Reid Hoffman is a LinkedIn cofounder and a partner at Greylock. His work combines company building, investment and public explanations of network effects, scaling organizations and the business consequences of AI.[2]
Start with Notes from the SaaS Funeral →
X · reidhoffman Career
Hoffman joined Greylock in 2009. Before cofounding LinkedIn in 2003, he was an executive vice president at PayPal and a founding board member. His investment focus includes businesses whose utility grows as more participants join. His public work extends to books and the podcasts Masters of Scale and Possible.[2]
Contributions
Hoffman published LinkedIn’s 2004 Series B deck with slide-by-slide context and retrospective advice. It shows how he framed a professional network as a way to find people through trusted connections, then connected that value to recruiting, subscriptions and listings. His annotations distinguish the original pitch from what he later learned. He recommends stating the investment thesis, supporting each claim and naming the risks and fallback options explicitly, so investors can examine the assumptions behind the business.[4]
Ideas
In Notes from the SaaS Funeral, Hoffman argues that generating application code does not remove the need for maintenance, security, compliance and adaptation to real workflows. He expects AI to weaken some traditional software advantages while increasing the value of domain knowledge, proprietary data and well-integrated agents. These are his business arguments and forecasts.[3]
Tools, writing & talks
Writing, research & talks
Start here
Notes from the SaaS Funerallinkedin.comHoffman’s argument about software maintenance, defensibility and AI-driven business-model changes.
Read the maintenance argument before the business-model predictions. No technical prerequisite is needed; compare the claims with one enterprise workflow and its obligations beyond writing code.
Author[3]A thought-provoking analysis of why SaaS isn't dead despite AI's ability to generate code, arguing that software businesses require ongoing maintenance, compliance, and AI-native evolution rather than one-time code generation.
Catalog workOriginal source- LinkedIn’s Series B Pitch to Greylockreidhoffman.org
An annotated original fundraising deck explaining the network thesis, revenue options and risks behind LinkedIn’s early business.
Original presenter and author of retrospective annotations[4]