Gainsight

On Hiring and Backchannel Reference Checks: I've hired 1000s of people (and hundreds directly). And the truth is each hire makes me LESS confident in the science of hiring. Over time though, one thing I grew to appreciate was a candidate's self-awareness. I would ask a potential hire this question: "I'm going to do backchannels on you if you're ok with it. Everyone has promoters and detractors - including me. Who are your detractors and what would they say about you? Same with your promoters? How have you evolved based upon the feedback?" I learned so much about a person based upon that question. Do they know the situations where they didn't fit? Do they know the specific people they impacted? Did they change? For me, I know I have promoters and detractors. The latter (especially 5 years ago) might say: * "Slow to move on low performers" * "Got too stuck in his core business" * "Company depended too much on him" * "Too high of a fashion budget" So if I were asked this question, I'd know the people who felt it, what they would say and how I've evolved since. For a candidate, with this info I then call backchannels and actually ask this same question: "Everyone has promoters and detractors. What would each say about this person?" The insight here is the reference giver isn't forced to own the feedback. Instead, they can do what many do - share their own input guised as being from others. This gives you real insight into what they think. Or if they're truly channeling others' input, they can then balance it out with their perspective. The best hire I ever made, Chuck Ganapathi , was kind enough to let me subject him to this process when I brought him on as President. And he was SUPER open about his detractors. To the point that when I called his supposed detractors, they were more positive than he let on. And now Chuck is crushing it as CEO of Gainsight. Ultimately, this process was me optimizing for people with self-awareness. This isn't universally correct (I can think of countless successful people with low self-awareness). But for my style, it was vital.

6 Thoughts About FDE and Customer Success FDE is suddenly everywhere. Originally pioneered by Palantir, the idea is now being reinterpreted across many categories. At the same time, AI startups are trying to define the future of Customer Success. After 13 years running Gainsight and helping build the CS category, I get lots of questions from AI founders: “I have a CS team but want to make them FDEs.” “I have an FDE team but want to scale with CS.” So here are 6 thoughts: 1. CS and FDE share one goal: outcomes In our original Customer Success book, we defined CS as: “Customer Success is when your customers achieve their desired outcome through their interactions with your company.” OpenAI describes FDEs as helping customers move from AI opportunities to production systems with measurable results. Those ideas rhyme. CS was never just a CSM role. It was a company strategy across CSM, PS, Training, Support, Product and more. 2. Both shift outcome ownership to the vendor In the pre-SaaS model, the customer largely owned outcome risk. They paid upfront. If the customer never got value, that was mostly on them. SaaS changed the incentives. FDE may be changing them again. 3. Consumption makes this more important In SaaS, much of CS was defensive: retention, churn mitigation, and proving “would they have churned without us?” With tokens and consumption, the link is more direct. FDEs remove bottlenecks by finding use cases, implementing them, and helping customers expand into real workflows. The land may be easier. The expand is where the value is. 4. Consumption justifies more investment CSMs always wanted to drive business outcomes. But unclear ROI led companies to stretch them across too many accounts. It also limited investment in technical resources to turn customer learnings into deployment or product changes. Now FDEs are core revenue drivers, so companies can justify more technical and expensive profiles close to the customer. 5. You still need an ongoing relationship Historically, PS was project-aligned and CSM was account-aligned. That made sense. Deployment work has start/stop dynamics. Relationship and value management are perpetual. I’m seeing more mature AI orgs with FDEs add CSMs for ongoing value management. 6. Forget the titles. This is vital. Some say “FDE is just PS and CSM with a new name.” Others say “FDE is completely new.” As usual in tech, both contain some truth. But one thing is clear: it has never been more important to invest in the success of customers using AI products. In a world where technical moats may compress, deeply owning customer outcomes may be one of the best chances we have to build durable businesses.

19 prompts. That's what my colleague Brady Bluhm is giving away for free in our latest Substack. But the prompts aren't even the most useful part. Brady runs Staircase AI here at Gainsight and quietly became the person every team comes to when they want to know how AI actually works in their day-to-day. He wrote out his full stack: Claude, Staircase, MCP, how he wires them together, and what it's done to his output. If you're in CS or post-sales and you're still figuring out what "working with AI" looks like in real life, this is probably the most practical 10 minutes you'll spend this week. Oh, and yes — he played Billy the blind kid in 4C in Dumb and Dumber. Completely irrelevant. Read the article anyway. 👉 https://lnkd.in/ebEFP3dK

Developer Studio for Gainsight Communities is here 🎉 You can now build fully custom community widgets with your own code, connect them to external services, and deploy everything through Git automatically. Connect your community to GitHub. Declare widgets, scripts, and stylesheets in your repo, push to your watched branch, and it publishes. No manual steps. Need your widget to call an external API? Configure a Connector once. Any widget can use it securely. No credentials ever touch the browser. Write in VS Code, Cursor, or whatever you think in. Check the video to see me vibe-coding a widget with Claude. Your stack, your way. If you're building on Gainsight Communities, this one's for you.

In 1994, a kid named Billy got handed a shoebox with a headless parakeet in it. "Pretty bird..." 🦜 🤣 One of the worst customer handoffs in cinematic history. Zero context, misleading packaging, and a deliverable that fell apart the second it was opened. (still one of my all time favorite movies!) That kid was childhood actor Brady Bluhm . Let's fast forward just over 30 years... Brady is now an AI product leader at Gainsight and just dropped an awesome substack article on where AI is actually going for CS and revenue teams: context engineering. Talk about a career transition! The short version: prompt engineering was table stakes. The real unlock is what you give the model to think with... transcripts, account history, relationship signals, you know... the QBR feedback from eight months ago you've half-forgotten. Most CSMs sit on the richest contextual dataset in the company (customer data, folks!) and ship it to their AI tools the same way Lloyd and Harry shipped that parakeet. One tab at a time. Copy & pasting. Head taped on (OK, that's a stretch 🤣 ) Brady's point, and the one I keep coming back to, is that the teams piping in real customer context into their AI systems right now (through MCP, skills, reusable workflows) are building a compounding advantage while everyone else is still copying & pasting one transcript at a time. The gap is growing faster than most CS & revenue leaders realize. Check out this article. Then go ask yourself the question Brady asks after every task: is this something I'll need to do again? If yes, turn it into a skill. https://lnkd.in/grh-tMMi