Maven

New quarter, new Lenny's List on Maven I'm seeing a shift from people wanting to learn how to use AI to write PRDs and brainstorm ideas, to answering more technical questions like: How do I build reliable agentic systems? What do I need to know about evals? How do I use AI even more in my product and design workflows? So I updated Lenny's List to reflect this evolution by adding a few more technical courses: - "Prototype to Production: The AI PM Playbook" with Aman Khan - "Agentic AI System Design for PMs" with Gabriela de Queiroz and Hamza Farooq - "Systematically Improving RAG Applications" with Jason Liu - "Level Up with Figma" with Joey Banks A few reasons why I continue to recommend Maven for learning: 1. Real practitioners - Every instructor has shipped many real products at scale. 2. Project-based - Each course makes you ship something. 3. Fresh - With the pace of AI innovation, live courses are the most up-to-date way to learn. Check out all of the courses at maven.com/lenny and use code LENNYSLIST to get a whopping 15% off any of the courses.

People assume more rules slow you down. In design, the opposite is true. According to Maven’s lead designer, to truly adopt AI, you need to create a ton of structure and rules. Yuan W. was previously on the design team at AirBnB, now she’s leading design at Maven and thinks most designers are using AI wrong. They treat it like a magic wand — type in a prompt, hope something good comes out, then fix everything AI got wrong. That workflow is slower than doing it yourself. The designers who are actually winning with AI took a completely different approach: they rebuilt their workflow first. AI needs structure to be useful. When your design system defines every component, style, and pattern, AI can generate assets that fit your brand instead of guessing. At Maven, Yuan’s team is connecting this end-to-end:  → using Figma MCP + Cursor to auto-generate front-end Storybook components directly from Figma designs  → setting up internal tools (Lovable & ComfyUI) to batch-generate branded visuals that stay consistent with our design language The result is designers spend less time on execution and more time on strategy, storytelling, and stakeholder influence. AI amplifies their output without taking away creative control. The designers who figure this out early will define the next era of product development. If you want to learn from designers on the cutting edge, we’ve partnered with Dive Club on a free series. Here’s the line-up: • How AI is changing Design Workflows with Michael Riddering (Host of Dive Club podcast), Henry Modisett (VP of Design at Perplexity), Pranathi Peri (Design at Vercel) and Nick Pattison (Founder at Primary) • Design Patterns For AI Interfaces with Vitaly Friedman (Smashing Magazine co-founder) • From Designer to Design Architect with MagicPath with Pietro Schirano (Founder of MagicPath) • Vibe Designing with AI with Xinran Ma (Founder of Design with AI) • Supercharge creativity with AI workflows in FLORA with Weber W. (Founder of FLORA) • Doing More With Your Design System in Figma with TJ Pitre (Founder at Southleft) and Joey Banks (Founder at Baseline Design) • AI-Driven Onboarding Workflows That 2x Activation with Kate Syuma (Founder at Growthmates) Check it out on Maven (it’s free): https://lnkd.in/eCwuwRNR

I’m celebrating 5 years at Maven and my 15th year as a founder. Here’s what I’m doing differently… 1/ Think extremely long term. I’ve seen way too many companies take 10-15 years to IPO or exit. This has completely shaped my sense of time, and it is probably why Maven still has nearly half of our Series A in the bank. We knew it was going to take time and planned accordingly. 2/ People, people, people. Companies are built with thousands of individuals: Maven has 21 employees, hundreds of instructors and investors, and hundreds of thousands of users. Treating each person well has contributed to incredible loyalty, even when it hurts Maven in the short run. When an employee or instructor leaves Maven, we try to keep it on extremely good terms which has led to many “return visits” where the person either comes back or delivers extraordinary value via referrals or references. 3/ Focus. Maven is 5 years old and has had the same rough vision the entire time. The biggest decision, however, has been NOT to enter B2B. While all of our competitors were stuck in 1-2 year buying cycles, we focused on the B2C market and built a product people wanted. This puts us in a much better position to add B2B when the time comes. 4/ Build in public. It works. I really didn’t believe it because there are some people who do it in a really cheesy way. But publicly sharing constantly has been a huge benefit to our ability to recruit instructors, employees, and users. This is the era of movement-driven companies and I expect Maven will be one of them. 5/ Stay lean. Maven is just 21 employees and has stayed roughly the same headcount as we’ve grown about 6-10x. That’s the power of leverage. You can often handle more customers, more users, and more product surface area with roughly the same number of people! Eventually though, you gotta grow the team and we’re in that stage now. We’re hiring in marketing, product, engineering, and instructor partnerships. Check out our open roles at maven.com/careers

Want to move from software engineer to AI engineer? Here are 5 skills you’ll want to master (and free lessons so you can dive deeper). 1. Context / Prompt Engineering How you frame prompts, manage context windows, and design agent memory or chains directly impacts performance. These are core levers for making LLMs more reliable. 🔗 Free lesson: https://lnkd.in/edFrjrsj 2. Retrieval, Search & Vector / Embedding Systems AI systems rely on retrieval for grounding and memory. Understanding embeddings, similarity search, and indexing is key to powering RAG and semantic search at scale. 🔗 Free lesson: https://lnkd.in/e94zD9hg 3. Agent / AI App Construction Real AI apps are built by composing agents, chaining tasks, and integrating tools and retrievers. This is the step from toy prototypes to functional AI systems. 🔗 Free lesson: https://lnkd.in/ep5kbu-Y 4. Evaluation & Observability Agents can drift, hallucinate, or fail silently. You’ll want to embed output checks, trace logs, metrics, and telemetry so you can catch issues early. Use human + LLM evaluation workflows, and equip your code with tools to trace each agent action and spot where things go wrong. 🔗 Free lesson: https://lnkd.in/eNFn-6_R 5. Scaling, Agent Design Patterns & Multi-Agent Architectures As systems grow, scaling requires design patterns: multi-agent coordination, memory hierarchies, and failure detection. These let you build more robust, distributed AI systems. 🔗 Free lesson: https://lnkd.in/evJH-XYr Want to see all the lessons and sign up for free? Check out the full Building Production AI Systems Lightning Lesson Series on Maven: https://lnkd.in/eCKGwRYF

Super pumped to be showing off some Clay x Lovable use cases during my Maven lightning lesson next Tuesday! Planning to cover how to use Lovable as a frontend to your Clay workflows in order to make them more accessible for your entire team, not just GTM engineers. We already have 400+ people signed up, join them using this link -> https://lnkd.in/ggw37dNz

How do you integrate AI into your daily workflow?

The “GTM Engineer” role didn’t exist 18 months ago. Now it might be the best career pivot you can make in tech. Companies like OpenAI and Ramp are paying $250k+ for GTM Engineers. Instead of throwing more reps at the problem, GTM Engineers design the systems that power growth by engineering sustainable, scalable growth engines. Here are some free resources to learn about the key skills for this AI-powered profession: 1. User Intent https://lnkd.in/eN-hbbFi How to understand and act on intent data, spot signals that actually matter, and prioritize the right prospects. Taught by Noah Adelstein (International Growth at Rippling). 2. Experimentation https://lnkd.in/eWAacCnz How to build GTM experimentation systems, run tests that reveal what drives conversion, and scale experiments into repeatable playbooks. Taught by Yash Tekriwal 🤔 (Head of Education at Clay). 3. Vibe coding https://lnkd.in/efGRJNDG How to identify vibe-coding opportunities for GTM teams, automate workflows with tools like Clay, N8N, and Lovable, and create custom “delight moments” in your sales process. Taught by Patrick Spychalski (Co-founder at The Kiln, a Clay Agency). 4. Data architecture https://lnkd.in/e83QuRuv How to design clean data flows, build enrichment layers to keep signals fresh, and power downstream GTM workflows. Taught by Manny Adelstein (GTM Engineering at Clay). 5. Target Account Engine https://lnkd.in/eGhGGf7r How to find your best-fit accounts, track the buying signals that actually matter, and keep your target lists clean and effective. Taught by Emre Kavaloglu (Co-founder at Waterfall.io & TAMradar). Maven has partnered with Clay to deliver a free 12 lesson series on GTM Engineering. Check it out here: https://lnkd.in/e-mvi9VD

I'm moderating a session hosted on Maven.com with Davide Grieco (Head of growth at Clay), Ilija Stojkovski (CRO @ HeyReach) & Alex Fine🌲 (Co-founder @ Understory) on hiring top 1% GTM Engineers! We’ll talk about what to look for in GTM Engineers, where to find top candidates, and how to stand out if you’re applying for roles. Link to register in comments, and if you have questions you want us to answer, drop them in the comments!

The GTM Engineer role didn't exist 18 months ago. Now every growth team from OpenAI, Ramp to Webflow is scrambling to hire for it. GTM engineers are part marketer, part engineer, and entirely essential to modern growth teams. They build the technical infrastructure that powers acquisition - automated lead scoring, dynamic pricing systems, and hyper-personalized scaled outbound. If you're leading growth, marketing, or sales, you're already competing against GTME teams. They're automating what you're doing manually. They're scaling what you can't scale. The gap widens every quarter you wait to understand how these roles work and how to leverage them in your organization. Meanwhile, the people actually building these functions are only getting better. That knowledge is incredibly valuable, but it only exists in their heads. That’s why we’ve partnered with Clay to launch a free series to define the GTM Engineer role and showcase what being in the top 1% looks like. Here’s the line-up: • Seeking GTM Alpha with Yash Tekriwal (1st GTME at Clay) • Capturing Intent Signals with Noah Adelstein (Growth at Rippling) • Adopting AI with a Hackathon with Emily Kramer (MKT1 / Former Head of Marketing at Asana) • Build an AI-SDR with Everett Berry (Head of GTM Eng at Clay) • Customer Empathy for GTM Wins with Rachel Gurman & Gabrielle Borenstein, Ph.D. (CX at Clay) Check it out on Maven (it’s free): bit.ly/mavenxclay

Check out this episode from our very own Michael Riddering and Dan Winer - how to go from pixel pusher to strategic partner and lead in the AI era 👇