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Jeff just shipped an internal CS platform to his team at Junction, imposter syndrome and all. He and Jay unpack what it means when software is effectively free: CS teams prototyping features before product gets to them, ops becoming the AI team, and why every agent needs an interface that isn't a chat window. KEY TAKEAWAYS Ship before it's perfect: Get the tool in people's hands. Broken things surfaced fast, and cross-functional ideas followed.Software is the new spreadsheet: Nobody is self-conscious showing execs a spreadsheet. Custom apps are heading the same way.Prototype the roadmap gap: CS and a solutions engineer can get a deprioritized feature 70-80% built, then hand it to engineering.Every software company becomes an FDE org: As packaged software loses value, the edge is tailoring the last 20% to each customer.Make AI visible: A "How I AI" channel of real screenshots and skill files shows people what's possible.Ops is the AI team: Ops should run ahead, building tooling and data plumbing AI first.Less instruction, better outcomes: Clear intent beats over-specification with AI and with people.The Ship It list: If you do it more than once a week, it goes on the list. A Friday tiger team tries to ship one in an hour.Every agent needs an interface: Humans need a purpose-built harness to review agent output and act, with a high bar for what reaches them.CHAPTERS 00:00 - Intro and the Q4 crunch00:55 - Jeff ships an internal CS platform03:34 - Is a custom app the new spreadsheet?04:15 - Building features product won't get to this quarter06:40 - Forward deployed engineering and "software is free"09:01 - Owning the last 20% for customers10:16 - An AI-first mindset and a "How I AI" channel12:42 - Why ops should be the AI team13:44 - Two-sentence prompts15:35 - Less instruction, better outcomes17:41 - The Ship It list and Friday tiger team19:05 - Every agent needs a custom interface23:03 - Raising the bar on what reaches humansAbout the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Most product companies don't have a shipping problem. They have a problem turning what they ship into money. In this solo episode, Jay Nathan, CEO of Balboa, breaks down product success: the loop that connects building, launching, adopting, and renewing, and the 5-step method his team uses with 200+ clients. KEY TAKEAWAYS Goals aren't strategy: "Grow 30%" is a goal. Good strategy has a diagnosis, a guiding policy, and coherent actions.Name the real problem: Year-one churn usually means customers never activated. Diagnose first, then act.Find your Herbie: Every system has one constraint. Improvements anywhere else are the illusion of progress.AI moved the constraint: Engineering is no longer the bottleneck. Adoption, enablement, and selling are.Product success is a loop: Market needs, launch and release, adoption, and customer lifecycle feed each other.Departments are the problem: The loop works when teams share one view of the customer and one strategy.Segment before you solve: A grid of segments by product turns "adoption is low" into a specific, fixable gap.Climb the measurement ladder: Signals feed leading indicators, then lagging indicators, then KPIs tied to the P&L.ABOUT YOUR HOST Jay Nathan is CEO of Balboa, which helps product, CS, and go-to-market teams turn product data into growth. He has led CS and go-to-market teams for 20+ years. Connect with Jay on LinkedIn CHAPTERS 00:00 - Why shipped software doesn't turn into money01:29 - Good Strategy, Bad Strategy primer02:24 - Four signs of bad strategy03:47 - The kernel of good strategy05:19 - Example: fixing year-one churn08:51 - Patterns from 200+ Balboa clients11:57 - The Goal and finding your Herbie15:59 - AI moved the constraint to adoption17:03 - Defining product success19:02 - The product success loop24:40 - Why departments are the problem25:20 - The Insights to Impact method26:45 - Step 1: Segmentation30:58 - Step 2: Prioritization33:59 - Step 3: Strategy definition35:57 - Step 4: The measurement ladder38:35 - Step 5: Deploy, measure, iterate40:16 - Beyond product analytics42:19 - This week's challengeAbout the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jeff is back from Junction's Portugal offsite with a reminder: most of your company knows far less about your customers than you think. Jay and Jeff dig into pushing customer insight into the business, why AI-built internal tools are now table stakes, and what Salesforce's reported $2B Listen Labs deal says about AI talking to customers. KEY TAKEAWAYS Your company doesn't know your customers: A half-day "who are our customers" session gave engineering a clearer view of how the product is actually used.Push beats pull: A Slack channel of customer quotes builds context but rarely drives action. Shadowing rotations, all-hands stories, and planning meetings do.Make insight capture a button press: Summarize calls daily and let CSMs approve what becomes a ticket, with a human in the loop.Internal tools are table stakes: Anyone can build them now. Alignment, strategy, and consistent communication from a leader are the differentiator.People stop reading AI: Jay cites a stat that 78% of readers quit when they detect AI, and most never come back. That includes agent-sent job applications.Weeks of work in minutes: Jeff built an interactive segmentation and account-transition tool in under 10 minutes. Rolling it out is still human work.Enterprise AI deployment is the opportunity: Agent-to-agent work gets complicated fast at scale, and public-company CEOs will soon face pressure to prove adoption.CHAPTERS 00:00 - Intro and Jeff's Portugal offsite01:45 - A half day on "who are our customers"04:09 - Operationalizing customer insights05:10 - Call-to-ticket workflows and all-hands rituals07:32 - The customer quotes channel and finite attention10:10 - Push vs. pull and shadowing rotations12:07 - AI is just technology: the factory robot lesson13:38 - Junction's company-wide support rotation15:05 - Leadership is the differentiator17:49 - The 78% stat and agent-sent job applications20:32 - Building a segmentation model in minutes22:01 - The future of customer success23:24 - A tool for CSM-to-CSM account transitions25:37 - Salesforce acquires Listen Labs27:50 - The harness race and the work/home AI divide30:14 - What personal AI assistants actually cost32:15 - Would you talk to an AI moderator?33:44 - Agents as necessary friction34:53 - Agent-to-agent work and enterprise AI deployment37:04 - Wrap-up and The GoalAbout the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Ziv Peled, Chief Customer Officer and Chief AI Officer at AppsFlyer, joins Jay to unpack how a $500M+ ARR company moved everyone to Claude, built its own AI stack, and now measures every role by "AI leverage." Plus: why Salesforce should resell Claude, and why FDE really means net dollar retention. KEY TAKEAWAYS Everyone is a builder now: Building isn't writing software. It's workflows, skills, and automations, and leaders have to be hands-on to know what their teams need.Work 24/7 without working 24/7: Split work between you and AI, keep agents busy around the clock, and step in for a quick eval when a human is needed.Agents from a central place: AppsFlyer built an MCP, semantic layer, and data lake over 29 data sets so 800 people inherit agents instead of each building their own.Classifiers power automation: Fast, cheap, typed models make agent decisions like routing a customer request reliable in under a second.Build near the system of record: Own your Salesforce, NetSuite, and billing developers. Buy at the application layer.FDE is NDR: Forward-deployed engineering isn't professional services. It's about outcomes the customer judges, tied to retention.Measure AI leverage: If an SDR goes from 5 to 10 meetings a month, that's 100% leverage. Measure end-of-funnel, quality KPIs.ABOUT OUR GUEST Ziv Peled is the Chief Customer Officer and Chief AI Officer at AppsFlyer, where he leads AI strategy across go-to-market while guiding a 170-person CS org. He previously served as VP Product and CCO at AppsFlyer. Connect with Ziv on LinkedIn CHAPTERS 00:00 - Catching up: Israel's tech moment06:08 - AppsFlyer's strategic investment from Meta, Google, Moloco, and Unity07:04 - From CCO to Chief AI Officer09:45 - Why every leader needs to be a builder10:13 - Assistants vs. automation and the new adoption curve13:24 - Multiplayer AI for teams15:14 - Inside AppsFlyer's internal AI stack19:56 - Splitting time between CAIO and CCO22:53 - The 24/7 mindset and human-in-the-loop evals25:44 - The AI budget equation27:01 - Teaching people to think like designers29:57 - Classifier models and go-to-market use cases34:59 - Build vs. buy39:08 - Salesforce, Anthropic, and the GRR play44:33 - The value era for customer success46:07 - The sewing machine story48:07 - FDE is net dollar retention52:25 - The AI leverage scorecard54:52 - Goodhart's Law and wrap-upAbout the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jay and Jeff dig into why Harvey went from SaaS to AI implementation, why agent infrastructure has to be a company-wide investment, and why the personal-agent wave is a platform war, not an app war. Then they get honest about AI writing: 78% of readers stop reading when they suspect AI wrote it. KEY TAKEAWAYS Paid AI is still niche: A16Z data shows only ~3% of US consumers pay for AI themselves, but the youngest buyers adopt at 4x the rate of the oldest.SaaS to AI implementation: Harvey went from app to harness to its own models, and now deploys that know-how inside clients as forward deployed engineering.Centralize agent infrastructure: When every department builds its own agents, context fragments. CS, support, product and engineering should share one customer brain.No plumbing, no agents: Messy CRMs and unused data warehouses mean you often have to build the infrastructure before agentic work pays off.Platform war, not app war: Most personal agents look the same. You'll buy into ecosystems (Meta, Amazon, Google, Apple) based on where your data lives.Don't use the words it suggests: LLMs write in magazine headlines and encourage your first-draft impulses. Readers sense you've become "artificially flavored."Readers punish AI writing: 78% stop reading suspected AI content and 71% avoid the author going forward.Use AI as researcher and editor: Let it gather sources, opposing views and data, then write yourself. Save generation for templated assets built from verified sources.CHAPTERS 00:00 - Welcome and AI in high school01:38 - Only 3% of consumers pay for AI04:19 - Meta Muse negotiates on Facebook Marketplace06:30 - Harvey's shift from SaaS to AI implementation10:59 - Why agent infrastructure should be centralized13:19 - You're never that far behind14:11 - Selling agentic work without the plumbing14:53 - Tool FOMO: Instinct, Town and Muse17:27 - A platform war, not an app war20:01 - Jay goes back to writing on his own23:28 - Two rules for writing with LLMs25:38 - Readers abandon AI-written content28:03 - AI for research, not writing29:48 - AI slop in client presentations31:19 - Claude in Slack and trusting AI messages32:18 - Branded two-pagers in seven minutesAbout the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jeff built seven screens of a customer success platform from one throwaway prompt, then sat in disbelief for three minutes. Jay argues he didn't build a platform at all — he built a UI, and that distinction may reshape who owns the CRM layer. Plus: the most pragmatic AI adoption playbook either host has seen, from a 700-person bank. KEY TAKEAWAYS You're building a UI, not a platform: The data layer, permissions, and system of record still have to live somewhere. Generated interfaces sit on top — they don't replace it.Make models check each other: Jeff runs Claude and Codex against the same codebase and PRs. Trusting one model unchecked is how quiet mistakes ship.Bake permissions in on day one: Field-level controls are cheap to design now, expensive to retrofit after someone overwrites a CRM field.Agents are employees, automations are triggers: Jay's team gives agents names, email addresses, and Slack accounts, then scopes specific tasks to them.Meet people where they work: A great internal tool nobody opens loses to a mediocre one that lives in Slack.Native beats bolted-on: Lightfield builds call recording into an agentic CRM — raising whether platforms simply absorb point solutions like Gong and Fathom.The 20-year default is up for grabs: AI-native companies are re-evaluating Salesforce and HubSpot, and $10–30M niche software businesses look far more buildable.Adoption is change management: Licenses aren't a strategy. Training, champions, and executive time are. CHAPTERS 00:00 - Six-and-a-half-minute podcast intros, and why we don't do them01:26 - Building a CS platform at Junction, and what early users saw in it02:50 - Running Claude and Codex against each other for checks and balances05:21 - One prompt, seven screens: the project management mockup10:23 - Dreamforce, and Jay's case that you're building a UI13:50 - Permissions, field-level controls, and moving slower on purpose16:39 - Working where your team works: the Slack problem17:36 - Agents as employees: names, email addresses, Slack accounts19:27 - Muse, personal agents, and Lightfield's agentic CRM22:16 - Do platforms eat point solutions like Gong and Fathom?24:02 - Would a new company pick Salesforce or HubSpot today?27:46 - Compound startups and the case for $10–30M software businesses30:50 - Bending Spoons, Airtable, and the no-titles debate38:41 - Superhuman acquires Fathom, and a very confusing product strategy41:33 - A bank CTO's pragmatic AI adoption playbook47:11 - Change management, prerequisites, and what most companies skip About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

For thirty years we bought software off the shelf and reshaped our processes to fit it. Jay and Jeff argue that era is ending: at Junction, a salesperson and an ops leader each shipped their own internal pricing app, and Shopify's River agent now authors one in eight pull requests merged into the main monorepo. This episode is about what happens when building beats buying — and where those agents should actually live. KEY TAKEAWAYS Skip the spreadsheet: The old path was spreadsheet, no-code, point solution, platform. Now you build the personal point solution first.Configurability becomes table stakes: If your platform can't be customized, customers will build around you or find a vendor who lets them.Business people are the builders: Junction's lab pricing tool came from a salesperson, the test kit tool from an ops leader — not engineering.Back-burner problems finally get built: Pricing lookups were always real friction, never big enough for an engineering sprint. Now they take a weekend.Go to fewer places, not more: Agents should meet your team in the inbox or Slack, not add another app to the switching tax.Systems of record go headless: Jeff's internal wiki lives in a GitHub repo as markdown, built for agents to read first and humans second.One meta-agent, many specialists: A central agent that delegates beats one agent holding every context — and it can query a teammate's agent for what it doesn't know.Modeling behavior drives adoption: Shopify's CEO works with River in an open Slack channel. 5,983 employees followed across 4,450 channels.The middle is thinning: Everybody's a builder. CS coverage moves from 50 named accounts per CSM toward 150. CHAPTERS 00:00 - Intro00:45 - An NFL survivor pool tool and the Benedict Evans thread02:08 - Spreadsheet, no-code, point solution, platform04:54 - Do platforms need to open up customization?07:16 - Junction's lab pricing app, built by a salesperson09:59 - The test kit pricing tool12:16 - Consolidating point solutions into one internal platform12:41 - Creativity is the limitation, not the technology14:51 - Instinct and Town: agents in your inbox17:16 - Building a wiki for agents first19:18 - One agent or many? The meta-agent pattern26:13 - Shopify's River: an AI teammate in Slack29:13 - Why CEO modeling drives adoption31:47 - Tactical vs. strategic work33:01 - Middle managers and bigger books of business About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jay walks through the customer segmentation workshop he ran this week — a deliberately simple grid of lifecycle stage, engagement model, and health status that gets leaders to say what should happen in the business before anyone argues about tools. Plus: what "harness lock-in" means for your AI stack, and why the customer quote you read never lands like the one you watch. KEY TAKEAWAYS Segment before you strategize: Product attachment, lifecycle stage, engagement model, health status — four inputs, and every row of the grid is a real situation to solve.Managed vs. scaled: Either an account has a named human or it doesn't. Pick the threshold, then design both sides.Red/yellow/green, not a health score: Sponsor, usage, sentiment, billing. One turns yellow, the account turns yellow — and you know what to go fix.Business requirements before playbooks: Ask leaders what should happen in each segment, not which system does it. Tools execute a plan; they don't replace one.Why CS platform deployments fail: The grid was never filled out. Teams buy a product hoping to get a strategy.Strategy is putting things in buckets: Rumelt's diagnosis, guiding policy, coherent action — one segment at a time. "Not strategic" usually means working hard without buckets.Bumpers, not scripts: A playbook keeps people in the lane. Word-for-word scripts belong in a contact center, not on the front line.Simple travels: The bigger the team, the worse the game of telephone. Simple to communicate is what actually spreads.Make the customer voice watchable: Jeff swapped text quotes in Slack for links to the recording — and the whole business started listening.Get executives back in the room: Exec sponsors, ride-alongs, 50 calls in 50 days. CFOs are the best execs to put on a customer call. CHAPTERS 00:00 - Apex habits and why consistency compounds03:23 - Jeff cheats on Claude and tries Codex06:04 - Model vs. harness: the real lock-in problem08:02 - Why enterprises can't move at personal-project speed10:53 - 87 out of 100 people have never touched AI11:44 - The skills AI doesn't replace: trust, transparency, relationships12:39 - Turning customer quotes into watchable clips14:29 - Ride-alongs, exec sponsors, and 50 calls in 50 days18:51 - Inside the segmentation workshop21:07 - Engagement model and the red/yellow/green grid23:33 - Business requirements before playbooks27:35 - Bumpers on a bowling lane, not word-for-word scripts33:02 - Segmentation as a microcosm of strategy37:25 - Why CS platform deployments fail About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jeff Breunsbach shipped three things in one week—a community platform, a Claude-built CSM training academy, and an agent-powered internal wiki. He and Jay Nathan unpack the Karpathy-inspired philosophy of designing knowledge systems for agents instead of humans, why the engineering bottleneck has moved to customer success, and how to map product usage to P&L outcomes a CFO can see. KEY TAKEAWAYS Design for agents, not humans: Stop forcing your knowledge into Notion or databases. Build in markdown files on GitHub—agents work natively on file structures, and your team gets a custom UI on top.The self-updating wiki: Three agents (writer, reviewer, verifier) continuously maintain your knowledge base by listening to Slack, support tickets, and email—so humans stop doing the updating.Build a learning loop: Jay logs what he edits vs. what the AI wrote, and the agent learns from the diff. That's the difference between a task tool and one that gets continuously smarter.One wiki powers everything: A live internal wiki can drive your CSM academy, customer-facing docs, and onboarding—without a dedicated writer for each output.The bottleneck has moved: AI eliminated engineering as the constraint. Now go-to-market teams and customers can't keep up with what's shipping. That's the new problem to solve.Feature velocity ≠ value: Shipping more faster can increase churn if customers can't absorb it and build an internal ROI story.Map usage to the P&L: Jay's framework—leading indicator → lagging indicator → KPI—connects product usage to financial outcomes a CFO can see.Pricing model literacy: The shift from seat-based to consumption or outcome-based pricing has real gross profit and AI inference cost implications CS leaders must understand. CHAPTERS 00:00 - Welcome & Jay's CCO Summit trip to Boston01:30 - Why in-person still matters for team chemistry03:00 - Launching Uncommon community + vector databases05:30 - The Claude-built CSM training academy08:00 - Agent learning loops: the lessons-learned file09:30 - The Karpathy-inspired agent-first internal wiki13:00 - Designing for agents, not humans15:30 - The autonomous CRM vision17:00 - One wiki powering the whole org downstream20:00 - Jobs aren't disappearing—they're shifting21:00 - P&L literacy gap at the CCO Summit24:00 - The new bottleneck: go-to-market teams26:00 - Feature velocity vs. the 1-degree problem29:00 - Teaser: consumption vs. outcome-based pricing32:00 - Jay's leading → lagging → KPI framework About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Forward deployed engineers are the new hotness—but Palantir's model was built for eight-figure deals with zero competition. Jay and Jeff break down what your team actually needs instead, from onboarding agents that cut a week off time-to-value to cataloging work your CS team shouldn't be doing. KEY TAKEAWAYS Think critically before copying Palantir: Their FDEs are deep AI engineers on eight-figure deals with no real competition—not relabeled CSMs or sales engineers.Match the motion to the deal size: Eight-figure deals can afford dedicated FDEs. Everyone else should use engineering capacity to build tooling that scales.Deploy engineers against onboarding first: Jeff's solutions engineer sits in CS, aiming to cut five days off onboarding—and reach revenue faster.Optimize for time to first result: Architect onboarding around the first core outcome instead of throwing the whole platform at customers.Async agents can replace the validation call: A Slack agent validates contract and configuration details before kickoff, so the first meeting starts from momentum.Map the process before adding AI: A Google Sheet and Figma board came first. Once mapped, it's obvious where AI fits.The job today isn't the job in twelve months: Both hosts now say this in interviews—hire people who want to build the plane while flying it.Give the team an outlet to flag work that shouldn't exist: Turn "I shouldn't be doing this" into a cataloged, prioritizable ticket—then solve one thing per quarter. CHAPTERS 00:00 - Charleston heat and offsite season01:09 - The forward deployed engineer hype, revisited02:08 - Why Palantir's FDE model doesn't map to your business05:20 - Getting ingrained in the customer's business07:12 - Cutting a week off onboarding with a deployed solutions engineer12:39 - Time to first result over throwing everything at customers13:34 - The onboarding agent and AI-first delivery at Balboa16:17 - Google Sheets, Figma boards, and mapping before automating20:00 - Blending AI into the service blueprint21:10 - "The job today isn't the job in twelve months"25:27 - Vision setting, rally cries, and the Kennedy moon speech29:00 - The Wayne McCulloch open-document vision exercise30:06 - Cataloging work your team shouldn't be doing36:56 - Working Genius, activators, and galvanizers38:12 - Community, Vistage, and relaunching Uncommon About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jay Nathan and Jeff Breunsbach break down an exercise Jeff ran with his CS team offsite—sorting every activity into keep, start, automate, delegate, or cut. Plus reverse roadmap reviews, cutting 50% of check-in calls, and the self-hosted agent platform Jeff's building with Buzz. KEY TAKEAWAYS Five Buckets: Jeff's team sorted last week's activities into keep/start/automate/delegate/cut. Only a small share landed in "keep it"—50-60% moved elsewhere.The Defensiveness Trap: CS teams over-claim "keep it" because giving something up feels like losing relevance. Anchoring to revenue cuts through that.Reverse Roadmap Reviews: Ask customers to share their roadmap instead of presenting yours. It surfaces product gaps and becomes a repeatable leading indicator.Cut the Check-In Call: Jeff's team is targeting a 50% cut of recurring check-ins that drifted into habit. Fix: give every call a purpose, start date, and end date.Field-Level Understanding: Palantir's "agent camp" echoes an old FLU playbook from Jay's consulting days—both build pre-sale conviction by mapping use cases with buyers.Pendulum Swings Back to Deterministic: Agent platforms are exciting, but many workflows need to run the same way every time—the win is blending agent judgment with deterministic code.Forecast Risk in Automation: An agent auto-moving a deal stage introduces risk into something reps must stand behind. Some steps still need a human check.Buzz as an Agent Harness: Jeff's self-hosting Block's open-source Buzz, where every channel is an agent he and Jay shape together—podcast producer, newsletter agent, and a content manager orchestrating both. ABOUT YOUR HOSTS Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.io Jeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io CHAPTERS [00:01] - Intro and the CS team offsite[00:49] - The keep/start/automate/delegate/cut exercise[03:20] - Anchoring the exercise to revenue[04:41] - The change management payoff for the team[06:34] - Reverse roadmap reviews as a leading indicator[09:58] - The goal: cut 50% of check-in calls[12:37] - Transition calls and giving check-ins a purpose[14:57] - FLU and Palantir's agent camp model[18:31] - Why AI adoption stalls at the enterprise level[19:27] - Single-player vs. multiplayer agent platforms[22:35] - The pendulum swings back to deterministic workflows[25:57] - Forecast risk when agents move deal stages[27:11] - The missing embedded product manager[30:20] - Buzz: a self-hosted agent messaging harness[33:51] - Standing up a podcast producer and content manager agent[36:32] - Turning call transcripts into a customer quotes channel About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it.

Jeff and Jay get honest about where the Chief Customer Officer podcast lost its spark—and what reignited it: a seven-capability framework for post-sale teams that cuts through the roles-and-titles noise. Support, onboarding, adoption, engagement, feedback, renewal, expansion. The fundamentals haven't changed. But how you build for them—and where AI fits in—has everything to do with what kind of CS org you'll have in two years. KEY TAKEAWAYS Capabilities beat titles: Whether you call them CSMs, TAMs, or revenue architects, what matters is which capability is being delivered—not what the role is named.AI amplifies, it doesn't shortcut: Jeff's team built an AI triage agent for support tickets using N8N and Claude—but only after mapping the underlying process first.CS is a cross-functional sport: Feedback loops involve product. Renewals involve finance. Onboarding involves engineering. The seven-capability frame makes it easier to pull other teams in.Customer journey ≠ your operational blueprint: Jay's key distinction: your internal capabilities are levers you control; the customer's maturity journey is theirs to own.Roles aren't disappearing: Gong now calls theirs "revenue architects." But support, onboarding, and expansion still need owners—the work hasn't gone away.Frank Slootman's warning: At Snowflake, he refused to name any team "customer success"—so every team stays accountable. It's a brilliant structural insight.CCO is looking for its next leader: Jeff and Jay want a young, energetic operator to help run this media company. Reach out if that's you. CHAPTERS 00:00 - What is this podcast even called?01:08 - Why the podcast lost its spark03:06 - Rebuilding for CS leaders in the AI era08:20 - The 7 core capabilities framework14:39 - Capabilities vs. titles: the real shift18:20 - Comparing to Wayne McCulloch's Seven Pillars21:18 - Customer journey vs. operational blueprint25:04 - Feedback loops and cross-functional ownership27:14 - Frank Slootman on CS accountability30:43 - How Gong reinvented their post-sale team33:29 - Guests, consistency, and podcast format35:23 - What's next: newsletter, community, and AI About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jeff is back from paternity leave and building a company brain. Jay challenges him to think bigger: before you can run agents, you need a context layer. They dig into data architecture, call transcript intelligence, and what it actually takes to build enterprise-grade AI for customer success. KEY TAKEAWAYS Source data stays in source systems: Pull via API from your existing tools rather than duplicating data. The real question is whether to write enrichment back to the CRM or store it natively.Context layer first, agents second: Every account needs a living record — call summaries, sentiment, history — before an agent can act intelligently on its behalf.Company brain = ontology + continuous enrichment: Map your key entities (customers, contacts, contracts, products) and keep populating them from calls, emails, and Slack.Agents vs. deterministic workflows: Renewals have fixed steps. Inject AI where judgment matters — like building a personalized proposal using full account context.Call transcripts are gold: Extract from Fathom, store in Postgres, add a sentiment + sensitivity classifier, expose via MCP — then query your entire call history from Claude.Cowork is MVP, not enterprise: Jeff's scheduled Fathom summaries are a perfect first step, but they stop when his laptop closes. Enterprise agents need to run independently.Harnesses vs. models: Claude and ChatGPT are harnesses above the intelligence layer. What teams actually need is an enterprise harness that shares context company-wide.LLMs need precision, not volume: Models are "dumb" because they know everything. Give them exactly the context they need — and nothing more. CHAPTERS 00:00 - Welcome & intro01:44 - Jeff's "Steve": building a custom CS platform04:23 - Should you write data back to the CRM?07:21 - Context layer vs. application layer10:44 - Building a company brain & ontology13:16 - Agents vs. deterministic workflows16:40 - Renewals as the perfect AI use case20:36 - MVP first, long-term vision22:30 - LLMs need precision context25:15 - Open source AI & why it matters26:35 - The Fathom + Postgres + MCP stack33:16 - Jeff's MVP: scheduled Fathom summaries in Cowork35:17 - From prototype to enterprise agents38:47 - What is a model harness?41:31 - Enterprise context & shared team knowledge45:19 - Wrap up About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jay and Jeff dig into two very different but connected stories: Jeff's homegrown AI "chief operating officer" for his household, and the $10B forward-deployed engineer boom reshaping enterprise services. Along the way: why task automation isn't the same as agents, and the skill that will matter most in the age of AI. KEY TAKEAWAYS Personal agents teach real agent behavior: Jeff's household agent, Mr. Baxter, learns from ongoing texts instead of needing reprogramming — a preview of how enterprise agents should work.Task automation isn't agents: Jay's take: most companies are building automation, not agents. Real agents remember, evolve, and run without babysitting.Enterprises are building personal agents too: A $10B industrial services company Jay spoke with made personal agents for employees a pillar of its AI strategy.Lean into human relationships: Automate what doesn't need a human touch, then reinvest the saved time into surprising and delighting customers.Be maniacal about killing process: Borrowing from Elon Musk, map every step and ruthlessly ask if it should exist — and if so, human, agent, or gone.FDEs are the new consulting: Unlike consultants who parachute in and hand off a deck, forward-deployed engineers stay and build the agents that actually run the business.Pair domain experts with engineers: The real unlock is combining business context with technical build skill — or training subject matter experts directly on AI once the architecture exists.Intelligence sovereignty is the next worry: As IP questions grow, expect more interest in post-trained open-source models for cost and control. CHAPTERS 00:00 - Catching up: inbox zero and using Claude to triage email02:46 - Meet Mr. Baxter: building an AI COO for the household07:17 - Why personal agents preview enterprise AI strategy14:45 - Three priorities: human relationships, killing process, more joy22:38 - The $10B forward-deployed engineer boom30:03 - Pairing business operators with FDEs to close the last mile34:23 - Early adopters, intelligence sovereignty, and open source catching up41:10 - Wrap-up and a tease for next week's Starbucks story About the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io

Jay and Jeff go deep on what's actually blocking enterprise AI adoption—and it's not the technology. They cover building a shared organizational brain from call transcripts, why Zapier banned Slack DMs, the $7.5B bet on forward-deployed engineers, and personal AI coaches that are already changing daily habits. KEY TAKEAWAYS Enterprise AI Blockers Are Legal and Cost, Not Tech: The technology is far ahead of adoption. Legal, IP, and data security fears—not capability—are slowing large organizations down.Single-Player AI Is the Real Bottleneck: Most teams are getting individual value but failing to share it. The shift from personal tools to team-based AI infrastructure is where the real gains live.Build a Shared Brain from Call Transcripts: Jay's "Balboa Brain" extracts an ontology from thousands of call transcripts—people, companies, engagements, best practices—and agents update it nightly.Public Channels Feed Better Agents: Zapier's Wade Foster raised internal public Slack usage from 33% to 46% via a transparency leaderboard. Private DMs destroy the context AI needs to do its job.Forward Deployed Engineers Are the New Gold: Amazon, OpenAI, and Anthropic have collectively invested $7.5B in FDE-style organizations—because the gap between AI capability and enterprise readiness is enormous.Amazon's 45-45-45 Methodology: 45 minutes to define the problem, 45 hours to build and validate, 45 days to productionalize. Fast but grounded.Systems Thinkers Win: James Clear: "You don't rise to the level of your goals, you fall to the level of your systems." This applies to AI adoption as much as any habit.Personal AI Agents Are Already Working: Jay's NanoClaw fitness coach "Jack" is tracking nutrition and workouts with measurable results after just one week. CHAPTERS 00:00 - Intro & Hot Summer in Charleston01:30 - Enterprise AI Adoption Barriers04:45 - Single-Player vs. Multiplayer AI07:15 - Zapier Bans DMs: Building AI Context in Slack11:30 - Building the Balboa Brain19:00 - From Files to a Vectorized Database23:00 - What Are Agents, Really?26:00 - Forward Deployed Engineers: $7.5B Bet30:00 - Amazon's 45-45-45 Methodology37:00 - Less Software, Better Outcomes41:00 - DesignJoy and the One-Person FDE Model44:00 - James Clear's Systems Quote45:30 - Teaching Non-Technical People to Use AI47:00 - Personal AI Fitness Coaches & NanoClaw50:30 - Cal AI's $30M Exit and the HackAbout the Show: Chief Customer Officer Podcast is a show about real strategies for customer-led growth in the AI era—from leaders actually executing, not just talking about it. Your Hosts: Jay Nathan – CEO of Balboa Solutions and Co-Founder of ChiefCustomerOfficer.ioJeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io