What Really Happens When AI Becomes Your Teammate ft. Brady Bluhm & Kalpana Krishna Kumar

Most CS orgs say AI is going to free up their teams to do more strategic work. Fewer say what that work actually is, or how to know when you're doing it. In this episode, two practitioners inside Gainsight who've quietly rewired how they work gave us the most concrete answer we've heard.

---

Listen on YouTube, Spotify and Apple Podcasts

---

Three Things We’re Taking Away:

1. The 5-tool EBR stack is real and repeatable. Staircase (account health + wins) → ChatGPT (synthesis) → NotebookLM (per-customer knowledge base) → Gamma (deck generation) → human judgment layer. Kalpana uses this for every annual and quarterly business review.

2. Grassroots beats top-down for AI adoption. Brady didn’t wait for an enterprise mandate. A team plan, two volunteers, and a 90-minute weekly course built more genuine AI fluency inside Gainsight than a vendor rollout would have. The model is replicable anywhere.

3. “More strategic” means specific activities, not a mindset shift. For Kalpana, the freed-up time went to chairside sessions and instance health reviews she used to skip because there wasn’t time. That’s what expanding coverage without headcount actually looks like.

🎯 The [Un]Churned Take: What You Find When the Busy Work Is Gone

Brady Bluhm, Senior Product Manager at Staircase AI (Gainsight), and Kalpana Krishna Kumar, Enterprise CSM at Gainsight, didn’t come on the show to talk theory. Both have spent the last two years methodically stripping manual work out of their day and replacing it with workflows they actually want to be doing. This episode is the clearest inside account we’ve had of what that shift actually feels like — and what it reveals about what the CSM role was supposed to be all along.

The 80% Rule Isn’t About Speed

Both Brady and Kalpana use a version of the same mental model: AI gets them 80% of the way there, then they take it the rest. But the more interesting part isn’t the speed gain — it’s what the last 20% turns out to be. “My time is spent in the fine tuning,” Brady said. “The creative aspects. The key call-outs. The things I need to really curate.” That’s not a description of administrative work. It’s a description of judgment. Kalpana put the same idea in one line before the recording even started: “My purpose with using AI is to be able to get the best version of myself as quickly as possible.” The implication is worth sitting with: the best version of a CSM has always been there. The busy work was just in the way.

What Scaling 40% Actually Looks Like

Kalpana’s book of business grew from 25 accounts to 35 — roughly 40% — without adding headcount, without burning out, and without the Sunday-night dread that used to come with a big EBR on Monday’s calendar. Her workflow: pull account health and wins from Staircase, synthesize in ChatGPT, build a per-customer knowledge base in NotebookLM, generate the deck in Gamma, then add the judgment layer herself. Five tools, one output. “I go to bed without worrying that I have an EBR coming up next week and I haven’t done X, Y, and Z,” she said. That sounds small. It isn’t. Chronic prep anxiety is one of the most reliable signals that a team’s tools are extracting energy rather than giving it back.

The Activities That Were Always the Job

Kalpana now offers two things broadly that she used to reserve only for at-risk accounts: chairside sessions (sitting with customers live inside the product) and instance health reviews (a deep-dive into configuration against best practices). “I’m not being selective about it very much,” she said. “And I’m not worried about it because I can offer it and know that I will deliver.” That shift — from triage to standard practice — is what “more strategic” actually means when it has teeth.

The Grassroots Model That Didn’t Wait for Permission

Brady and a colleague named Seth Wiley started a voluntary weekly course inside Gainsight called “AI for All” — 90 minutes, practical exercises, no budget. About 45 people enrolled; 20 graduated and joined a Builders Club that still runs today. His advice for orgs that can’t get 150-seat enterprise licenses approved: start with the team plan, prove the use cases, make the business case. The grassroots model is slower, but it produces something a vendor rollout can’t — people who understand the tool well enough to teach it.

Wrapping Up

The CSMs winning on AI aren’t the ones with the most tools. They’re the ones who figured out which part of their job they actually want to be doing — and built backward from there.

See you next week 🧠

---

Where to find Brady Bluhm:

• LinkedIn: https://www.linkedin.com/in/bradybluhm/

Where to find Kalpana Krishna Kumar :

• LinkedIn: https://www.linkedin.com/in/kalpana-krishna-kumar/

---

Referenced in This Episode

• Staircase AI — Gainsight’s AI-powered customer intelligence product. Kalpana uses it to pull account health, engagement signals, and past wins for EBR prep. Brady uses it to get full customer context before calls without pinging the CSM. staircase.ai

• ChatGPT — Used by both Brady and Kalpana for synthesis, ghostwriting, and structured output generation. chat.openai.com

• NotebookLM — Google’s AI notebook tool. Kalpana keeps a notebook per customer, loading call transcripts and account data to build per-account knowledge bases and surface key themes. notebooklm.google.com

• Gamma — AI-powered presentation builder. Kalpana uses it as the final step in her EBR stack to turn synthesized content into a polished deck. gamma.app

• Claude (Anthropic) — Brady’s preferred LLM for writing, technical documentation, and agentic workflows. claude.ai