began as a one-person effort has grown into an 80+ person channels team supporting more than 800 active selling partners delivering over $500M of that total ARR number. That scale did not happen by accident.

“We look at our partners as our customers. Without their success, we don’t have any success.”

That philosophy shows up in how Granite structures its teams, invests in enablement, and evaluates ROI across the entire partner lifecycle.

Scaling a channel without losing focus

One of the most striking aspects of the conversation is how deliberate Charlie is about scale. Granite’s channel organization is large, but it is not generic. Roles are segmented by partner type, solution expertise, and regional coverage.

“Partnerships are about ROI - but not just dollars spent. It’s human resource spend as well. How are our people spending their time, and who are they spending it with?”

ROI, in Charlie’s view, is not just a finance exercise. It is a discipline that forces focus. Which partners are aligned. Where Granite can truly add value. And where deep expertise - not just broad coverage - makes the difference.

This is especially important in a channel ecosystem that includes individual agents, large VARs, MSPs, distributors, and mobility-focused specialists. Each partner operates differently, and Granite adapts its engagement model accordingly.

The evolution of the network business

Granite’s roots were in simplifying telecom complexity - aggregating disparate copper-based services into a single billing and service platform. That model fueled early growth, but the industry has changed dramatically.

Copper is being retired. Networks are converging. UCaaS, CCaaS, SD-WAN, 5G, fiber, and edge computing are now table stakes. And AI is putting unprecedented pressure on bandwidth, latency, and security.

“AI is impacting every facet of the business. The need for throughput and bandwidth is putting real pressure on end users.”

Charlie makes it clear that these changes are not abstract trends. They directly affect how partners sell, how customers buy, and how Granite builds solutions. The company has responded by developing proprietary offerings, including patented POTS replacement solutions, while also aggregating best-of-breed providers across mobility, networking, and security.

Collaboration as a competitive advantage

A recurring theme throughout the discussion is collaboration. Granite does not position itself as the single answer to every problem. Instead, it acts as an orchestrator - combining its own network and platforms with a broad ecosystem of underlying providers.

“The whole ecosystem requires partnership. We want to make sure partners see all the different things available to take to market.”

This approach gives partners flexibility while still benefiting from Granite’s scale. Volume matters. Granite’s purchasing power and critical mass translate into leverage with underlying carriers and technology providers - leverage that partners can bring to their customers.

Measuring partner performance beyond revenue

Revenue matters, but it is not the only metric that counts. Charlie describes a performance framework that looks at engagement, responsiveness, and mutual investment.

“If we’re providing training, marketing, and expertise, what’s coming back? It has to be a win-win that leads to an end-user purchase.”

Granite aligns partner-facing roles around relationship management, solution expertise, and specialized vertical or solution focus. That structure allows the team to stay close to partner needs while still maintaining accountability.

M&A, private equity, and channel disruption

The channel landscape is changing fast. Private equity and venture capital are reshaping partner organizations, driving consolidation and new competitive dynamics.

Charlie views this influx of capital as both an opportunity and a risk.

“Capital allows for growth and innovation. But we can’t lose sight of why this industry grew in the first place - taking care of the customer.”

Some partners are building at scale through acquisition. Others are choosing to remain independent and differentiate through expertise and service. Granite works with both, but the underlying principle stays the same - customer outcomes come first.

Why AI makes the channel more relevant, not less

Rather than disintermediating partners, AI is increasing their importance. As customer environments become more complex, the need for consultative guidance grows.

“AI and bandwidth-driven demands create a myriad of opportunities for partners to have better conversations with end users.”

From real-time analytics to customer experience optimization, the network is now a strategic asset. Partners who understand that shift are well positioned. Granite’s role is to give them the tools, infrastructure, and support to deliver.

Looking ahead

Granite is privately held, which gives it freedom to play the long game. Charlie is optimistic about the future, but grounded in execution.

“We’re not beholden to anyone but our customers and ourselves. What do they need, and how can we get it for them?”

For partner leaders navigating rapid change, this conversation is a reminder that fundamentals still matter - trust, ROI discipline, and relentless focus on customer value.

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The shift from office-first to remote, hybrid, and now partial return-to-office has permanently raised expectations. Employees expect technology to work seamlessly wherever they are, while IT leaders are under constant pressure to control costs and reduce downtime.

“The only thing that’s consistent besides change is that employee expectations keep getting higher and higher on the tools they need to get work done.”

Masooma’s role sits right at the intersection of those pressures.

Inside HP’s Workforce Experience Platform

At the center of HP’s digital services portfolio is its Workforce Experience Platform (WXP). The platform spans device telemetry, collaboration tools, network data, and application insights to help IT teams understand what is happening across their entire estate.

“It is really geared toward fleet management of the IT estate - PCs, printers, collaboration equipment, the network - and how we can proactively identify issues and remediate them.”

The goal is not visibility for visibility’s sake. It is about proactive action - identifying issues before they impact productivity and resolving them automatically where possible.

AI as Interface and Intelligence Engine

Masooma described two distinct ways HP applies AI inside WXP.

First, AI acts as the conversational interface. CIOs and help desk teams can ask natural-language questions about cost drivers, recurring incidents, and optimization opportunities.

“We use AI as the conversational interface of the platform so CIOs and help desk agents can quickly understand where the biggest issues and costs are.”

Second, AI works behind the scenes, analyzing massive volumes of telemetry data across devices to predict and prevent failures.

“That’s where AI becomes really powerful - using machine learning and inference to proactively solve issues before they happen.”

Predictive Self-Healing at Scale

One of the most compelling outcomes of this approach is predictive self-healing. By working with Amazon Web Services and Amazon Bedrock, HP can anticipate recurring issues and deploy fixes automatically.

“We can not only identify that an issue might reemerge, but tell you what the appropriate fix is - and in some cases deploy that fix on your behalf.”

The impact is measurable - less downtime, lower help desk costs, and better employee experiences across distributed environments.

A Platform Built for Partners

A recurring theme in the conversation was HP’s partner-first mindset. WXP is designed not just for direct enterprise customers, but also for MSPs and GSIs who wrap their own services and tooling around the platform.

“For our partners, we give them these tools so they can wrap services or incremental value around it and better serve their customers.”

This approach allows HP to scale across enterprise, mid-market, and SMB segments without relying on heavy customization.

What Customers Are Asking for at re:Invent

Like nearly every conversation at re:Invent, AI dominated customer discussions - but with a more practical tone than in previous years.

“It’s not just a technology anymore. Customers are asking what AI is actually doing for them in terms of optimization and understanding.”

Masooma noted a visible shift from proof-of-concepts to real, production-ready solutions across the expo floor, reflecting faster development cycles and maturing AI platforms.

Co-Building With Amazon

HP’s partnership with AWS spans co-build, co-market, and co-innovation. Beyond using Amazon tools to accelerate development, HP actively feeds enterprise-scale requirements back into Amazon product teams.

“Many of the requirements we have around predictive analytics have come from us into the Bedrock team to say we have to be able to solve these problems.”

The collaboration also extends into sovereign data initiatives, particularly for European customers with strict data residency requirements.

Product Leadership at Ecosystem Scale

As a product leader, Masooma plays a critical role in translating customer and partner needs into platform-level capabilities that can scale globally.

“We want to build for scale. We don’t want to do a lot of custom work.”

That philosophy mirrors AWS’s own approach and helps explain why the partnership continues to deepen.

Final Takeaway

This conversation is a clear reminder that successful AI strategies are no longer about experimentation alone. They are about operationalizing intelligence, embedding it into platforms, and enabling partners to deliver measurable outcomes at scale.

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Rather than focusing on abstract AI potential, the discussion centered on execution, data gravity, and the operational realities faced by Global 2000 enterprises.

Why So Many AI Pilots Stall

One of the core challenges Pankaj highlighted is something many partner leaders are seeing first-hand: an explosion of pilots with very little follow-through.

“There’s a lot of money being poured into agentic AI that start with the pilot, but a very small percentage of those pilot projects actually see ROI in terms of real world executable projects.”

The issue isn’t lack of tooling or ambition. It’s that most pilots don’t connect deeply enough to the systems that actually run the business. Without access to mission-critical environments and operational data, pilots remain isolated experiments.

The Role of Mission-Critical Systems

Kyndryl’s position in the market is unusual. The company manages complex, long-running systems for a majority of Fortune 100 enterprises, including a significant portion of the world’s managed mainframe environments.

“We manage more than two to three decades of mission-critical systems for our customers. I think we have access to data which very few in the industry have.”

That access becomes the foundation for making agentic AI useful. Instead of training agents on abstract datasets, Kyndryl works directly with the operational knowledge embedded in real systems, workflows, and infrastructure.

The Enhanced Agentic AI Framework

At re:Invent, Kyndryl highlighted its enhanced agentic AI framework, which combines several layers:

• Deep operational knowledge from managed services

• Proprietary platforms like Kyndryl Bridge with billions of data points

• Agent builders developed by Kyndryl

• Native integration with AWS services

“That repository of knowledge that we have is the critical fuel that you require to make an agent AI project successful.”

This approach is not positioned as a one-size-fits-all product. Instead, the framework is designed to be customized by region, industry, and customer maturity.

From Assessment to Execution

Another theme that surfaced repeatedly was execution discipline. Kyndryl works across the entire transformation lifecycle, from assessment and migration to modernization and operations.

“We are able to translate those pilot projects into real world executable projects.”

That translation is reflected in business outcomes. According to Pankaj, a meaningful portion of recent Kyndryl signings already include an agentic AI component, suggesting that customers are moving beyond experimentation.

AWS as a Strategic GTM Partner

The conversation also explored the depth of the AWS partnership. Kyndryl has aligned its go-to-market motion with how AWS now sells by industry rather than horizontal services.

“Our sales motion and our collaboration with AWS is in tune with how AWS is going to the market, what solutions they are taking to the market.”

This includes co-sell engagement across financial services, insurance, healthcare, automotive, and the public sector, where Kyndryl was a finalist for multiple AWS Partner of the Year awards.

Industry-Specific Execution Matters

One insight particularly relevant for partner leaders is the emphasis on regional and industry focus.

“Something that works in Japan could not be the same thing that we take to continental Europe or Australia.”

Rather than forcing global uniformity, Kyndryl and AWS customize plays based on local regulations, market maturity, and customer expectations, especially in regulated industries and sovereign cloud environments.

Consulting as a Growth Engine

Since spinning out as an independent company, Kyndryl has invested heavily in consulting capabilities to complement its managed services heritage.

“Our consult business is more than $3 billion, growing at about 35 to 40% year on year.”

That consulting layer allows Kyndryl to engage earlier in transformation conversations and stay involved through execution, which is essential for agentic AI initiatives that cut across infrastructure, data, and operations.

A Grounded View of What Comes Next

Rather than framing agentic AI as a sudden revolution, Pankaj described it as an evolution that depends on execution maturity.

“This would be something where Kyndryl fills a gap in the market.”

For partner leaders, the takeaway is clear: success in the agentic AI era will depend less on novelty and more on operational credibility, trusted data access, and tight collaboration with hyperscalers.

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🎙️ Inside Partnering is a podcast for ecosystem builders, alliance leaders, and the people shaping the future of partnerships.

Let’s build the future of partnering - together.

📌 If you found this post helpful, would you please consider restacking it and sharing it with your audience? This spreads the word and keeps me interviewing and sharing content that will help you grow your partnership business and career.

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Kelley Lear stepped into her role as CVP and GM, Global Alliances for Blue Yonder just four months ago, and she arrived at Microsoft Ignite with major momentum behind her team’s work.

Fresh off winning Microsoft’s Global ISV Partner of the Year award, Blue Yonder is doubling down on AI innovation, ecosystem collaboration, and a platform vision designed to transform supply chains end to end.

“Ultimately we need to partner not just to partner so that we get an award. It’s really what is the value that we’re bringing to the customer.”

From keynotes to side conversations with SIs and product leaders, Kelley emphasized that supply chain complexity demands deep partner expertise, global reach, and joint innovation. Blue Yonder now works with more than 300 partners - spanning tech vendors, hyperscalers, global SIs, and boutique regional firms.

Why Supply Chain Needs a Connected Ecosystem

Kelley shared that Blue Yonder is the only platform with AI embedded across the full supply chain - from planning to execution to returns. That end-to-end view has become essential as supply chains face disruptions from geopolitics, tariffs, weather, social pressures, and demand volatility.

“You need complete visibility to the supply chain and the ability to plan and pivot and incorporate all the data you need to make good decisions quickly.”

The partner ecosystem is central to delivering this vision. Strategic systems integrators like Accenture, Deloitte, PwC, EY, and specialized regional partners provide decades of experience within specific verticals and customer environments. Their understanding of systems, workflows, and C-suite priorities allows Blue Yonder’s platform to land with higher adoption and faster value realization.

Mapping the Right Partners to the Right Customers

Given the scale and complexity of a 300-partner ecosystem, Kelley described the importance of careful alignment between field teams, industry specialists, and partners. Blue Yonder has an industry advisory team that matches the right partner - by region, vertical, subvertical, and product expertise - to each opportunity.

The company is also launching a new agentic AI partner scorecard, which allows sales and alliance teams to ask natural-language questions about partner capabilities.

“We’re looking at things like how many accredited personnel they have, in which regions, on which products, customer sat scores, and project expertise.”

The goal is not to rank partners for competition but to help internal teams and customers find the best match for each scenario.

Scaling the Long Tail with Modern Partner Marketing

Kelley also highlighted the importance of supporting the “long tail” of smaller partners who may not have dedicated alliance managers. Blue Yonder is rolling out scalable partner programs including updated portal content, channel calls, toolkits, and campaigns-in-a-box.

“We’re getting a little more sophisticated with really professional marketing toolkits instead of just saying - you could spin up a webinar and use our name.”

As Blue Yonder expands its new Azure-based platform - with deep Snowflake integration and advanced AI - the company is also ramping up global enablement to help partners stay ahead of the rapid innovation curve.

Co-Innovation with Microsoft and a Shared Future Vision

Blue Yonder’s Global ISV Partner of the Year recognition reflects a rapidly strengthening relationship with Microsoft. Kelley noted that the two teams are deeply aligned across co-innovation, product development, co-marketing, and field co-sell motions.

“We’re collaborating with Microsoft on incorporating our AI into our product mix, and also on how others can build agents onto our platform.”

Beyond technology, the joint marketing and field alignment efforts are helping both teams articulate their “better together” story - including scalability, time to value, and end-to-end security.

What Comes Next for Supply Chain Leaders

Kelley closed with a reminder that global supply chains are under more pressure than ever - and that only an integrated ecosystem can help companies respond in real time.

“We want to disrupt the market and really transform supply chain end to end.”

With AI advancing rapidly, Microsoft partnership momentum building, and a global partner network evolving around industry expertise, Blue Yonder is positioning itself as a leader in the next era of intelligent, adaptive, resilient supply chains.

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The pace of change has become the defining characteristic of the AI era. As Marc Monday puts it, quoting Bill McDermott, “The pace of change has never been this fast and it’ll never be this slow again.”

And inside ServiceNow’s rapidly expanding partner ecosystem, that accelerating change is creating unprecedented opportunity for partners.

In this episode, I spoke with Marc Monday, GVP of Americas Partnerships & Channels at ServiceNow. Marc and I dive into how ServiceNow is approaching AI, why partners remain essential, and why orchestration - not infrastructure - is becoming the most critical layer in the enterprise tech stack.

The Partner Role in an Agentic World

ServiceNow’s AI strategy is focused on meeting customers where they are. That means working with the infrastructure, data, and applications they already have - not forcing costly rip-and-replace motions.

Marc emphasizes that this is exactly where partners shine.

“Partners bring a deep level of specialization in customer understanding, and partners know how to move fast and meet the market where it is.”

ServiceNow has five partner routes to market - consulting and implementation, resellers, service providers, hyperscaler co-selling, and tech/build partners. Increasingly, partners combine multiple motions, creating IP, offering managed services, and developing apps.

Marc’s view is simple: focus on outcomes, not taxonomy.

“If we fall into that legacy taxonomy, sometimes it hamstrings what the partner is providing.”

Workflow Orchestration as the New Control Tower

One of the big ideas Marc shares is the rise of the orchestration layer - the system that coordinates agents across the enterprise.

ServiceNow sits across the data layer, application layer, and now agentic workflows, giving it a unique ability to coordinate how work actually gets done.

“At the end of the day, it’s about workflow orchestration and what that control tower is going to look like.”

This orchestration layer determines which agent acts first, what data it accesses, and how steps flow across systems. It’s the enterprise equivalent of air traffic control.

Real Value: Pragmatic AI, Not Whiz-Bang Demos

Marc shares an important reminder - the most meaningful AI value often comes from eliminating the everyday “administrivia.”

“If you talk to a user, they can tell you right away… This is the administrivia that just takes the air out of my day.”

Partners play a crucial role in discovering these real-world use cases, mapping processes, and turning small but painful inefficiencies into major productivity improvements.

Where the Opportunities Are Emerging

ServiceNow is seeing strong opportunity across four primary areas:

1. Autonomous IT

Hardware management, IT service delivery, systems improvement.

2. Security

AI is increasing both complexity and opportunity across the security surface.

3. CRM and Customer Experience

Extending ServiceNow’s strong CSM foundation.

4. Cross-Application Interoperability

Where agents, workflows, and orchestration combine.

Throughout all of these, partners act as the translators connecting enterprise reality with AI-enabled execution.

Co-Sell: It Depends - Because It Must

When I asked Marc about co-sell motions, his answer was delightfully honest:

“It depends. It really does depend what is the customer’s expectation.”

ServiceNow supports store listings, deal registration, partner-led opportunities, and multi-party co-sell with hyperscalers.

Marc’s team brings together the right partner and the right opportunity at the right time.

The Road Ahead

Marc’s final insight was about trust and flexibility - two things customers need most right now.

“Customers need flexibility. Customers need partners that can meet them where they are.”

As AI accelerates, orchestration becomes more important, partners become more essential, and the opportunities multiply.

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In this episode, Gretchen shares her early impressions of Sage, why she joined, and how she sees AI reshaping partner opportunity across the world.

This conversation offers an inside look at the major announcements coming out of Sage Future for Partners in Barcelona - including Sage’s new Finance Intelligence Agent, next generation Sage X3 Cloud, and Sage AI Developer Solutions built with AWS Bedrock.

Why Gretchen Joined Sage

Gretchen has spent her career building partner ecosystems at massive scale. Yet she says Sage had something unique - a deep, community-driven network of partners rooted in finance, accounting, and operational systems.

One quote from the transcript captured her motivation perfectly:

“I always had an eye on Sage… I was really envious of what Sage had in terms of that deep partner commitment and this inherent community that has rallied around Sage.”

She also saw something else: the finance function as one of the first places where AI will deliver real, practical value.

“I knew that AI is gonna have very practical impact… and I think this is where you’re gonna see a lot of this in full production first.”

Sage’s 40 years of financial data, combined with its cloud first and AI first ambitions, made the move compelling.

A Complex and Growing Ecosystem

Sage works with a uniquely diverse partner mix: global SIs, accounting firms, MSPs, ISVs, VARs, and developers.

“There’s not one type of partner that Sage works with… we have SIs, advisors, accounting consultants, ISVs, VARs, MSPs - all building capabilities in this new cloud and AI world.”

For Gretchen, the opportunity is to unify and accelerate this ecosystem - not just through programs and incentives, but through AI driven capabilities that help partners differentiate and grow.

Inside Sage Future for Partners: AI Takes Center Stage

Just a few weeks into the job, Gretchen was dropped straight into Sage’s global partner event in Barcelona. And Sage delivered several major announcements that will shape partner strategy for years to come.

1. Sage AI Developer Solutions (built with AWS Bedrock)

This initiative lets partners build and deploy certified AI agents and workflows directly within Sage Copilot.

“We announced the Sage AI for Developers program… leveraging AWS Agentic AI Marketplace to speed partners’ ability to build AI agents embedded right into Sage.”

For partners, this means new revenue streams, faster innovation, and a clear place to bet in the agentic AI era.

2. Finance Intelligence Agent

Sage also revealed its flagship AI Agent for CFOs and finance teams - prebuilt, trusted, and immediately usable.

“We announced one of our own agents, the Finance Intelligence Agent… so partners can provide instant value without having to build anything themselves.”

This agent connects Sage’s Close, AP, Assurance, and Time agents, creating a unified intelligence layer for finance operations.

3. Sage X3 Cloud

A next generation cloud deployment of Sage’s manufacturing and operations platform.

“We recommitted to our partner ecosystem that X3 is a big bet for Sage… partners were extremely excited about the deeper industry strategy.”

Across these announcements, a consistent theme emerged: industry depth + AI agents + partner led innovation.

Partner Profitability, Enablement, and Co Innovation

Gretchen emphasized that partner success is not just about revenue - it is about making sure Sage partners are able to build and manage profitable, sustainable business models when working with Sage.

“If you can’t have a profitable practice, then you start looking somewhere else… and I want all my partners to stay with Sage.”

Sage’s strategy includes:

• Helping partners build recurring ARR based businesses

• Reducing implementation time with cloud and AI

• Supporting partners as they expand into adjacent practices

• Deepening technical and business enablement

And importantly, Gretchen sees co innovation as central.

“We want to co innovate with our partners… bring more value together to our mutual customers.”

Measuring Success: Shared Outcomes

When asked how Sage measures partner success, Gretchen cited:

• Growth and co sell wins

• Marketplace innovation

• Partner IP

• Expansion into new markets

• Customer success metrics

• Capacity and delivery strength

But measurement itself is evolving, especially as influence, indirect impact, and AI driven services become more important.

The Road Ahead

Gretchen closed with a call for partners to prepare for the AI empowered future, balancing today’s opportunities with tomorrow’s shifts.

“Have one step in the future so that as the market shifts, you’re there with us to support that long term.”

This episode is essential listening for partners, ISVs, SIs, accountants, and anyone watching how AI is reshaping the finance and ERP ecosystem.

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At AWS re:Invent, I had the opportunity to chat with Chandos Quill, Senior Vice President of Channels and Alliances at Epsilon, for a rich discussion about building a partnership discipline inside a global data and marketing technology organization.

Chandos brings deep experience across data, ad tech, and marketing platforms - and her work at Epsilon demonstrates how a focused, disciplined approach to alliances can unlock entirely new routes to market.

Who Epsilon Serves and Why Partners Matter

Chandos began with a quick overview of Epsilon’s role within Publicis Groupe. Epsilon is the data, technology, and services arm that helps brands acquire customers and deepen relationships with existing ones. As she put it, the mission is simple - bring data driven solutions to marketers that drive meaningful outcomes.

But the real story comes through the evolving role of partners. Infrastructure providers, Martech platforms, ad tech channels, and specialized point solutions all play a part.

“What we’ve tried to do is within each of those categories of partners, we focus on the most important thing that Epsilon can bring to add value on top of the partners’ technology or products.”

Building a Partnership Function from the Ground Up

When Chandos joined Epsilon a year and a half ago, partnerships existed only in pockets across the business - organic, siloed, and ad hoc. Her charter was to build a centralized function that aligned tightly with corporate direction and product strategy.

“We had a few pockets of people doing partnerships, but we didn’t have a centralized partnership function.”

The first year focused on talent assessment, team formation, defining strategy, and building foundational systems - including tracking, measurement, and aligning the field around partner value.

Quality Over Quantity

Epsilon works across several categories of partners - infrastructure players like AWS and Databricks, technology platforms like Adobe and Salesforce, ad tech channels, and point solution integrations. But Chandos emphasizes disciplined focus.

“My message to all of our partners is we’re leaning in on the ones that really matter and continuing to grow and scale those versus signing up 20 or 30 new ones.”

With finite resources and a mandate to prove value, prioritization is essential. The goal is not breadth - it’s depth.

A Breakthrough Moment with AWS Marketplace

A major milestone came recently when Epsilon transacted its first large deal through AWS Marketplace. The impact was immediate - seller excitement, internal visibility, and growing alignment with AWS.

“We actually closed an extremely large deal through the Marketplace… and it’s gotten the attention of our sales people.”

This opens new opportunities for Epsilon sellers accustomed to working with Marketing and Line of Business buyers, as AWS provides access to IT and procurement relationships that accelerate deal velocity.

Enabling Sellers for a New GTM Motion

For many sellers, partnering with AWS requires a shift in mindset. They now have the opportunity to jointly navigate enterprise accounts from two different entry points - Marketing and IT.

“Some of our sellers are kind of newer to that idea of how you can use an AWS partner to help us get those relationships with IT, get those relationships with procurement, get our deals through faster.”

Much of Chandos’s 2026 agenda centers on sales enablement - making these motions repeatable, predictable, and valuable for both sides.

Data Privacy and the Future of Clean Rooms

As a global data provider, Epsilon is deeply invested in privacy, compliance, and responsible data stewardship. This extends to partnerships as well.

Chandos noted that clean rooms are becoming increasingly important as brands seek to collaborate on data without exposing sensitive information. Epsilon is integrating its clean room technology with infrastructure partners to support enterprise scale use cases.

AI, Personalization, and One to One Marketing

AI’s role is expanding rapidly across Publicis and Epsilon. Chandos described a future where AI helps marketers achieve the long sought ideal of true one to one engagement.

AI will shape everything from audience creation, to content personalization, to cross channel orchestration. And partners play a massive role in aligning the technical stack and data foundation needed for that future.

The Road Ahead

Chandos is clear that the partnership journey at Epsilon is still early. The foundation is built, the internal momentum is growing, and the first Marketplace wins are creating confidence.

Her focus now is steady growth, demonstrable value, and scaling the GTM with partners that matter.

This is the type of transformation that reshapes how a company goes to market - and Chandos is right in the middle of it.

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🎙️ Inside Partnering is a podcast for ecosystem builders, alliance leaders, and the people shaping the future of partnerships.

Let’s build the future of partnering - together.

📌 If you found this post helpful, would you please consider restacking it and sharing it with your audience? This spreads the word and keeps me interviewing and sharing content that will help you grow your partnership business and career.

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What an incredible week in Las Vegas.

AWS re:Invent once again delivered a remarkable mix of energy, innovation, and real partner momentum. From major AWS announcements to deep conversations with executives who are building, scaling, and redefining ecosystem strategy, the week was packed with insights that highlight where cloud, AI, Marketplace, and partner-led growth are headed.

Below is a quick recap and link to every interview I recorded during the week - each one offering a different perspective on what’s changing and what’s coming next for partner leaders.

(Includes links to the 8 interviews already published. Four more will be published over the coming days.)

Recorded ahead of re:Invent and released on announcement morning, Monday, Dec 1st, this interview with Matt Yanchyshyn focused on the major AWS Marketplace and Partner Services announcements shaping the upcoming year.

Matt walked through improvements designed to streamline procurement, accelerate transactions, and support ISVs building AI-enabled solutions on AWS. He discussed new capabilities intended to reduce friction for buyers and sellers, expand global reach, and help partners move from prototype to production faster.

A key takeaway was AWS’s increasing focus on simplicity and flexibility - giving partners more commercial options while helping customers access cloud software with far fewer barriers. The conversation set the tone for the week’s Marketplace momentum.

Mona Chadha shared her perspective on how AWS is evolving to meet partners in a rapidly shifting market shaped by AI, data gravity, and customer expectations. She discussed the acceleration of ISVs building on AWS and the increasing importance of co-innovation in landing and expanding enterprise relationships.

Much of the conversation focused on how AWS is helping partners deliver measurable customer outcomes faster - a recurring theme across re:Invent. Mona also highlighted the continued rise of Marketplace as a preferred buying channel and how AWS teams are aligning earlier with partners to simplify procurement and support broader GTM alignment.

Rohan Karmarkar offered a strategic lens on partner engagement at scale, digging into what AWS is seeing across global markets. He talked about how AI is reshaping business models for ISVs and GSIs, and why partners that lean into industry specialization are gaining a competitive edge.

The conversation also touched on modernization, cloud economics, and the ways AWS is helping partners build differentiated solutions with reusable assets and repeatable plays. Rohan emphasized that ecosystem success now depends on creating joint value propositions that compress time to outcome for customers.

Asher Mathew and I shot this conversation live at re:Invent on Tuesday morning sharing the energy, announcements, and emerging themes shaping the week.

Asher shared what he was hearing from Partner Leaders across the conference - from the excitement around AWS Marketplace enhancements to the accelerating shift toward AI-enabled co-sell motions. He talked about the rapid expansion of the partnering profession, how Catalyst 2025 is shaping up, and why partner leaders are becoming central to company strategy rather than support functions.

The conversation captured the momentum of the week and the sense that partnership roles are transforming faster than ever before.

Deepak Arora brought a GSI perspective grounded in large-scale digital transformation. He shared how Publicis Sapient is using AWS to help clients move from experimentation to operational impact with AI and data platforms.

A key theme was alignment - how GSIs and hyperscalers create value when strategy, delivery, and sales motions are tightly integrated. Deepak also reflected on the shift toward product-based engagements and reusable accelerators that speed transformation.

His insights underscores how partner-ecosystem collaboration is evolving from transactional to deeply co-architected.

Sanjay Bhakta offered a fascinating media-industry perspective. The following day, Sanjay would be joining Ruba Borno on the big stage for her keynote telling the Condé Nast journey with AWS.

In our conversation, Sanjay spoke about Condé Nast’s technology transformation, including the modernization of global platforms that power iconic brands. He discussed how AWS plays a role in scale, reliability, and data capabilities, particularly as the company builds more personalized, AI-driven digital experiences.

Sanjay also talked about how a media enterprise approaches innovation - balancing creativity, experimentation, and engineering excellence. For partner leaders, his lens was a reminder that ecosystem value extends well beyond traditional software and services.

There was some BIG NEWS in the partner tech world announced at re:Invent. Tackle has been a leader in the Cloud GTM space for many years, and last week, AppDirect and Tackle announced they’ll be merging with AppDirect acquiring.

I reached out to Tackle CEO, John Jahnke and was excited to have the opportunity to chat with John and AppDirect CRO, Emanuel “Bert” Bertolin about the announcement.

We discussed the changing landscape for cloud commerce, the evolving role of hyperscaler marketplaces, and how the acquisition of Tackle by AppDirect is shaping a more connected purchasing and selling experience for software companies.

John and Bert also explored what customers want - simplified buying, consolidated spend, and integrated workflows - and how the combined capabilities of both companies support ISVs and channel partners navigating multi-cloud commerce. It was a rare chance to hear both sides reflect on the future of cloud sales.

What a great opportunity to talk with a CEO who totally “gets” the value of partnerships. And in Dynatrace’s case, that includes being a driving force in growing ARR by 2X from $1B to $2B in the last four years.

Rick shared a CEO’s view on the intersection of AI, cloud modernization, and the partner ecosystem. Dynatrace has long been a leader in observability, and Rick discussed how AI is accelerating the shift from reactive monitoring to proactive, automated intelligence across entire cloud environments.

He reflected on customer expectations, how Dynatrace partners with hyperscalers to drive platform adoption, and why trusted relationships still matter in a landscape increasingly shaped by automation. The interview also touched on the importance of simplicity - helping customers realize value faster and with less friction.

Jessica’s story resonates deeply with partner leaders in the cloud GTM space.

Before founding Skematic, she spent nine years at CrowdStrike and led the AWS partnership - a partnership that has now transacted over $2B on AWS Marketplace and become a blueprint for AWS co-sell and marketplace success.

Jessica shares the lessons learned about building a scalable co-sell engine, aligning field teams, and creating repeatable motions that accelerate growth.

Jessica also reflects on why she built Skematic and how AI can streamline deal orchestration for partner and sales teams. Her experience makes this conversation especially valuable for anyone building marketplace, co-sell, or partner-led revenue strategies - and wanting to learn from the incredible Crowdstrike success story.

Chandos brings a data-driven, customer-centric perspective on partnership strategy. She speaks about how Epsilon helps global brands leverage data to create personalized experiences at scale and how partnerships play a central role in delivering these outcomes.

The conversation touched on co-innovation, industry solutions, and how Epsilon collaborates with cloud providers to align GTM and drive measurable revenue impact. Chandos emphasized the increasing need for clarity in partner roles, value exchange, and data-sharing models - topics top of mind for many ecosystem leaders.

Pankaj Kumar – VP, Kyndryl

As a leader at Kyndryl, Pankaj brings a large-scale GSI services perspective to the conversation, highlighting how Kyndryl is helping some of the world’s biggest enterprises modernize legacy environments while adopting cloud and AI at speed.

He discussed how Kyndryl partners closely with AWS to bridge the complexity gap that many customers face - migrating critical workloads, securing hybrid environments, and operationalizing AI in real production settings. A core theme was trust: enterprises rely on Kyndryl and AWS together to reduce risk during transformation. Pankaj also emphasized the growing importance of co-innovation, reusable solution frameworks, and repeatable services that create measurable outcomes for customers navigating long-term modernization journeys.

(To be published soon…)

Masooma Naqvi – VP of Digital Services, HP

Masooma shares insights into how a major global technology brand like HP approaches digital transformation, services modernization, and customer experience at scale.

She shared how HP is evolving its digital services portfolio, how AI is improving operational efficiency and customer outcomes, and how partners contribute to accelerating transformation across industries.

Masooma also discussed organizational alignment - how large enterprises integrate product, services, and ecosystem motions to create more holistic value. Her perspective highlighted the importance of collaboration across multiple layers of the value chain.

(To be published soon…)

My Closing Video from AWS re:Invent

What an incredible week at AWS re:Invent!

With 88,000 attending in Vegas, the energy was off the charts - and the announcements from AWS and AWS Marketplace will shape partner strategies for months to come.

The generosity of leaders who sat down to share their insights made this one of the most memorable events I’ve covered.

Each guest offered a unique lens on where cloud, AI, Marketplace, and partner-led growth are headed, and I’m grateful to everyone for taking the time during such a busy week.

So much insight packed into a few days.

Huge thanks to Allison Bishop, Matt Yanchyshyn and the entire AWS Communications team for making this possible and helping coordinate a fantastic lineup of guests.

Already looking forward to next year.

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Jessica is now Founder and CEO of Skematic, where she’s encapsulating those learnings into an AI-powered platform designed to help ISVs navigate AWS programs, messaging, alignment, and execution far earlier and far more effectively than most can today.

It is rare to hear this level of clarity about what truly makes an AWS partnership work. Jessica lived it. And now she is scaling it.

The Early Days at CrowdStrike - And Why Marketplace Was Hard

When Jessica arrived in 2016, CrowdStrike was already a strong product - but its AWS motion was immature. They saw an opportunity to partner deeper with AWS, both to differentiate and to build a 360 relationship that included buy-from, sell-with, and sell-through motions.

“We initially launched our marketplace listing and thought there’s gonna be a whole bunch of people who are gonna show up. And nobody showed up.”

This is the moment almost every ISV experiences. Marketplace is not magic. It is a multi-year internal and external enablement effort.

CrowdStrike learned that success required educating customers on how to take advantage of AWS EDP (Enterprise Discount Program) funds, influencing AWS sellers, and aligning internal teams that had never collaborated this way before.

“It was a five year journey to develop that flywheel of how do we do private offers, how do we scale marketplace transactions.”

That flywheel eventually became legendary - but only because the company invested deeply in internal alignment.

Why Internal Alignment Is the Real Secret to AWS Success

Jessica emphasized repeatedly that AWS partnership success is not just an alliance-led motion.

It is organizational.

“We think of partnerships as who we partner with externally, but the key to success is how you partner internally.”

At CrowdStrike, she created a global specialist team that “spoke AWS,” navigated EDP ownership, trained the sales organization, and partnered closely with product, finance, and marketing.

One of her biggest internal allies might surprise people:

“One of my early allies internally was our finance team because they saw how fast marketplace transactions reduced our daily sales outstanding.”

This internal partnership became one of the catalysts that helped CrowdStrike scale its marketplace motion faster than nearly anyone else in the industry.

Why Skematic Exists

After advising many startups, Jessica saw the same repeated pattern:

ISVs want to partner with AWS. But they do not know:

• When they are ready

• What programs apply to them

• How to build their messaging

• Who internally needs alignment

• What AWS expects

• Or how to operationalize the entire motion

So she built Skematic to solve this.

“We’re hoping to simplify this with Skematic and help ISVs navigate the process a lot faster, a lot earlier, with fewer resources.”

Skematic is an AI platform that generates partnership pathways, creates better together stories, aligns executive teams, and provides prescriptive, personalized recommendations based on where an ISV is in their AWS journey.

It also includes coaching for the first three months to ensure companies set the right strategy and internal structure.

“The goal is for the platform to be prescriptive and personalized - contextually aware of where the ISV is and how to market to their AWS customer.”

And it is built entirely on AWS using Bedrock and Claude Sonnet.

Scaling What Used to Require Full-Day Workshops

Jessica compares Skematic directly to the workshops historically run by AWS partner leaders.

“We want to make this programmatic and accessible to more people. Jen [Dawson] was one person. I’m one person. How do we scale this across thousands of software companies?”

This is where Skematic becomes transformational - taking the manual, human bottlenecks of cloud GTM and turning them into intelligent automation.

Founding a Company After Years of Partnership Leadership

Jessica describes founding Skematic as the most energizing step of her career.

“You jump out of the airplane and realize you don’t have a parachute - but then you realize there’s no bottom. I’m doing what I love doing.”

The reception from AWS has been strong. AWS sees Skematic as a capacity multiplier: helping more ISVs become partner ready, program eligible, and marketplace capable earlier in their lifecycle.

What’s Next for Skematic

Skematic is continuing to evolve with deeper AWS integrations, more automated workflows, portfolio-level insights for investors and accelerators, and expanded guidance mapped directly to AWS programs.

And this is only the beginning.

Startups today want to grow the way CrowdStrike did.

Skematic is giving them the roadmap Jessica spent nearly a decade building out.

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🎙️ Inside Partnering is a podcast for ecosystem builders, alliance leaders, and the people shaping the future of partnerships.

Let’s build the future of partnering - together.

📌 If you found this post helpful, would you please consider restacking it and sharing it with your audience? This spreads the word and keeps me interviewing and sharing content that will help you grow your partnership business and career.

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There may be no better person to explain why it matters than Brian Landsman - CEO of AppExchange and EVP of Global Partnerships at Salesforce.

In this episode of Inside Partnering, Brian breaks down what the news means for builders, ISVs, consultancies, and customers as the industry shifts to an agentic era.

A Platform Built for the Agentic Era

Brian describes the announcement as the next evolution of Salesforce’s long history of enabling others to build on the Salesforce platform. This new model opens the door for startups, founders, ISVs, and global enterprises to use the full power of Salesforce - including Agentforce 360, Data 360, Marketing, Tableau, and Industries - to turn their expertise into revenue-generating products.

“We are now bringing all of those capabilities to our partners to incorporate into their business.”

The platform is designed to connect data, automation, and intelligence into unified solutions, versus isolated apps. For partners with deep domain expertise, it creates a foundation to build sophisticated AI-enabled products much faster than building standalone infrastructure from scratch.

Why Innovation Is Stalling - and Why Salesforce Thinks It Can Help

Salesforce cites a major industry problem: 95 percent of generative AI pilots never reach production because companies lack platforms that connect intelligence with data, workflow, trust, and scale.

Brian sees that same challenge reflected across Salesforce’s ecosystem. Partners want to innovate, but need enterprise-grade capabilities ready-made.

“Enterprises don’t want disposable software. They want something maintained with 24/7 operations, threat detection, compliance auditing, enterprise uptime, and guaranteed SLAs.”

Salesforce describes how companies building their own SaaS foundations spend more and go to market slower. This announcement is designed to remove that friction by letting them build directly on Salesforce’s decades of platform investment.

Building Intelligent, Integrated Solutions - Not Point Products

Brian shares a core theme: customers are buying solutions. They want integrated workflows, industry context, and intelligent processes - not individual apps.

This is where Salesforce believes its model excels. By combining partners’ domain expertise with Salesforce’s architecture, builders can meet specialized needs without recreating essential components.

“If you are a business with an object that moves through a process and has workflows associated with it, it’s a natural fit on the platform.”

He shares examples ranging from highly regulated manufacturing to livestock management. Each illustrates how partners can infuse IP into an extensible platform that already handles identity, security, scalability, and integration.

AgentExchange, AppExchange, and the Shift to AI Skills

Today over 90 percent of Salesforce customers use at least one partner-built application from AppExchange. The same pattern is beginning with AgentExchange as partners build new agentic skills, actions, and capabilities.

“Many of the early success cases we’re having with the AgentExchange are existing AppExchange partners who have created agentic skills customers can plug into Agentforce.”

These skills allow agents to:

• Generate documents

• Pull in sales enablement content

• Trigger e-signature workflows

• Configure CPQ

• Query domain-specific knowledge bases

Salesforce’s bet is that agentic adoption will follow the same trajectory as apps.

How Co-Sell Is Changing in an Agentic World

Brian provides one of the clearest explanations of how co-sell is evolving.

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