Jim Thompson

A lot of the conversation around the recent software selloff is really about terminal value. During the 2022 software selloff, rising interest rates pushed down valuations, but no one seriously questioned whether Salesforce or ServiceNow would still be valuable businesses in 10 years. This time, the selloff is about something different. The market is starting to question whether the business models that justify SaaS valuations remain valid at all. One reason is that the seat model is breaking. When a team can do more with fewer people, companies stop expanding their seat count. With agentic AI, pricing will increasingly shift from predictable per seat subscriptions toward usage and outcome based models. Agentic AI also makes it possible to charge for outcomes, which puts software in direct competition with the much larger services economy for the first time. In the latest edition of B2BaCEO, I unpack what this month’s software selloff is pricing in and how the economics of software are starting to change. Full p.o.v. here: https://lnkd.in/gP25Qvzt

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Custom Software vs. Off-the-Shelf: The Value of Fit Over Cost It’s true — custom software typically comes with a higher upfront cost compared to off-the-shelf solutions. Off-the-shelf tools can be a great starting point, but they often require businesses to adapt their processes to fit the software. Over time, those workarounds add up — in lost efficiency, limited flexibility, and frustration. Custom software, on the other hand, empowers businesses to operate the way they want to operate — not how a generic platform thinks they should. Custom software isn’t for everyone, and it isn’t for every stage. But when fit, flexibility, and long-term ROI matter — it’s a conversation worth having. #CustomSoftware #SoftwareDevelopment #BusinessStrategy #DigitalTransformation #TechForBusiness

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Why We Use Custom Metadata To Simplify Flows “If you’ve ever had to update a flow because a picklist value changed or a rule shifted, you already know the pain of hardcoded logic.” https://lnkd.in/gTSViYmU

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I’m very much in the camp of empowering marketers to help themselves... thoughtfully. As a marketer, I value self-service. We need the ability to move, test, and adapt without having to go through layers of process every time. We also need guardrails and context so that work stays responsible and connected to the bigger picture. This piece does a good job of laying out how agent-based capabilities can support that balance in practical ways. Hope you find it as useful as I did.

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I like the Parmy Olson article "Salesforce and Friends Deserve This AI Squeeze" (Article in the comments - gift link). Provides some clarity on the great SAAS meltdown. The article makes the point that agents may replace the "tasks" but not the data and workflows. The apps may suck (many do) but the underlying data infrastructure acts as a "lock-in" for customers for whom the cost of moving off their incumbent provider is prohibitive. The AI wars are raging, SAAS is threatened and the AI providers are racing to compete. Not a whole lot of differentiation between them and now the (Anthropic / OpenAI) agents are threatening the market specific AI providers too. The real (data) wars are just beginning and the data management market is ripe for disruption. Switching data platforms is going to become a whole lot easier.

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Very cool to see Salesforce Ben highlighting Arovy! "A #Salesforce Data Dictionary is the foundation for analytics and AI... And fortunately, Arovy has built the most advanced data dictionary solution."

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Try asking a tailor for an off-the-rack suit, but custom-made. Sounds confusing, right? Operators ask providers the same thing. First, the request is a "template" solution, usually pointing to a GEO where they’ve seen it perform. Providers roll it out. And the same operators open 250 tickets the next day after signing: “Add a bonus flow like our competitor’s.” “Integrate this new PSP by next week.” “Why can’t we change the margins by ourselves?” Half of those requests are dev-heavy, and all of them are urgent. Is it still a template? Or already a custom build? After a while, the lines blur completely. The only thing that works is partnership. We’ve seen it work with GR8 Tech clients: collaborating closely on processes that actually keep the business moving. #sportsbook #igamingplatform #casinogames #bettingprovider

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In my ongoing conversations with clients, I hear feedback that Marketing teams are stuck in legacy systems, lagging in personalization, or wasting time on dev-heavy updates. Addressing this feedback, I am excited to share Velir's Sitecore XM Cloud migration solution to help you quickly get to a modern, AI-powered, data-driven marketing stack. This is a fast and easy way to solve big pain points many of you are wrestling with. This migration solution will instantly: Accelerate time-to-value Unlock personalization at scale Future-proof with a composable, cloud-native platform We’re not just migrating your site—we’re upgrading your marketing game. See how we do it here: https://lnkd.in/epU_M4Wg

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𝗧𝗵𝗲 𝗔𝗜 𝗴𝗼𝘃𝗲𝗿𝗻𝗮𝗻𝗰𝗲 𝗾𝘂𝗲𝘀𝘁𝗶𝗼𝗻 𝗶𝘀𝗻’𝘁 𝗷𝘂𝘀𝘁 𝗮𝗿𝗿𝗶𝘃𝗶𝗻𝗴 𝗮𝘁 𝗲𝗻𝘁𝗲𝗿𝗽𝗿𝗶𝘀𝗲 𝗯𝗼𝗮𝗿𝗱𝘀. 𝗜𝘁’𝘀 𝗮𝗿𝗿𝗶𝘃𝗶𝗻𝗴 𝗶𝗻 𝗲𝘃𝗲𝗿𝘆 𝗽𝗮𝗿𝘁𝗻𝗲𝗿 𝗰𝗼𝗻𝘃𝗲𝗿𝘀𝗮𝘁𝗶𝗼𝗻 𝘁𝗼𝗼. I’ve spent 20 years working with the channel – at Jitterbit, MuleSoft, EMC. The pattern I’ve seen is consistent: the partners who build durable client relationships are the ones who get ahead of the next board question before the client has to ask it. Right now, that question is: how do we adopt AI without losing control of costs, governance, and the systems we’ve already invested in? Maicell (formerly ConnectPlaza) was built to give partners a direct answer to that question. An integration platform that connects what clients already have, extends it with AI where it makes sense, and keeps everything governed and auditable from day one. No forced migration. No new vendor dependency. No governance bolted on after the fact. Witold Kepinski covered the full story on Dutch IT Channel. Link in comments. If you’re a partner working through AI adoption conversations with your clients – worth a read.

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Are you confident in the quality of your data? In today’s data-driven world, clean, reliable data isn’t just a nice-to-have — it’s a business necessity. Whether you're in analytics, marketing, operations, or IT, this is a conversation you need to be a part of to reduce errors, improve trust, and drive better decisions with clean data!

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