Courtney McShane

Describing the launch of ServiceNow's AWS business, McShane lists what was not there — no co-sell motion, no Marketplace presence, no joint field coverage — and treats each gap as a build task rather than a footnote. The reasoning is that the value of a partnership comes from assembling that machinery, and the early phase is expected to be costly: McShane writes that in the beginning the team "lost far more than we won" and that the alternative was to lower the ambition.

At AWS Summit in New York, McShane walked through the 0-to-1 story of standing up the AWS business and then framed the next phase as taking it further — delivering "outcomes and value faster" through the partner ecosystem rather than adding more alliance language.

The same wrench-by-wrench framing reappears after the move to OpenAI, where McShane describes building with AWS again from a starting point rather than inheriting an established motion.

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The OpenAI charter covered the mission, the possibilities, and a 1-10-100 structure for scale; two months after a San Francisco lab, McShane reopened those slides at a joint close lab in New York and told the room that one "borderline impossible" goal had already been passed.

• The point is not the number but the rhythm — targets stay live across labs and checkpoints instead of being set once.
• McShane also uses small, capped offers to pull partner teams into that rhythm.

McShane offered the first ten AWS teams to invite OpenAI to co-present at a customer Executive Briefing Center a one-year OpenAI Pro subscription, with details to be shared at OpenAI and AWS happy hours in San Francisco and New York, and separately described the AWS and OpenAI Joint Close Lab in New York.

When McShane moved to OpenAI, the stated ambition changed scale: a post about the move reads, "instead of aiming for $1B, let's shoot for $100B," and the charter post notes that at OpenAI every person on the team has the opportunity and expectation to build a billion-dollar business in under a year.

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Each example names a platform pairing, the industry, and the problem removed — AI agent sprawl, unplanned equipment downtime, call routing — which is the level of detail a buyer can check.

Three scenarios from the AWS Summit post: for banks, Amazon Bedrock combined with ServiceNow's AI Control Tower and the Veza and Armis acquisitions gives one view of every AI agent running in an enterprise, including what data it can touch and what permissions it holds; for an auto manufacturer, ServiceNow OT workflows with AWS IoT SiteWise flag machinery at risk of failure and route a technician with the right parts; and for a medical device and health company, a next-generation contact center built with a systems integrator on Amazon Connect plus ServiceNow CRM, with the interaction tracked in ServiceNow.

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This is a repeated instinct: capability matters only if it arrives through controls the enterprise already trusts.

The Daybreak post defines the offering for authorized cybersecurity teams as advanced AI models that find, understand, test and fix software vulnerabilities faster, lists five defender tasks, splits the catalog into Daybreak Blue for frontier general-purpose models with safeguards for authorized defensive work and Daybreak Red for purpose-trained vulnerability research and security testing, and states that customers keep familiar AWS controls for security, access, governance and procurement.

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The reasoning is that peer proof sources the deal: a buyer who has watched a similar company describe extra value will choose the procurement route that captures it. McShane also attributes the compounding to continuing joint product investment rather than to a single campaign.

McShane recounts a California bank executive who approached the team about procuring ServiceNow through AWS Marketplace after watching one account executive's video about bringing AWS into a deal, and then reshares the series with the results attached: featured deals ranged from $35K to $10M in new annual contract value and $66K to $100M in total contract value, and a $400K deal closed in 2024 became a $10M account the following year, with that customer appearing as a panelist at K26.

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The closing ServiceNow post counts the achievement as ecosystem-wide and names partners, sales, and functions across Operations, Product, Solutions Consulting, Legal, Finance, Tax, RevOps, Marketing and Partner teams. The leadership post does the same at individual scale, crediting people for removing blockers, answering the phone, giving honest feedback, and acting today rather than next month.

McShane writes that the AWS business exceeded a five-year strategic goal in its first year and reached a billion dollars in under two years, and closes on the idea that the best leaders build people, not just businesses.

• In a separate post, McShane quotes Bill McDermott's line — "Dream Big.
• Elite Execution.
• Wear the Jacket." — attributing it to him.

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Start here because it is the only post in the set that pairs the origin story with named customer scenarios.

Speaking at AWS Summit in New York, McShane described starting ServiceNow's AWS business with no co-sell motion, no Marketplace presence, and no joint field coverage, then building it from the ground up.

• The post then walks through three concrete combinations of the two platforms: automated cloud governance for banks, where Amazon Bedrock plus ServiceNow's AI Control Tower and the Veza and Armis acquisitions give one view of every AI agent, what data it can touch, and what permissions it holds; predictive equipment maintenance at an auto manufacturer, using ServiceNow OT workflows with AWS IoT SiteWise to flag machinery at risk and dispatch a technician with the right parts; and a next-generation contact center for a medical device and health company, built with a systems integrator on Amazon Connect plus ServiceNow CRM, with the whole interaction tracked in ServiceNow.
• McShane also names the AWS and ServiceNow people involved, including Rich Geraffo, Michael P Kelly, and Whitney Bragg-Sabins.

For brands planning a campaign

Treat this as a template for joint positioning: pick a platform capability, pair it with a hyperscaler service, and name the buyer problem it removes (agent sprawl, unplanned downtime, call routing). A new AWS-focused GTM plan can reuse these three shapes and the language of "outcomes and value faster" rather than feature lists.

On leaving ServiceNow, McShane wrote that the AWS business exceeded a five-year strategic goal in its first year and reached a billion dollars in under two years, after an early period when the team "lost far more than we won."

• The post credits named groups rather than only a headline figure: the ServiceNow sales team, individual AWS counterparts including Ruba Borno, Rich Geraffo and Carol Potts, and functions across Operations, Product, Solutions Consulting, Legal, Finance, Tax, RevOps, Marketing and Partner teams.
• McShane frames the achievement as ecosystem-wide rather than individual, writing that great companies are built by entire ecosystems moving in the same direction.

For brands planning a campaign

The named AWS counterparts are a practical map of who already co-sells with McShane and can be approached for an introduction or a joint pipeline motion. The post also sets an expectation for how McShane credits partners, which matters when negotiating how a new alliance will be announced.

If you want to know how a new AWS-focused GTM would be run, this shows the operating rhythm.

McShane describes writing a charter for the OpenAI team covering the mission, the possibilities, and a 1-10-100 structure for scale, then reopening those slides at an AWS and OpenAI joint close lab in New York two months after a San Francisco lab and finding one of the "borderline impossible" goals already exceeded.

• The post compares the pace to building ServiceNow's AWS business from zero to a billion dollars in 22 months, and states that at OpenAI every person on the team has both the opportunity and the expectation to build a billion-dollar business in less than a year.
• McShane calls the intensity demanding, tiring and exhilarating, and names colleagues across OpenAI and AWS.

For brands planning a campaign

Useful as evidence of a specific management approach — explicit tiered targets, short review cycles, and public scorekeeping — that could be applied to a first-year AWS GTM plan. The comparison to the ServiceNow timeline gives a benchmark for how fast McShane expects a new alliance to move.

Read it to see how peer proof, not advertising, sourced a large deal.

McShane tells of a California bank executive who approached ServiceNow about procuring through AWS Marketplace after watching one rep's on-camera customer story about the extra value of bringing AWS into the deal.

• McShane then collected and reshared the series, noting the featured deals ranged from $35K to $10M in new annual contract value and from $66K to $100M in total contract value, and that one rep's $400K deal in 2024 became a $10M account the next year, with that customer appearing as a panelist at K26.
• McShane attributes the compounding effect to continued joint product investment with AWS and to reps willing to tell their stories publicly.

For brands planning a campaign

A low-cost, repeatable play: turn sales reps and customers into short videos, then use them as inbound proof for the Marketplace procurement path. Measure it in expansion, not views — the post's own evidence is a deal that moved from a few hundred thousand dollars to eight figures.

It is the best sample of the writing style the other posts assume.

Announcing that Daybreak models are available on AWS Bedrock, McShane leads with the business point — the fastest path from innovation to production — then defines the product in one plain sentence: authorized cybersecurity teams get advanced AI models to find, understand, test and fix software vulnerabilities faster.

• The post lists five defender tasks (discover weaknesses, reproduce vulnerabilities, develop and test mitigations, build threat detections, investigate incidents) and separates the offering into Daybreak Blue for frontier general-purpose models with safeguards for authorized defensive work, and Daybreak Red for purpose-trained vulnerability research and security testing.
• It also states that customers keep familiar AWS controls for security, access, governance and procurement.

For brands planning a campaign

A reusable launch structure for a co-sold product: lead with the time-to-value claim, define the product in one line, split the catalog into named tiers, then remove buyer objections by showing that existing procurement and governance controls still apply. That last step is usually what stalls marketplace purchases.

Read it for the mechanics rather than the strategy.

McShane notes that OpenAI demos shown at Executive Briefing Centers impress AWS audiences, then makes a defined offer: the first ten AWS teams to invite OpenAI to co-present at an upcoming customer EBC receive an OpenAI Pro subscription, valued at $200 per month for a year. The official details were to be shared at OpenAI and AWS happy hours in San Francisco and New York in August.

For brands planning a campaign

Shows a tactic for moving a hyperscaler's field teams from polite interest to booked joint activity: a capped, first-come offer with a named value and a scheduled event to collect it. Worth copying for a new AWS-focused GTM, with a limit low enough to create urgency and a metric tied to meetings held.

Written near the end of her ServiceNow tenure, the post credits specific leaders with specific behaviors rather than adjectives: Bill McDermott for building a culture where people believe they own the outcome and think like the CEO of their own business; Paul Fipps for late-night strategy sessions, calls from the other side of the world to remove an operational blocker, and challenging the team to think ten steps ahead; Eric Kropp for answering the phone and delivering without politics; Anshuman Didwania for hustle and systems-building and for a bar for excellence McShane describes as higher than anything previously experienced; Alix Douglas for honest feedback and an industry-wide network; John Aisien for a bias for action balanced with never missing a family event; and Michael Park for backing a vision early. McShane closes on the idea that the best leaders build people, not just businesses.

For brands planning a campaign

Use this to predict working style: McShane rewards responsiveness, blunt feedback and speed, and publicly credits individuals by name. A partner plan that assigns named owners for blockers and reviews will fit how she already operates; a plan built on escalation through titles will not.

The account is operational: the team built those motions from scratch, then exceeded a five-year goal in year one and reached a billion-dollar business in under two years. At AWS Summit NYC, McShane framed the next phase as taking that business further by delivering outcomes faster through the partner ecosystem.

Starts with the absent assets, then describes the build, goal, and milestone.

For brands planning a campaign

For an AWS-focused GTM brief, McShane is a direct fit on the earliest stage: no co-sell motion, no Marketplace listing, and no joint field coverage, then building each. A brand can evaluate McShane for launch design, partner-motion sequencing, and early field alignment rather than for maintaining an established alliance.

Examples: Source 1 · Source 2

McShane uses these to show how the alliance moves from story to operational outcome.

For brands planning a campaign

A campaign can follow McShane's example-led approach: pair a platform narrative with industry-specific workflows and named joint capabilities so partner value is inspectable. This fits enterprise cloud or AI campaigns where buyers need concrete use cases, not abstract alliance language.

Examples: Source 1

McShane then compiles ServiceNow-on-AWS success stories, noting deal sizes from $35K to $10M NNACV and $66K to $100M TCV, and a 2024 $400K deal that became a $10M account the following year.

For brands planning a campaign

McShane treats customer video as a pipeline asset, not just brand content.

• A brand can design a campaign that turns frontline seller stories into buyer-facing video and connects that content to Marketplace or partner procurement.
• The strongest use is a field-led customer evidence program with a clear route from content to transaction.

Examples: Source 1

McShane translates the launch for buyers: authorized security teams can find, understand, test, and fix vulnerabilities faster, and enterprises can use frontier AI through familiar AWS procurement and governance.

For brands planning a campaign

For an AI security or enterprise AI brief, McShane can bridge frontier-model capabilities and enterprise buying requirements. Use McShane where the campaign must answer governance, procurement, and authorized-use questions, not just model performance.

Examples: Source 1

The posts also describe joint close labs, AWS Summit appearances, and the expectation that each team member can build a billion-dollar business in under a year. The method combines a public target with a cadence of labs, events, and cross-company teaming.

For brands planning a campaign

A brand can evaluate McShane for founder-like or launch-energy campaigns where public goal-setting and operating cadence are part of the story. The evidence supports campaigns that need an ambitious, pace-driven partner narrative, with the caveat that the targets are self-reported.

Examples: Source 1 · Source 2 · Source 3

A later post thanks sales, AWS partners, and cross-functional teams. The posts treat people and culture as the reason execution worked.

For brands planning a campaign

McShane's public voice is relationship-heavy and generous with credit.

• That can fit employer-brand, partner-ecosystem, or internal-change campaigns where recognition and cross-company teaming matter.
• It is less suited to a hard product-feature campaign unless paired with the operational examples above.

Examples: Source 1 · Source 2

McShane also issues an offer to AWS teams: the first 10 to invite the team to co-present at a customer Executive Briefing Center receive an OpenAI Pro subscription for one year, with happy hours in San Francisco and New York. Another post describes an AWS and OpenAI Joint Close Lab in New York.

For brands planning a campaign

McShane uses events and field offers as activation tools. A brand can consider McShane for co-hosted EBCs, partner happy hours, joint labs, or field incentive campaigns that need a public call to action and a light commercial hook.

Examples: Source 1 · Source 2 · Source 3

Later posts mark a last day at ServiceNow, joining OpenAI, and then OpenAI and AWS work including the Joint Close Lab, Daybreak on Bedrock, and the EBC offer. The recurring theme remains 0-to-1 enterprise alliance building, but the platform pair changes from ServiceNow and AWS to OpenAI and AWS.

The reviewed posts do not state dates or confirm current employer details beyond McShane's own account.

For brands planning a campaign

For current campaigns, the OpenAI and AWS context is the most recent public focus, while ServiceNow and AWS experience is the deeper proof of the build method. Brands should not treat the older platform work as current employment; they can use it as evidence of transferable co-sell and marketplace experience.

Examples: Source 1 · Source 2 · Source 3 · Source 4 · Source 5 · Source 6 · Source 7

Later posts mark a final day at ServiceNow and thank named leaders there.

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The posts cover ServiceNow's AWS business built from zero with no co-sell motion or Marketplace presence, the launch of OpenAI's Daybreak models on Amazon Bedrock, joint customer labs, and co-hosting events. The posts describe partnership work, not employment at AWS.

View example

Both take a new platform capability and ask what has to be true operationally before it is worth anything, rather than stopping at the announcement.

Womack writes as an outside evaluator advising buyers to confirm the business problem, assess operational readiness and validate the roadmap before expanding licensing. McShane writes from inside the vendor alliance, describing how the co-sell motion, Marketplace route and joint field coverage were actually built and what they closed.

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Kadar's battery-level signal post and his three options for agentic commerce read much like McShane's list of what didn't exist yet and the customer workflows that followed.

Kadar's subject is fraud, identity and payment risk as AI agents start transacting, and his writing is aimed at risk and trust teams weighing verification choices. McShane's subject is alliance building and partner-sourced revenue, aimed at the teams designing a joint motion with a cloud provider.

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That combination of practical AI argument plus public credit for the people involved runs through McShane's ServiceNow posts as well.

Cohen's audience is distributors and the distribution software world, and the payoff he argues for is people spending less time holding data together and more time on relationships. McShane's payoff is a joint cloud business built to a revenue target, with the human note kept mostly to how the results were credited.

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The two retained posts work through ServiceNow's roughly $11.6B to $12B run of acquisitions in about six months — Moveworks for conversational AI and enterprise search, Veza for identity intelligence, Armis for cyber exposure across IT, OT, IoT and medical devices — and then hand the reader four steps to run before expanding licensing: confirm the business problem, assess operational readiness, validate the roadmap, and measure expected value against outcomes like faster employee resolution or tighter access control.

• The second post does the same for AI in ServiceNow's Australia release, testing each feature against whether it improves incident, change, service mapping or IT operations work, and landing on duplicate CIs, import-set problems and data quality as the places AI earns its keep.
• For a launch where the buyer needs a skeptical, buyer-side evaluator to explain why the new capability is worth adopting, that posture does more work than a joint-activity story.

Nothing in the reviewed posts shows co-sell, alliance building, or joint pipeline with a hyperscaler, which is the centre of McShane's case.

• The voice is also deliberately cautionary — it tells buyers to slow down before investing — so a vendor paying for a launch campaign would be buying a posture that includes public caution about platform investments, not just advocacy.
• Both posts are about ServiceNow, so the material shows depth on one platform rather than a hyperscaler partnership in motion.
• The packet carries no audience figures for this account, so reach cannot be compared against McShane's 12,198 LinkedIn followers.

Examples: Source 1 · Source 2

One retained post walks through catching 5,000 fake accounts on a large e-commerce platform from a single signal — every account reported the same battery level and an external keyboard — then traces them to a Chinese cloud device farm that rents real Android hardware and drives it with robotic process automation, and closes on the fix: an SDK flag, five similar farms taken down, and ongoing monitoring.

• The other takes on shopping agents, contrasting Amazon's block of Meta's Muse with Shopify and Walmart letting it in, and lays out three options for fraud teams before landing on verify-once-then-continuous-trust.
• Both posts make a mechanism concrete and end on a product consequence.
• For a buyer launching a detection or trust product, that is closer to the work than McShane's field updates.

The same posts are openly promotional for SEON, including an expansion announcement with a link, so a campaign for a competing product would place a rival vendor's positioning inside the buyer's launch.

• There is no co-sell, marketplace or cloud-partner motion in the reviewed material, so the alliance-acceleration half of the brief has no evidence behind it.
• The material is also tied to one category — fraud and identity — and a brief outside that category gets less.
• No audience or engagement figures were supplied for this account.

Examples: Source 1 · Source 2

One retained post describes hosting 30 distributors for dinner in Nashville, where customers compared what they had built with each other rather than talking about CRM, and credits a colleague for handwritten notes and wearable pins so people still evaluating the product could find someone to question.

• The other makes the argument that when AI absorbs end-to-end work, people get time for relationship-building, using a team member's 18-month ERP learning curve in distribution as the example.
• For a launch that needs a founder who can convene customers and speak about AI and work in plain language, the reviewed posts show that pattern being practised, not just described.

Cohen is the chief executive of the product being discussed, and both posts are about that company and its customers, so a campaign for a different platform would be asking for an advocacy voice the reviewed work shows is bound to a named employer — a conflict McShane's material does not raise.

• The brief's measures are joint pipeline and meetings with a cloud partner's field teams; none of that appears here.
• The reach claim in a consumer or broad-awareness brief cannot be tested either, since no audience figures were supplied for this account.

Examples: Source 1 · Source 2