Shubham Goel is a company builder who co-founded Affinity, a CRM company, and says they are now building a new AI company. Goel also shares lessons from conversations with CIOs about enterprise AI adoption, governance, and technology change.
Shubham Goel is most useful for enterprise AI adoption and governance content from CIO conversations.
Best for
Enterprise software brands targeting IT and AI adoption leaders for interview-led content partnerships.
Not for
Consumer fintech reach campaigns measured by follower count or broad brand awareness.
Key takeaways
A team builds an app in two days but waits two weeks to ship.
A CIO's toaster method pairs enthusiasts with eager learners and gives late adopters tested examples.
A lead-scoring process had 17 customizations nobody could explain three years later.
Check first: Confirm audience demographics and engagement results for comparable CIO-conversation posts before budgeting.
Main ideas
Building AI faster does not mean companies can put it to work faster · Adoption works better when people get different kinds of help · Organizational complexity can become process debt
Shubham Goel is a company builder who co-founded Affinity and says they are building a new AI company with longtime collaborator Ray.
They are also known for sharing what CIOs say about enterprise technology and AI adoption.
Their posts connect big claims about AI to practical constraints: who approves new tools, how teams absorb change, and who is accountable when systems fail.
Their posts do not identify a signature book or show.
For examples of earlier work beyond Affinity and a now-defunct Harlem Shake website, ask them directly.
Goel makes enterprise technology problems concrete.
In one post, they describe a team that builds an app in two days but waits two weeks to ship it because security, governance, testing, and release reviews still take time.
In another, they relay a CIO’s “toaster people” method: find enthusiastic early users, pair them with people eager to keep up, then give late adopters tested examples relevant to their jobs.
These examples make their writing useful to readers weighing AI adoption: it focuses less on what a tool promises and more on the work required to put it into practice.
They also write about company building and event positioning, and occasionally share practical resources such as CIO job listings.
That range makes their feed broader than an AI commentary stream.
Shubham Goel’s recurring argument is that enterprise AI is not mainly a matter of building more tools.
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Companies also need the governance, people, processes, and connected systems to approve those tools, fit them into daily work, and take responsibility for their results.
Building AI faster does not mean companies can put it to work faster
Goel argues that AI development is running into limits in approval, security, adoption, and support.
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More tools can add to an already crowded IT backlog, while unclear ownership makes risk harder to manage. The question is not just whether a tool works, but whether an organization can safely deploy and maintain it.
Drawing on more than 100 CIO conversations, Goel contrasts building an app in two days with taking two weeks to get it into production. They also describe companies that do not know how many AI apps employees are already using or who owns the risk if one fails.
Adoption works better when people get different kinds of help
Goel presents technology adoption as a staged process, rather than expecting everyone to experiment in the same way.
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Find eager early users, let interested colleagues learn alongside them, then give less adventurous users relevant examples they can use without starting from scratch.
Goel attributes the “toaster people” approach to Allen Fazio, CIO at Houlihan Lokey and former CIO at Disneyland. As Goel recounts it, Fazio starts with people who like taking new technology apart, pairs them with colleagues who want to keep up, and gives other employees ready-to-use instructions and examples.
Goel argues that avoiding difficult decisions across departments can leave a company with exceptions and workarounds that become hard to understand or change.
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Companies can limit this by putting shared interests ahead of team preferences and giving a leader authority to make cross-department decisions.
Goel relays a CIO’s example of sales and marketing spending six weeks on a lead-scoring process with 17 customizations.
Three years later, people no longer remember why some criteria exist.
Goel uses the example to show how political compromise can create lasting operational friction.
AI depends on the systems and context behind the interface
Goel’s Dreamforce recap focuses less on a new screen than on the infrastructure behind AI interactions: data, context, governance, and agent management.
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They connect that shift to a practical question: whether enterprise systems can work together well enough for AI tools to be reliable.
Goel describes Salesforce presenting itself as an AI company and positioning its products to support interactions in tools such as Claude and Slack. They ask whether Salesforce can address underlying problems such as data quality, system integration, and security.
This is the only post that states the current venture and its stage, useful context before reading older material about Affinity or CIO conversations.
After a decade building Affinity, a CRM company, and taking a break, Goel and Ray are building a new AI company and hiring their first two sellers.
Early customer feedback has been strong.
Sales will target upper mid-market and lower enterprise buyers across industries, and the roles are San Francisco only, five days a week.
Goel lists grit, customer obsession, large-deal sales experience, pipeline sourcing, and early-stage experience as priorities, citing Affinity's growth to a global company with 500+ hires as the track record behind the new venture.
The post says more product details will come in a few months.
For brands planning a campaign
A vendor selling to early-stage GTM teams or AI-native startups could view this company as a potential early design partner or case study, but there is no product to co-market yet. Goel is actively shaping a sales motion and may be receptive to practical help with enterprise buyers—not broad brand awareness.
This post explains where the Affinity story begins and why Goel writes about co-founder trust and early company building.
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It offers the shortest path to understanding the relationship behind the current venture.
Before Affinity, Goel and Ray built maketheharlemshake.com, a now-defunct site that let people create Harlem Shake videos in three steps.
They met at Stanford orientation, lived in the same dorm, and got to know each other by building.
Goel describes the partnership as low ego and high trust.
Building Affinity meant learning to hire, let people go, win and lose customers, and have hard conversations at 20 years old.
The post ends with advice to choose a hackathon partner wisely.
For brands planning a campaign
For a brand considering a founder-led partnership, Goel's post shows how they tell origin stories with specific, self-aware detail rather than polished marketing language. A campaign about founder-to-founder learning, early-stage mistakes, or co-founder dynamics would have authentic material to work with.
This is the clearest introduction to Goel's CIO research format: a numbered list of specific problems raised by enterprise IT leaders, not general predictions about AI.
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Goel reports five themes from conversations with IT executives.
First, the citizen developer problem: teams build useful AI tools, then ask the CIO about governance, safety, and deployment.
Second, ownership of AI risk: some CIOs propose an independent 'Agentic AI Oversight Board' because the probability of something going wrong is high and IT bandwidth is limited.
Third, the emerging title of Agentic AI Manager: one person oversees a team of roughly 20 agents, with review capacity becoming the bottleneck.
Fourth, lost institutional knowledge, illustrated by one incentive: answering 50 questions in the company wiki raises a bonus by 5%.
Fifth, integration between systems such as CRM and ERP remains a roadblock.
For brands planning a campaign
A vendor selling AI governance, agent management, or enterprise integration could use this post to frame a webinar or research report around CIO buy-in. Its five headings map directly to product categories, making it a conversation starter with IT leaders rather than a top-of-funnel awareness piece.
Goel states the scale of the research behind the CIO series and names operating constraints that recur across posts, making this the best overview before reading individual examples.
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AI is the top topic across more than 100 recent CIO conversations, Goel writes, and much of the discussion centers on fear and pain. Four points stand out: a team can build an app in two days but takes two weeks to get it into production because governance, security, testing, and release processes still apply; shadow IT is becoming shadow AI because companies do not know how many AI apps are already in use or who owns the risk; businesses have limited capacity to absorb change, so even a better workflow takes time to adopt; and AI work lands on top of an existing IT backlog, adding decisions about who manages agents and who owns outcomes.
For brands planning a campaign
This is the strongest post for a campaign aimed at IT and AI-adoption leaders because it frames the buying problem as approval, adoption, and support capacity rather than tool availability. A vendor focused on governance, security review, or change management could build a co-marketing piece around the approval gap Goel describes.
This is Goel's most practical adoption walkthrough: a repeatable three-step method that credits a named CIO practitioner.
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Goel shares advice from Allen Fazio, CIO at Houlihan Lokey and former CIO at Disneyland, on driving adoption across 30 years of technology shifts.
Step one: find 'toaster people' who take technology apart and figure it out; give them time and resources, then see who uses a tool most in the first week.
Step two: pair the FOMO group with those enthusiasts so they learn alongside them and capture what works.
Step three: give late adopters relevant use cases and examples that work without hours of experimentation.
Goel closes by asking readers which type they are.
For brands planning a campaign
A vendor running an internal AI rollout or external adoption campaign could reuse this three-step structure almost directly, especially the advice to identify heavy early users before a broader launch. The named CIO example also gives a partnership or content collaboration a credible practitioner voice.
This post shows Goel as an event analyst, not just a CIO interviewer, capturing a moment when a major enterprise vendor changed how it describes itself.
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Reporting from Dreamforce, Goel argues it would be easy to mistake the event for an AI conference, citing keynote speakers Dario Amodei, Jensen Huang, and Sam Altman and product launches AIForce, AgentFabric, Salesforce Guardian, and Data 360.
Three takeaways: Salesforce wants to be seen as an AI company, with the headline 'welcome to the agentic enterprise'; the product is no longer the UI, as more interactions happen in tools like Claude and Slack while Salesforce supplies data, context, governance, and agent management behind them; and AI adoption is uneven, with Marc Benioff comparing adoption across companies to Waymo adoption across countries.
Goel ends with an open question: can Salesforce fix enterprise data, integration, and agent-management problems?
For brands planning a campaign
For a brand planning around an enterprise software event, this post shows how Goel turns a keynote into a positioning question centered on a named uncertainty. A co-marketing piece could pair vendor event commentary with a practical follow-up on the enterprise problems Goel flags, rather than repeat launch announcements.
This post takes one CIO conversation and follows it to a concrete business diagnosis, showing how Goel turns a single remark into an argument rather than a summary.
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Goel relays a CIO's observation that much complexity comes from people being unwilling to push back, and calls the result “process debt.”
For example, marketing and sales disagree on lead-scoring criteria, so the company spends six weeks building a Frankenstein process with 17 customizations and exceptions for whoever argued loudest.
Three years later, nobody remembers why half the criteria exist.
Goel proposes two fixes: build a low-ego culture where people put company interests ahead of team interests, and empower the COO to make hard cross-department calls.
Their conclusion: the most valuable action is often making hard business decisions before they become expensive technical problems.
For brands planning a campaign
A vendor selling CRM, ERP, or process-consulting services could use this example to reframe a lead-scoring or customization conversation around governance and decision rights. The 17-customization image is memorable enough to anchor a short campaign piece or sales-deck slide.
This is the one post here aimed at CIOs and candidates rather than enterprise buyers, showing how Goel serves the executive audience directly.
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Goel shares 12 open CIO roles readers have asked about, with employer, location, and salary range for each where listed.
Examples include Stanford Doerr School of Sustainability, Amplify, TeraWulf, nVent, Sysco, FairSquare, Aramark, Dartmouth College, and UnitedHealth Group's Optum Serve.
Several entries include salary bands such as $250K to $290K, $300K to $325K, and $200K to $343K.
Numbered entry 11 is missing; ask for its details if you need a complete list.
For brands planning a campaign
A recruiting, HR technology, or executive-search brand could use this post to reach technology leaders with career information.
It serves readers rather than promoting a product or vendor, so keep any partnership from turning it into an ad.
It is the least useful item for a campaign selling enterprise software.
The CIO conversation as a repeatable content format4
Founder building, company updates, and GTM hiring2
A persona-based adoption playbook1
Process debt and organizational complexity1
Conference and event takeaways1
CIO job-market curation1
Enterprise AI adoption as an operating problem
Across several posts, Goel returns to the gap between building AI tools and getting them approved, adopted, and governed.
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Recurring concerns include citizen developers, shadow AI, unclear ownership of AI agents, security and data integration, limited management capacity to review agent work, and approval processes that slow production even as development speeds up. Goel links these observations to CIO conversations and Salesforce's Dreamforce messaging about uneven enterprise AI adoption.
Conversation-led synthesis: Goel distills multiple CIO conversations into numbered lessons, then closes with a question inviting readers to share their priorities.
For brands planning a campaign
An enterprise software company targeting IT and AI-adoption leaders can work with Goel to address the bottlenecks buyers face after a pilot: governance, integration, and rollout capacity. A content partnership could have Goel interview customer CIOs and turn those conversations into practical lessons, tying claims to named sources rather than a vendor pitch.
The CIO conversation as a repeatable content format
Goel draws on a stated volume of CIO conversations and structures the findings as numbered lessons or top takeaways.
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Posts follow a consistent shape: brief context, itemized observations, and a closing prompt for reader participation. The format gives a brand a predictable basis for sponsorship or co-production, but needs fresh primary conversations to avoid repeating themes.
Numbered lessons drawn from direct conversations, usually ending with a question for the audience.
For brands planning a campaign
A series of co-branded CIO roundtables, interview recaps, or executive briefings could work, with Goel as interviewer and synthesizer. Partners should supply new source conversations or data to keep the output from becoming a generic list.
In the toaster method post, Goel relays a CIO's approach to technology adoption: find enthusiasts, or "toaster people"; pair them with FOMO followers; then give late adopters ready-made examples and instructions.
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It's a concrete change-management method, not a general argument about AI.
Unlike the broader CIO synthesis posts, this item names a specific CIO and centers on an adoption metaphor rather than AI governance.
For brands planning a campaign
This is strong material for an enterprise software company whose product depends on internal adoption.
A co-marketing piece could turn the toaster method into a practical rollout worksheet or customer workshop, using Goel's interview as the source narrative.
Since the method comes from one executive's account, present it as an approach to test, not a proven playbook.
Goel argues that politics and a lack of pushback create process debt: custom invoicing rules, CRM workarounds, and over-customized lead scoring that eventually slow enterprise agility.
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Suggested fixes include a low-ego culture and empowering a COO to make hard cross-department calls.
For brands planning a campaign
Useful for positioning enterprise software around simplification, governance, and operations. A brand could sponsor a discussion or guide on avoiding process debt, but should not present the argument as product-specific proof.
Goel shares that after building Affinity, they and Ray are building a new AI company and hiring early sellers.
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A separate post tells the Affinity origin story and emphasizes the value of a trusted co-founder.
Not an enterprise technology topic; relevant mainly as background on Goel's company-building record.
For brands planning a campaign
This audience is founder- and operator-oriented, not primarily enterprise IT buyers. For campaigns targeting IT and AI-adoption leaders, these posts support Goel's credibility as a repeat founder and potential interviewee, but offer weaker evidence of reach than the CIO-conversation content.
The Dreamforce post summarizes announcements about Salesforce as an AI company, AI agents, data, and uneven enterprise AI adoption.
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Goel turns a large industry event into a compact set of takeaways and closes with an open question for readers.
For brands planning a campaign
A practical fit for event-based co-marketing: sponsored attendance, executive recap posts, or follow-up webinars that translate conference themes into buyer implications.
Goel lists open CIO and IT leadership roles with locations, salary ranges where included, and application links.
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The post serves IT leaders considering their next role.
This is a roundup of external job links, not a synthesis of Goel's CIO conversations.
For brands planning a campaign
This niche audience-service format could suit recruiters, leadership networks, or enterprise vendors seeking to reach senior IT talent. It is not a direct product-education format; sponsors need a clear reason beyond logo placement.
Goel refers to Claude as the model Salesforce demoed at Dreamforce and suggests giving teams access to Claude to find early AI adopters, including through its Skills and Design features.
Numbered posts built from CIO conversations collect what IT leaders say about AI adoption, governance, security, and rollout.
The Dreamforce recap turns a major vendor event into buyer questions, while the toaster-method and process-debt posts offer concrete arguments about change management and operations.
Company-building posts add background on their founder path, and the CIO job roundup presents a service format for IT leaders.
Together, the posts show a consistent approach: brief context, a named source or conversation, numbered observations, and a closing question for the audience.
Keenan also writes for readers tracking enterprise software strategy in the Salesforce ecosystem, including AI agents, platform governance, and what acquisitions mean for customers.
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Keenan’s posts dig into vendor strategy and release or DevOps tooling, often through long-form analysis and reported deal detail; Goel’s package CIO conversations as numbered adoption lessons.
Markman posts about AI adoption, Salesforce, and whether enterprise technology delivers ROI, overlapping with Goel’s focus on the gap between AI demos and production use.
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Markman writes opinionated hot takes and questions vendor claims directly; Goel focuses on CIO interview synthesis and practical operating questions.
Mansfield also covers Salesforce from the customer’s side, including acquisitions, pricing, licensing, and procurement questions that affect enterprise software buyers.
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Mansfield focuses on procurement and commercial leverage—what customers should ask and how licensing changes; Goel focuses on adoption, governance, and the operating constraints inside IT.
Goel's posts show what Goel posts about, not who reads them.
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Eight LinkedIn posts published between 16 September and 7 October 2026 cover enterprise AI adoption, who owns AI agents and AI risk, CIO operating constraints, and vendor positioning (a Dreamforce day-one recap).
A separate post lists open CIO roles, and several posts (the Affinity origin story, the new-company hiring call) speak to founders and go-to-market people rather than to IT buyers.
That topical mix is a reasonable signal of appeal to enterprise technology decision-makers, but it is an inference from subject matter, not a measurement of the readership.
Measured audience composition published in the posts here is thin.
The only audience figure published here is a LinkedIn follower count of 6,765, observed 9 October 2026.
The posts here give no follower geography, industry, job seniority, or role, and include no per-post engagement counts (impressions, reactions, comments, shares).
So the posts here cannot show whether those followers are CIOs and IT leaders, other vendors, recruiters, or general observers of the AI-news cycle.
No video or podcast audience data is published here, so format-level audience comparisons are not possible.
For a campaign aimed at IT and AI-adoption buyers, the practical reading is: the content is written at the level of enterprise IT leadership, and the CIO-conversation posts are the closest match to an IT and AI-adoption buyer.
Treat that as a placement hypothesis to verify, not a proven audience match.
Next step: ask Goel for (1) LinkedIn follower demographics or an audience survey covering seniority, industry and geography, and (2) engagement results (impressions, reactions, comments, shares) for two or three posts closest to the campaign need, such as the CIO-conversation posts and the Dreamforce recap, at comparable topics, depth and format.
If a sponsored placement is being priced, request results from a comparable sponsored post as well.
Requesting recent results for comparable topics, depth and formats is the minimum needed before budgeting.
LinkedIn followers
6,765
LinkedIn profile @shubham-goel-7b723419, follower count recorded in the account evidence · 2026-10-09
Shubham Goel’s posts do not describe a sponsorship offer, media kit, rate card or partnership terms.
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Across eight LinkedIn posts published between mid-September and early October 2026, they write about enterprise AI adoption as a founder who talks regularly with CIOs, and about building companies.
None describes sponsored content, paid placements, affiliate arrangements or a route for brands to inquire, so partnership formats remain unconfirmed.
The posts offer themes a co-marketing or content partnership could draw on: CIO priorities such as AI governance and oversight, shadow AI, change fatigue, process debt, and the gap between building fast and shipping fast, alongside a founder narrative around Affinity and a new AI venture.
Buyers should treat any partnership as bespoke and ask Goel directly about scope, deliverables and disclosure before planning around it.
Fit for an interview-led content partnership. Goel’s strongest and most frequent material draws on CIO conversations about what happens after an AI pilot: who governs a tool a team built on its own, who owns AI risk, why a two-day build takes two weeks to reach production, and why systems such as CRM and ERP still do not talk to each other. That is the same ground the brief’s buyers are trying to cover, and Goel already writes about it in a format a sponsor can use: brief context, numbered observations from named conversations, then a question for readers. Clear examples include the five-lessons post based on conversations with IT executives at large banks, telecom and technology companies, and the post summarizing more than 100 CIO conversations about build speed versus shipping speed. Goel also turns a single conversation into a practical method, as in the toaster post, where a named CIO describes finding enthusiasts, pairing them with the FOMO group, and giving late adopters ready-made examples. The process-debt post turns another conversation into a business diagnosis: a lead-scoring process with 17 customizations that nobody can explain three years later. A vendor whose product addresses governance, security review, integration or rollout capacity has a natural reason to join the conversation.
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Brief
An enterprise software company wants to reach IT and AI adoption leaders; propose a co-marketing or content partnership.
Reasons
The recurring subject matter matches the buyer’s concerns. Goel returns to adoption, governance, approval and integration bottlenecks rather than general AI commentary.
The format is predictable and repeatable. Numbered lessons drawn from conversations give a partner a structure to co-produce against, and Goel has used it across several posts.
There is analysis, not just summary. The Dreamforce day-one post examines vendor positioning and ends with an open question about whether the underlying enterprise problems will be fixed, giving a sponsor more to work with than a recap.
Goel has relationships to draw on. The posts describe a substantial volume of CIO conversations and quote at least one named practitioner—the raw material for a co-marketing series.
A campaign aimed at a particular need does not require a published sponsorship menu; Goel’s posts list none. A content partnership would be bespoke and negotiated, not selected from published rates.
Limits
Audience composition is unproven. The only audience figure in Goel’s posts is a LinkedIn follower count of 6,765, recorded on 9 October 2026. The posts do not identify followers’ job titles, seniority, industries or geography, so it is unclear whether they are IT leaders or mostly other vendors and observers. Treat the match as a placement hypothesis; ask for follower demographics and engagement results for two or three comparable posts before budgeting.
Goel’s posts show no engagement counts, per-post performance or comparable sponsored-post results. Ask for those results before setting a price or making a reach claim.
Several posts target founders and go-to-market readers rather than IT buyers, diluting the account-level signal.
One post rounds up open CIO roles. It serves the executive audience directly but is not a product-education format.
Poor fit for a reach buy. Goel’s posts do not address a consumer audience. The writing targets enterprise technology leaders and, in a few posts, founders and sales hires; a consumer fintech buyer would be reaching a different reader. There is also no evidence to support a reach-based purchase: the only audience figure in the posts is a LinkedIn follower count of 6,765, and they list no impressions, reactions, comments or shares. A follower-based or reach-based campaign would rely on numbers the posts do not show.
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Brief
A consumer fintech app wants broad brand awareness through a high-volume creator campaign measured by reach and follower count.
Reasons
The subject matter is enterprise adoption, governance and operating constraints. None of the eight posts address consumer finance, personal money management or consumer behavior.
The format relies on access to executives and synthesis of their conversations. That does not suit a mass-reach brief measured by impressions.
Goel’s posts do not provide audience composition. A consumer brand would be guessing who actually reads the account.
There is no documented reach performance or published sponsorship terms, so a reach-priced deal cannot be benchmarked against alternatives.
Alternative
If the consumer fintech brief is fixed, shortlist a different creator with consumer audience data. If the brand instead wants to reach enterprise buyers inside banks and fintechs, this account becomes relevant, but the campaign should focus on adoption and governance rather than reach.
A co-marketing series with an enterprise software vendor selling AI governance or agent-management tools, aimed at IT leaders who already have AI pilots running.
Campaign angle
Run a short interview series on agent oversight, with the sponsor providing access to its customer CIOs and Goel conducting and writing up the conversations. The series builds directly on material already in their posts: who owns AI risk and why some CIOs want an independent oversight group, why agents need a manager to review their work, and why approval and integration slow production even when development speeds up.
Deliverables
Three co-authored posts in Goel’s numbered-lessons format, each based on one or two named CIO conversations provided by the sponsor, with the sponsor’s involvement disclosed in the post.
One longer written piece consolidating the three conversations and ending with actionable decision points, such as who owns an agent’s output and what the approval path looks like.
A closing discussion prompt written for the series, not generic boilerplate, so readers who have run pilots can share their own constraints.
Named CIOs or senior IT leaders willing to be interviewed and quoted, with employer attribution agreed in advance.
New primary material, not a restatement of public announcements. The series works only if the conversations are fresh; otherwise, it repeats themes Goel has already published.
A subject-matter reviewer from the sponsor to keep product claims accurate without turning Goel's synthesis into a product pitch.
What good looks like
Test the finished piece against its reader task: a CIO should be able to name one oversight decision the company has not yet made, say who currently holds it, and describe the next internal step. If readers recall only the sponsor's product, the series failed at its reader task, even if the placement performed. Consider a related deliverable: a working rollout worksheet built from the toaster method and credited to the named CIO whose account it came from. The material already reads as a three-step method rather than an argument.
Choose Keenan when the campaign needs dated, source-linked analysis of Salesforce's own roadmap and commercial posture rather than interview synthesis.
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The two posts read the ServiceNow acquisition of Sweep as a strategic signal — a "Delivery Digital Twin" that lets ServiceNow govern Salesforce estates without moving customer data — and reconstruct Salesforce's AIforce launch as a timeline of five acts across 168 days, quoting the co-founder and the release and noting that pricing and packaging are subject to change. A sponsor selling platform governance, release management or agent oversight could place its message in this kind of long-form analysis, where readers are already thinking about how enterprise systems are governed and what a vendor's announcements actually commit to.
The writing draws on public announcements and press reporting, reinforced by the writer's own published analyses, rather than first-hand conversations with named buyers.
Goel's posts draw on statements about 100+ CIO conversations and at least one named practitioner, giving partners quotable first-party detail and a repeatable interview format.
Keenan's pieces carry an analyst's voice and a delivery scorecard; a partnership there looks closer to sponsored research than a conversation series, offering argument and sourcing rather than buyer voices.
Choose Markman when the sponsor wants an operator-voiced counterweight to launch messaging.
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The posts state flat return on investment as a personal mission, argue that small teams with the right tools can outrun larger ones, and challenge the claim that AI replaces the interface: they predict under 20% of users will be independent of logging in a year after Dreamforce, name KPIs, clean data and permissions as the real barriers, and describe the cost of a premature production bet as a year of cleanup, a trust hit and a board question. A vendor selling data quality, governance or production readiness could use that skepticism as the frame for its own offer.
Markman argues a thesis rather than reporting what buyers said.
The two posts rest on personal assertions, one cited macroeconomic source and one funding example, while Goel attributes observations to CIO conversations and a named CIO and gives readers a method they can follow.
Markman's willingness to call unpriced, half-GA platform bets a bad idea also cuts against a vendor's launch narrative.
The fit is with sponsors whose product can withstand the argument that the platform wave will not solve the hard problems, not those seeking a neutral host.
Choose Mansfield when the campaign's decision point is a renewal or contract negotiation rather than adoption.
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The posts treat Salesforce news as commercial news for customers: the reported $2 billion purchase of Listen Labs at roughly 67 times annualized revenue, and the new suites that bundle Slack, Tableau Next, Premier Success and AI consumption credits.
Mansfield urges customers, especially those with renewals coming up, to get ahead of the changes and ask their representatives what they mean.
A sponsor selling procurement advisory, license optimisation or third-party support reaches buyers as they weigh cost and lock-in.
Mansfield's framing is openly adversarial toward vendor economics: Mansfield asks whether an acquisition pays off for customers or investors, and warns that any answers may not be insightful.
That is strong ground for a buyer-side service and a poor host for a vendor's own bundling or pricing message, whereas Goel's posts describe adoption and governance obstacles without directing readers against a supplier's commercials.
Mansfield's posts are also short procurement commentary, leaving less room for a sponsor seeking a longer co-produced structure than Goel's numbered-lesson format provides.
Eight LinkedIn posts Shubham Goel published cover CIO conversation recaps on enterprise AI adoption and governance, a Dreamforce recap, a named-CIO adoption method, process debt, company-building history, hiring, and a list of open CIO roles.
The posts describe co-founding Affinity with a longtime collaborator, an earlier Harlem Shake project, a new unnamed AI venture, and a recurring focus on the approval, governance, and integration work that follows an AI pilot.
The posts carry no individual publication dates, so they do not show how views changed over time.
They also do not provide audience composition or engagement data beyond a follower count recorded in October 2026.
The posts do not establish whether Goel has a signature book, show, or other public work beyond the businesses they describe.
Brand relationships and campaign fit are reasoned from the published writing, not from interviews or third-party profiles.