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 money
• 01:29 - Good Strategy, Bad Strategy primer
• 02:24 - Four signs of bad strategy
• 03:47 - The kernel of good strategy
• 05:19 - Example: fixing year-one churn
• 08:51 - Patterns from 200+ Balboa clients
• 11:57 - The Goal and finding your Herbie
• 15:59 - AI moved the constraint to adoption
• 17:03 - Defining product success
• 19:02 - The product success loop
• 24:40 - Why departments are the problem
• 25:20 - The Insights to Impact method
• 26:45 - Step 1: Segmentation
• 30:58 - Step 2: Prioritization
• 33:59 - Step 3: Strategy definition
• 35:57 - Step 4: The measurement ladder
• 38:35 - Step 5: Deploy, measure, iterate
• 40:16 - Beyond product analytics
• 42:19 - This week's challenge

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.io
• Jeff 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 offsite
• 01:45 - A half day on "who are our customers"
• 04:09 - Operationalizing customer insights
• 05:10 - Call-to-ticket workflows and all-hands rituals
• 07:32 - The customer quotes channel and finite attention
• 10:10 - Push vs. pull and shadowing rotations
• 12:07 - AI is just technology: the factory robot lesson
• 13:38 - Junction's company-wide support rotation
• 15:05 - Leadership is the differentiator
• 17:49 - The 78% stat and agent-sent job applications
• 20:32 - Building a segmentation model in minutes
• 22:01 - The future of customer success
• 23:24 - A tool for CSM-to-CSM account transitions
• 25:37 - Salesforce acquires Listen Labs
• 27:50 - The harness race and the work/home AI divide
• 30:14 - What personal AI assistants actually cost
• 32:15 - Would you talk to an AI moderator?
• 33:44 - Agents as necessary friction
• 34:53 - Agent-to-agent work and enterprise AI deployment
• 37:04 - Wrap-up and The Goal

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.io
• Jeff 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 moment
• 06:08 - AppsFlyer's strategic investment from Meta, Google, Moloco, and Unity
• 07:04 - From CCO to Chief AI Officer
• 09:45 - Why every leader needs to be a builder
• 10:13 - Assistants vs. automation and the new adoption curve
• 13:24 - Multiplayer AI for teams
• 15:14 - Inside AppsFlyer's internal AI stack
• 19:56 - Splitting time between CAIO and CCO
• 22:53 - The 24/7 mindset and human-in-the-loop evals
• 25:44 - The AI budget equation
• 27:01 - Teaching people to think like designers
• 29:57 - Classifier models and go-to-market use cases
• 34:59 - Build vs. buy
• 39:08 - Salesforce, Anthropic, and the GRR play
• 44:33 - The value era for customer success
• 46:07 - The sewing machine story
• 48:07 - FDE is net dollar retention
• 52:25 - The AI leverage scorecard
• 54:52 - Goodhart's Law and 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.io
• Jeff 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 school
• 01:38 - Only 3% of consumers pay for AI
• 04:19 - Meta Muse negotiates on Facebook Marketplace
• 06:30 - Harvey's shift from SaaS to AI implementation
• 10:59 - Why agent infrastructure should be centralized
• 13:19 - You're never that far behind
• 14:11 - Selling agentic work without the plumbing
• 14:53 - Tool FOMO: Instinct, Town and Muse
• 17:27 - A platform war, not an app war
• 20:01 - Jay goes back to writing on his own
• 23:28 - Two rules for writing with LLMs
• 25:38 - Readers abandon AI-written content
• 28:03 - AI for research, not writing
• 29:48 - AI slop in client presentations
• 31:19 - Claude in Slack and trusting AI messages
• 32:18 - Branded two-pagers in seven minutes

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.io
• Jeff 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 them
• 01:26 - Building a CS platform at Junction, and what early users saw in it
• 02:50 - Running Claude and Codex against each other for checks and balances
• 05:21 - One prompt, seven screens: the project management mockup
• 10:23 - Dreamforce, and Jay's case that you're building a UI
• 13:50 - Permissions, field-level controls, and moving slower on purpose
• 16:39 - Working where your team works: the Slack problem
• 17:36 - Agents as employees: names, email addresses, Slack accounts
• 19:27 - Muse, personal agents, and Lightfield's agentic CRM
• 22:16 - 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 businesses
• 30:50 - Bending Spoons, Airtable, and the no-titles debate
• 38:41 - Superhuman acquires Fathom, and a very confusing product strategy
• 41:33 - A bank CTO's pragmatic AI adoption playbook
• 47:11 - 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.io
• Jeff 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 - Intro
• 00:45 - An NFL survivor pool tool and the Benedict Evans thread
• 02:08 - Spreadsheet, no-code, point solution, platform
• 04:54 - Do platforms need to open up customization?
• 07:16 - Junction's lab pricing app, built by a salesperson
• 09:59 - The test kit pricing tool
• 12:16 - Consolidating point solutions into one internal platform
• 12:41 - Creativity is the limitation, not the technology
• 14:51 - Instinct and Town: agents in your inbox
• 17:16 - Building a wiki for agents first
• 19:18 - One agent or many? The meta-agent pattern
• 26:13 - Shopify's River: an AI teammate in Slack
• 29:13 - Why CEO modeling drives adoption
• 31:47 - Tactical vs. strategic work
• 33:01 - 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.io
• Jeff 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 compounds
• 03:23 - Jeff cheats on Claude and tries Codex
• 06:04 - Model vs. harness: the real lock-in problem
• 08:02 - Why enterprises can't move at personal-project speed
• 10:53 - 87 out of 100 people have never touched AI
• 11:44 - The skills AI doesn't replace: trust, transparency, relationships
• 12:39 - Turning customer quotes into watchable clips
• 14:29 - Ride-alongs, exec sponsors, and 50 calls in 50 days
• 18:51 - Inside the segmentation workshop
• 21:07 - Engagement model and the red/yellow/green grid
• 23:33 - Business requirements before playbooks
• 27:35 - Bumpers on a bowling lane, not word-for-word scripts
• 33:02 - Segmentation as a microcosm of strategy
• 37:25 - 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.io
• Jeff 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 Boston
• 01:30 - Why in-person still matters for team chemistry
• 03:00 - Launching Uncommon community + vector databases
• 05:30 - The Claude-built CSM training academy
• 08:00 - Agent learning loops: the lessons-learned file
• 09:30 - The Karpathy-inspired agent-first internal wiki
• 13:00 - Designing for agents, not humans
• 15:30 - The autonomous CRM vision
• 17:00 - One wiki powering the whole org downstream
• 20:00 - Jobs aren't disappearing—they're shifting
• 21:00 - P&L literacy gap at the CCO Summit
• 24:00 - The new bottleneck: go-to-market teams
• 26:00 - Feature velocity vs. the 1-degree problem
• 29:00 - Teaser: consumption vs. outcome-based pricing
• 32:00 - 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.io
• Jeff Breunsbach – Head of Customer Success at Junction and Co-Founder of ChiefCustomerOfficer.io