Clay

AI in GTM at Notion — Flora Liu

Aug 26, 2026 · 21:15

Flora Liu, an engineer on Notion's GTM team, argues GTM is now a distributed systems problem, not marketing ops, and details how Notion built a unified decisioning system across self-serve and sales-assist. Workflows reduce to four questions — what do we know, what should happen next, how to execute safely, did it work — built as Know, Decide, Act, Learn layers. Snowflake computes the profile, DynamoDB serves it in milliseconds, and Notion is the substrate where humans and agents operate on the same context; signals become Temporal workflows. Agents research and draft, humans approve customer actions, and contact-sales forms are untrusted input. After 13 weeks, enterprise reps log more qualified opportunities, and context-aware recommendations made users 63% more likely to take next step.

Reverse-Engineering the AI Buyer — Aliisa Rosenthal, Acrew Capital

Aug 26, 2026 · 19:10

Aliisa Rosenthal, who helped take OpenAI's enterprise business from a couple million to several billion in revenue, argues founders should build the automated sales machine before hiring humans. ChatGPT launched with no enterprise features; nine months later they shipped an expensive product, but self-serve cannibalized it four months on. Advice: capture phone numbers at signup, reply to every inbound (10,000 a day), never give buyers homework, avoid pilots via reference calls, data evals, or 90-day opt-outs. $60 per user per month was too high; a low base fee plus usage spread. Automate security, don't pull up-market, hire AI-native sellers when buyers need contact, and use forward deployed engineers sparingly—scarce but sticky. First 10 customers should be handpicked design partners, and POCs aren't self-serve.

Cognitive Exhaust Fumes, or: Read-Only AI Is Underrated — Šimon Podhajský, Head of AI, Waypoint

Apr 8, 2026 · 11:31

Šimon Podhajský argues that read-only AI systems that analyze personal digital exhaust without the ability to write back are more valuable than agentic AI that acts on users' behalf. He built a system ingesting six read-only sources (email, journal, tasks, CRM, browser sessions, notes) that surfaces insights like intention-action gaps, attention drift, and relationship decay via cross-source pattern detection—things no single source reveals. For example, a weekly reflection skill in Claude synthesizes a brutal review of his week, and a cross-source query maps his recent reading to contacts in his CRM using Vivaldi SQLite and Clay MCP. He emphasizes risk asymmetry: read-only errors cost nothing, while write errors can be unbounded. He also acknowledges security risks like the mosaic effect and Simon Willison's lethal trifecta, noting that shell access still allows exfiltration, but argues that examined risk is better than ignorance.

The AI Engineer’s Guide to Raising VC — Dani Grant (Jam), Chelcie Taylor (Notable)

Jul 27, 2025 · 34:17

Dani Grant (CEO of Jam) and Chelcie Taylor (Notable Capital) give AI engineers a tactical playbook for raising venture capital, arguing that you don't need revenue, a product, or even to leave your full-time job to raise a pre-seed or seed round. They explain that VCs bet on founders' vision and unique insights, not perfect technology or traction, and share real cold emails that led to investments—including one that simply referenced a blog post and another that didn't mention the startup at all. In pitch meetings, they advise focusing on 'why you, why now' over tech deep dives, making the conversation bidirectional, and ending by asking about next steps. Common mistakes include over-engineering the demo, failing to acknowledge competitors, and not having a prepared pitch deck to send afterward. Grant's original Jam pitch deck is still live at deck.jam.dev. Taylor's contact is ctaylor@notablecap.com.

The Price of Intelligence - AI Agent Pricing in 2025

Feb 22, 2025 · 20:38

Shitej, co-founder and CTO of Orbe, argues AI agent pricing must continuously evolve, citing Intercom's 99 cent per resolution outcome model, Clay's prospecting credits, and Cursor's tiered usage limits. He stresses aligning pricing with target audience—SMB vs. enterprise—and maintaining simplicity and predictability. Cost structure is key: Character.AI optimized inference to support 100M DAUs, while Jasper leveraged a model decision engine to offer unlimited credits. Shitej emphasizes flexibility, noting OpenAI's price drops force repricing, and predicts 2025 will see more unlimited plans, outcome-based pricing with SLAs, and greater investment in pricing R&D for usage visibility.

The era of unbounded products: Designing for Multimodal IO: Ben Hylak

Sep 25, 2024 · 20:32

Ben Hylak, founder of Dawn and former Apple Vision Pro designer, argues that the key to building intuitive AI products in the era of unbounded interfaces is adding structure—highlighting what matters, establishing hierarchy, and leveraging familiarity—lessons from designing VisionOS. He shows how successful AI apps like Dot, Perplexity, and Claude use structure (e.g., Claude pulling code into artifacts) while the Vercel chatbot's inline dynamic UI is an anti-pattern because it disrupts conversation flow. For agents, spreadsheets (like Clay) make unfamiliar multi-step tasks familiar. Looking ahead, Hylak predicts less prompt engineering via sparse autoencoders for millions of ranked, personalized presets, shifting product evaluation from evals to user analytics as apps become increasingly personalized.