Aakash Gupta

Complete Course: AI Agent Products (with Warp.dev CEO Zach Lloyd)

Zach Lloyd, CEO of Warp ($1M ARR growth every 10 days), reveals how to build AI agents that developers actually pay for. He breaks down the exact frameworks for profitable agent development, and shares his controversial take on why most AI products are built the wrong way. ----- Full Writeup: https://www.news.aakashg.com/p/zach-lloyd-podcast Transcript: https://www.aakashg.com/the-ai-pms-guide-to-building-profitable-agents/ ---- Timestamps: 00:00 Intro 02:00 How big is Warp 08:27 How he made Warp 14:53 Ads 15:42 Why Most AI Agents Fail at Launch 16:37: UX process on an AI agent 19:35 Live Demo: Building AI Agent with Warp 29:32 Ads 31:05 Systems That Drive Adoption 38:25 Workflow to build AI Agents 46:15 How to choose right metrics for your Agent 53:00 How to Actually make Money with AI Agents 59:24 Why Traditional SaaS Pricing Breaks 1:06:00 AI Agents will change the way you work 1:11:25 Outcome-Based Pricing Strategies 1:17:50 Roadmap to Build Ai Agents 1:10:55 Outro ---- Thanks to our sponsors: 1. Vanta: Automate compliance, manage risk, and prove trust - http://vanta.com/aakash 2. Kameleoon: Leading AI experimentation platform - http://www.kameleoon.com/ 3. Amplitude: The market-leader in product analytics - https://amplitude.com/session-replay?utm_campaign=session-replay-launch-2025&utm_source=linkedin&utm_medium=organic-social&utm_content=productgrowthpodcast 4. The AI Evals Course for PMs: Get $1155 off with code ‘ag-evals’ - https://maven.com/parlance-labs/evals?promoCode=ag-evlas ---- Key takeaways: 1. Find Where People Hate Rules: Look for workflows where users write algorithms, formulas, or complex syntax. Zach discovered developers were already telling computers what to do through terminal commands - they just needed to do it in English. 2. Apply the $20 Intern Test: Ask what tasks you'd give a smart college intern. Focus on time-consuming work requiring intelligence. If you wouldn't pay someone $20/hour for it, don't automate it. 3. Check If It Really Hurts: Test against four criteria: frequency (weekly use), expertise barrier (requires learning), Google dependency (users search "how to"), and time cost (saves hours). Most failed AI features only hit one criterion. 4. Make Old Things Smarter: Don't add chat panels. Make existing interfaces understand natural language. Users already express intent through formulas and commands - make those conversational instead of teaching new behaviors. 5. Help When People Get Stuck: Surface agent suggestions during error states, not randomly. When users hit errors, auto-suggest "Let agent fix this" with one-click activation. 6. Start Small, Grow Trust: Begin with simple, safe capabilities and add tools as users get comfortable. Week 1: basic requests. Month 3: complex workflows with approval gates. 7.Don't Let Power Users Bankrupt You: Fixed subscriptions make power users unprofitable. A user with 2,000 monthly interactions costs $80 in API fees while paying $50 subscription. 8. Price Like Cell Phone Plans: Use base subscription plus overages. Give predictable costs for normal usage but protect margins on heavy use. Users understand and prefer this model. 9. Charge for Results, Not Usage: When possible, price based on outcomes like resolved tickets or completed tasks rather than conversations. Aligns your success with customer value creation. 10. Catch the Next Wave: Three phases exist - autocomplete (done), interactive agents (current opportunity), full automation (future). Most industries are still in phase one, creating first-mover advantages. ---- Where to find Zach: LinkedIn: https://www.linkedin.com/in/zachlloyd/ X: https://x.com/zachlloydtweets?lang=en Warp: https://www.warp.dev/ ---- Where to find Aakash: Twitter: twitter.com/aakashg0 LinkedIn: linkedin.com/in/aagupta/ Newsletter: news.aakashg.com #aiagents #productmanagement #artificialintelligence ---- About Product Growth: The world's largest podcast focused solely on product + growth, with over 187K listeners. Hosted by Aakash Gupta, who spent 16 years in PM, rising to VP of product, this 2x/week show covers product and growth topics in depth. Subscribe and turn on notifications to get more videos like this.

AGAakash GuptahostZLZach Lloydguest

Sep 27, 2025·1h 11m·Watch on YouTube ↗

📖 CHAPTERS

1. 1

   Warp’s breakout growth: $1M ARR every 10 days and 700k active developers

   Aakash and Zach open with Warp’s recent growth, including rapid ARR acceleration and a large active developer user base. Zach frames the inflection as a product shift: Warp’s terminal roots became a natural home for agentic workflows.

2. 2

   From terminal reimagining to “agentic dev environment”: how Warp was built

   Zach explains Warp’s origin as a terminal UX rework and why that interface became uniquely suited to agentic work. He describes the June repositioning and how CLI-based agents validated the approach.

3. 3

   Why “agentic AI” is a new product primitive (and why PMs can’t ignore it)

   Zach argues intelligence is now a core building block like databases or APIs. Most software problems can benefit from embedded intelligence, shifting how PMs should think about solution design.

4. 4

   Where agents add real value vs. gimmicks: start with the problem, then insert intelligence

   Zach shares a framework: begin with a meaningful user problem, form hypotheses about where intelligence can improve a workflow, and validate. He contrasts brittle rule-based solutions with LLM-driven intent understanding.

5. 5

   Product iterations with AI: from command translation to chat panel to native agent mode

   Warp tried multiple AI integrations: English-to-command translation, then an in-app chat panel, then a more native approach. The “unlock” was realizing the terminal is already an instruction interface—agents should execute English as commands.

6. 6

   Agent UX principles: avoid “just add chat,” build intent-first interactions in the native UI

   Zach generalizes the UX lesson: chat overlays are thin differentiation; the best agent UX lives inside the app’s core interaction model. He uses spreadsheet examples to show agents should operate where work happens (cells), not in side panels.

7. 7

   Live demo: building a real feature in Warp with an agent (tooltip change end-to-end)

   Zach demonstrates using Warp’s agent to implement a UI tooltip improvement, providing screenshot + file context. The agent explores the repo, edits code (Rust, large codebase), builds the project, and ships a working result with iterative prompting.

8. 8

   Making agents feel personalized: rules, memory, and reducing user repetition

   They discuss how agent products should learn user preferences and avoid repeated instructions. Warp uses “Rules” (persistent context) and explores system behaviors like suggested rules and reusable prompts to improve reliability and stickiness.

9. 9

   Dogfooding and adoption systems: the “coding mandate,” Slack feedback loops, and showcase culture

   Zach outlines how Warp uses Warp internally: engineers start tasks with prompts, share failures and successes, and create internal content (e.g., Looms) that also becomes external education/marketing. This creates a tight loop for improving agent UX and reliability.

10. 10

    Competitive landscape: IDE forks vs. pure CLI agents—and Warp’s “third path” differentiation

    Zach compares Warp to Cursor/Windsurf (IDE + side chat) and to pure CLI tools like Claude Code. Warp aims to be a new category that supports prompt-first development while still enabling rich GUI affordances (diffs, navigation, editing) for the new workflow.

11. 11

    Onboarding that actually activates: in-the-moment “next action” suggestions (agentic autocomplete)

    Zach shares what didn’t work (tours, copy tweaks) and what did: catching users at moments of friction (e.g., terminal errors) and suggesting an agent-driven fix. This creates an immediate aha moment and teaches the workflow by solving a real problem.

12. 12

    Measuring agent products: engagement depth, retention, and evals for nondeterministic systems

    Zach explains metrics that predict conversion: long, frequent agent conversations/tasks (depth), along with cohort retention improvements. He then covers why evals are essential for nondeterministic behavior and how Warp uses public and internal benchmarks plus real-world feedback.

13. 13

    Monetization and pricing: why fixed SaaS breaks, hybrid usage models, and outcome-based pricing

    Zach breaks down what it takes to make money with agents: willingness to pay, retention, and especially margins given high inference costs. He argues per-seat SaaS pricing misaligns incentives, explores subscription + overages, and highlights outcome-based pricing where value is measurable (e.g., customer support tickets).

14. 14

    Where agents are headed: three phases (autocomplete → interactive agents → automation) + how PMs can ramp fast

    Zach forecasts a progression from autocomplete to prompt-orchestrated interactive agents, then partial automation of simpler tasks. He closes with actionable advice for PMs: get hands-on with tools, prototype instead of only writing PRDs, and build intuition for what’s feasible.