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Drew Bredvick
Mengembangkan teknik GTM ▲ @Vercel
Bersemangat untuk yang satu ini! Kami telah belajar banyak selama proyek ini sehingga senang berbagi pembelajaran & OSS kode.

Alex Lieberman2 Jan, 07.38
Bergaul dengan @DBredvick hebat minggu depan.
(Direktur Teknik GTM @vercel)
Dia mengecilkan fungsi penjualan 10 orang Versel menjadi satu orang ditambah seorang agen.
Saya akan belajar:
1/ bagaimana dia benar-benar melatih agen untuk menangani konvo pelanggan nyata
2/ di balik layar tentang perutean pesan, kualitas prospek, kapan harus mengulang manusia, dan bagaimana sistem melatih diri + menjadi lebih pintar dari waktu ke waktu
3/ kerangka kerjanya untuk memutuskan apa yang harus diotomatisasi vs menjaga manusia
Kami sedang membangun secara langsung. Bergabunglah dengan saya 👇

19
Taruhan pasti yang dapat Anda buat: AI akan lebih pintar dan lebih murah pada tahun 2026.
Ada banyak konsekuensi urutan kedua dan urutan ketiga, tetapi berikut daftar singkatnya:
- jika menambah tenaga manusia, jangan pernah khawatir tentang biaya LLM
- menulis kode sehingga mendapat manfaat dari model yang lebih mumpuni (tidak terlalu kaku)
- gunakan AI untuk memeras semua jus dari bahan baku Anda
Yang terakhir layak diberi contoh:
Banyak perusahaan memiliki daftar prospek. Manusia akan menanggapi petunjuk yang baik dan membuang sisanya.
Karena AI, masuk akal untuk menanggapi semua orang karena AI dapat melakukan pekerjaan.
Kerjakan setiap prospek. Tidak ada limbah.

Sam Altman12 Des 2025
390x cost reduction in a year!
15
Hai, saya insinyur yang membangun agen AI SDR pertama Vercel yang disebutkan di bawah ini👋
AMA

Lenny Rachitsky2 Des 2025
My biggest learnings from Jeanne DeWitt Grosser (ex-Chief Business Officer at @Stripe, now @Vercel COO):
1. What failed seven years ago now works with AI. In 2017, Jeanne tried to build a system at Stripe that would automatically personalize outbound emails based on company data. Despite working with world-class data scientists, it failed due to too many errors. Today, that exact same approach works. This shows how AI has made previously impossible ideas suddenly viable.
2. A single GTM engineer at Vercel reduced a 10-person sales team to 1 (in just 6 weeks). Jeanne’s team at Vercel had an engineer build an AI agent that handles inbound lead qualification, outbound prospecting, and deal loss evaluation. The agent costs $1,000 per year to run versus over $1 million in salaries for the sales team. The nine displaced team members moved to higher-value work rather than being laid off, and the remaining salesperson is 10 times more efficient.
3. Their AI deal-loss bot has become better at understanding what went wrong than humans. When Jeanne analyzed her biggest loss of the quarter, the salesperson blamed pricing. But an AI agent reviewed every email, call transcript, and Slack message and discovered the real reason: they never spoke to the person who controls the budget, and when ROI came up, the customer clearly didn’t believe the value claims. They are now using AI to analyze sales calls in real time and send alerts like “You’re halfway through the sales process and haven’t talked to a budget decision-maker yet.”
4. Wait until $1 million in revenue before hiring your first salesperson. Founders should continue selling themselves until they reach around $1 million in annual revenue with a repeatable process. The key is having a defined ideal customer profile—customers who look alike.
5. Segment customers on what drives their buying decisions, not just company size. OpenAI has roughly 3,000 employees, which would typically put them in the “mid-market” category. But they’re a top-25 website globally by traffic, so Vercel treats them as enterprise customers requiring complex sales. Effective segmentation combines company size with growth rate, web traffic, workload type, and industry—because selling to e-commerce companies requires completely different language than selling to crypto companies.
6. Most customers buy to avoid risk, not to gain opportunity. About 80% of customers purchase to reduce pain or avoid problems, while only 20% buy to increase upside. This means you should focus your sales messaging on what could go wrong without your product—like falling behind competitors or damaging their reputation—rather than just talking about exciting features. This is especially true when selling to larger companies, where individual careers are on the line.
7. Sales teams should be indistinguishable from product managers—for a bit. Jeanne hires salespeople who have such deep product knowledge that if you put one in front of a group of engineers, it should take 10 minutes to realize they’re not a product manager. This credibility allows sales teams to serve as an extension of research and development—a 20-person sales team talks to hundreds of customers weekly and can translate those conversations into product insights at scale.
8. Building your own AI sales tools may beat buying off-the-shelf software. Because AI is so new and every company’s sales process is unique, Jeanne finds that building custom internal agents often delivers more value than buying vendor solutions. A single go-to-market engineer built their deal analysis bot in just two days, perfectly tailored to their specific workflow. These engineers shadow top salespeople to understand their workflows, then build automation that would have taken months or been impossible just a few years ago.
9. Make every sales interaction great, whether customers buy or not. Jeanne replaced boring discovery calls at Stripe with collaborative whiteboarding sessions where customers drew their payment architecture. Many customers had never visualized their own systems before. They left with a useful asset and a feeling of collaboration, regardless of whether they bought. Many returned years later to purchase. Think about your go-to-market process like a product, not just a sales function.
10. Product-led growth has a ceiling—no $100 billion company runs on it alone. While product-led growth (where users can sign up and start using a product without talking to sales) works well for early growth, customers generally won’t spend a million dollars through a self-service flow. Every major technology company eventually builds a sales team for larger deals. The mistake is waiting too long, since building a predictable sales process takes time.
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