Insight Partners: “Everyone will have an AI assistant, from consumers to knowledge workers. This will redefine traditional boundaries between vertical applications, automation platforms, and IT services, creating transformational market opportunities for entrepreneurs. AI assistants will take different forms, from copilots for incumbent platforms to applications with embedded AI and various forms of AI Agents. Human-in-the-loop is the operative framework for deploying generative AI solutions. Most use cases today are in experimentation or early production with a focus on advisory and assistant-oriented workflows. LLMs can’t yet predictably plan or reason and areas like memory and context are still in research. In Automation platforms where deterministic execution is critical, LLMs are being used for specific tasks at “design time,” not at “run time.” Automation is a hard problem and is often underestimated. Incumbents are adding AI to their playbooks and deep experience to improve platform efficiency and UX. State-of-the-art LLM providers are adding Agent modeling, collaboration, and access to tools to enable users to rapidly build AI Agents (GPTs). ScaleUps looking to break through need to deliver differentiated customer value with reimagined workflows grounded in unique datasets and a simple UX.”
Andrew Chen writes about boom time startups vs gloom time startups: “I hope many of you who are thinking of building a new startup are undeterred from the economic turbulence we’ve recently seen. There are huge benefits from building something new when things are a little slow. And they help create the opportunities for the next wave.”
FT: “An intriguing window into the future of money and how central bank digital currencies (CBDCs) might be used has opened up in Thailand. This future holds promise but has many hazards as well. Countries barrelling towards it, and especially their citizens, should give it careful thought. Fulfilling an election promise, the Thai government has initiated a programme to distribute money to low-income households through digital wallets. About 50mn Thais who fall below certain income and savings thresholds will get about $280 each, roughly half of monthly per capita income. This will temporarily boost household consumption and GDP but at a significant fiscal cost and without doing much to tackle deep-rooted problems, including low investment which is holding back growth.”
WSJ: “In “Pattern Breakers,” Mike Maples Jr. and Peter Ziebelman offer their perspectives on why some startups succeed while others fail, and propose a road map for improving the odds of entrepreneurial success. As venture capitalists themselves (Mr. Ziebelman also teaches a course on entrepreneurship and venture capital at Stanford’s Graduate School of Business), the authors draw heavily on their experiences with the founders of several startups, including the streaming platform Twitch, the ride-hailing service Lyft and the online education company Chegg. The premise of “Pattern Breakers” is that “inflections—such as a change in the power of a technology, a change in people’s attitudes, a change in regulations—are the underlying force that start-ups can exploit to radically alter how people think, feel, and act and thus create a radically different future.” The internet, smartphones and—most recently—rapid advances in large language models are examples of technological inflection points. The 2008-09 financial crisis and the imposition of Covid-related regulations were moments of societal and political inflections. Transformational startups, the authors observe, often “harness one or more inflections to change human capacities or behaviors in a radical way.”
