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The Twenty Minute VCThe Twenty Minute VC

Des Traynor: How to Survive and Thrive in a World of OpenAI | E1082

Des Traynor is a Co-Founder of Intercom, and has built and led many teams within the company, including Product, Marketing, and Customer Support. Today Des leads all Intercom’s R&D efforts, and parts of Intercom’s marketing.

Des TraynorguestHarry Stebbingshost
Nov 14, 20231h 32mWatch on YouTube ↗

Summaries, chapters, transcripts, and FAQs on this page are made by uListen, not YouTube.

At a glance

WHAT IT’S REALLY ABOUT

Des Traynor on AI Moats, Thick Wrappers, and Surviving OpenAI

  1. Des Traynor, co-founder of Intercom, explains how AI is fundamentally reshaping customer support and why many “AI-first” claims are superficial if they don’t change the underlying workflow. He distinguishes “thin wrappers” around LLMs from “thick wrappers” that solve an entire user workflow end-to-end, arguing that the latter will capture durable value. Traynor discusses Intercom’s AI chatbot Fin, how they evaluate and switch between LLMs, and why commoditization of models would actually benefit application-layer companies. He also explores who wins in an AI world (startups vs incumbents), how pricing, margins, culture, and marketing must adapt, and why most B2B marketing and AI features are still largely bullshit.

IDEAS WORTH REMEMBERING

5 ideas

Being truly “AI-first” requires reimagining the workflow, not sprinkling features.

Traynor argues most products claiming to be AI-first are unchanged at their core; real AI-first products redesign the job-to-be-done (like customer support) so that AI performs core workflows rather than just assistive add-ons.

Thick wrappers around LLMs will capture more value than thin wrappers.

A thin wrapper is a quick demo (e.g., ‘paste URL, answer questions’); a thick wrapper handles integration, permissions, reporting, collaboration, approvals, and end-to-end workflows that OpenAI will never go deep on—this is where defensible product value accrues.

Don’t build where OpenAI (or platforms) will hit “minimum viable good enough.”

Traynor likens chasing small gaps in a platform to picking coins on train tracks; anything that looks like a generic capability—simple chatbots, basic wealth advice, generic tools—will eventually be absorbed by foundational providers.

AI will increase startup mortality and also kill many incumbents’ products.

Many AI startups will die either because they’re thin wrappers or because margins are eaten by LLM costs, while incumbents whose workflows are easily automated (e.g., some ad-ops or analytics tools) will be outcompeted by AI-native redesigns.

Future SaaS pricing will shift from per-seat to pricing on work done.

As AI replaces or augments human work, Traynor expects pricing models to move toward value-based or consumption models tied to outcomes (e.g., tickets resolved, assets created), not headcount.

WORDS WORTH SAVING

5 quotes

OpenAI will hit some sort of minimum viable ‘what’s good enough for everyone.’ You’re never gonna make money filling in the gaps in a platform.

— Des Traynor

There’s a massive difference between a thin science-fair tech demo and an actual fully commercialized product.

— Des Traynor

If you were to build a customer support solution today, you’d build it totally different than when Zendesk was started in 2007.

— Des Traynor

Advice is almost out of date by the time it’s ‘best practice.’

— Des Traynor

You can’t listen to your customers if they’re using your competitor.

— Des Traynor

Read the available transcript
Origins and evolution of Intercom and messaging-based customer supportWhat “AI-first” really means vs superficial AI featuresThin vs thick wrappers on LLMs and where value accruesIntercom’s AI strategy, Fin, and choosing between LLM providersCommoditization of LLMs, compute costs, and infra vs application valueImpact of AI on incumbents vs startups and product strategyB2B marketing, content strategy, and lessons from scaling Intercom

High quality AI-generated summary created from speaker-labeled transcript.

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