20Product: Is the Design Phase Dead in a World of AI | Has Claude Code Crushed Anthropic Already | What Roles of a PM Are Less and More Important with AI | How the Best Product Leaders Tell Stories with Noam Lovinsky, CPO @ Superhuman
Episode
45 min
Read time
2 min
Topics
Fundraising & VC, Leadership, Design & UX
AI-Generated Summary
Key Takeaways
- ✓AI Code Generation Impact: Superhuman approaches 50% of net new code written by AI, targeting 90% within twenty four months. Teams don't shrink but build more products with smaller ratios—shifting from five to ten engineers per PM to just two engineers per product team.
- ✓Spec Writing Evolution: Product teams now write specifications for AI agents rather than humans, requiring different structure with explicit context libraries, examples of past successes and failures, and using the coding agent itself to help write specs it will later execute for better compatibility.
- ✓Design Phase Transformation: Design thinking remains essential but shifts form. High fidelity prototypes via vibe coding become standard for stakeholder communication, while early exploration still benefits from whiteboards and Figma. Claude Code dominates as the primary tool, with engineers transitioning from Cursor to terminal based workflows.
- ✓Product Team Acceleration: AI most significantly shrinks the exploration phase and iteration cycles. Teams test multiple solution variations in parallel, dramatically increasing learning velocity. Engineers spend saved time on product strategy, data analysis, and wearing multiple hats rather than purely reducing headcount or costs.
What It Covers
Noam Lovinsky, CPO at Superhuman, discusses how AI transforms product development workflows, team structures, and the role of product managers. He covers vibe coding, Claude Code adoption, spec writing for agents, and predictions for twenty four seven inference.
Key Questions Answered
- •AI Code Generation Impact: Superhuman approaches 50% of net new code written by AI, targeting 90% within twenty four months. Teams don't shrink but build more products with smaller ratios—shifting from five to ten engineers per PM to just two engineers per product team.
- •Spec Writing Evolution: Product teams now write specifications for AI agents rather than humans, requiring different structure with explicit context libraries, examples of past successes and failures, and using the coding agent itself to help write specs it will later execute for better compatibility.
- •Design Phase Transformation: Design thinking remains essential but shifts form. High fidelity prototypes via vibe coding become standard for stakeholder communication, while early exploration still benefits from whiteboards and Figma. Claude Code dominates as the primary tool, with engineers transitioning from Cursor to terminal based workflows.
- •Product Team Acceleration: AI most significantly shrinks the exploration phase and iteration cycles. Teams test multiple solution variations in parallel, dramatically increasing learning velocity. Engineers spend saved time on product strategy, data analysis, and wearing multiple hats rather than purely reducing headcount or costs.
Notable Moment
Lovinsky changed his view on AGI proximity after Claude Opus 4.5 release, believing we crossed an invisible capability threshold where output quality for coding and knowledge work became exceptional, but the industry lacks proper user experience packaging to make it accessible beyond technical users.
Episode Transcript
This is 20 Product with me, Harry Stebbings. Now 20 Product is the monthly show where we sit down with the best product leaders to reveal their tips, tactics, and strategies to building great products and product teams in a world of AI. I'm thrilled today to be joined by Noam Levinsky, CPO at Superhuman, formerly Grammarly. Prior to Superhuman, Nom was a senior director of product management at Facebook. And in his earlier years, he was a CPO at Thumbtack and spent five years as a director of product management at Google, where, check this out, he was responsible for all of YouTube's applications. But before we dive into the show today, you know what's wild? It's 2026 and so many product teams are still flying blind, buried in spreadsheets, chasing feedback across 10 different tools, trying to figure out what actually will move the needle. I've spoken with hundreds of product leaders, and the best teams all do one thing differently. They build a system to capture ideas, validate them with real data, and focus their road map on the right things. That's why product teams at Canva, Deliveroo, Toast, Decathlon use Jira product discovery. It pulls ideas and feedback into one place with built in tools to prioritize what will actually have the biggest impact. That's when a roadmap stops being an endless list of ideas and becomes a plan people actually believe in. Join more than 20,000 teams already using Chira product discovery. Head to atlassian.com/harry. Oh, I like it. I get my name in there. Atlassian.com/harry and start building the right thing today. After Atlassian helps your team build and ship great products, Intercom helps you support the customers using them. If you're looking for a way to transform your customer service, let me introduce you to Fin, baby. Fin is the number one AI agent for customer service resolving up to 93% of customer queries automatically. There is no other agent that can do that. Not 93% of customer queries. Okay? No other agent can do that. So why choose Fin? Fin is the best performing AI agent for CS. Fin doesn't just answer questions. It takes actions. It automates the most complex customer queries like refunds, transaction disputes, technical troubleshooting with speed and reliability. I wish my team was speedy and reliable. Beats every competitor in every head to head bake off. Completely configurable and code optional setup. My word. I mean, the benefits just go on and on. It's easy and efficient implementation. It works on any help desk with no tedious migration needs. It's trusted by over 6,000 customer service leaders, including top AI companies like Anthropic, Lovable, Synthesia, Clay, Vanta. So if you're ready to transform your customer service team, scale your support, and give team members time to focus on the really high level strategic work, learn more about Fin at fin.ai/20vc. While Fin scales your support without losing speed, Reforge shows you how to translate that scale into …
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Books, tools, and gear mentioned in this episode
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Tools
“Claude Code dominates as the primary tool, with engineers transitioning from Cursor to terminal based workflows.”
- Claude CodeRecommended
by Anthropic
“Claude Code dominates as the primary tool, with engineers transitioning from Cursor to terminal based workflows.”
by Figma
“High fidelity prototypes via vibe coding become standard for stakeholder communication, while early exploration still benefits from whiteboards and Figma.”
course
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