Coinbase Launches 'Based Agent' for Easy AI Creation

"Based Agent" is constructed using Coinbase's own developer tools, including the OnchainKit, and integrates with OpenAI's models. This allows the AI agents to perform a range of on-chain activities such as trades, swaps, and staking. For developers looking to get started, Coinbase provides a template that can be forked on Replit, requiring only API keys from Coinbase and OpenAI to begin building. The broader trend of no-code and low-code AI agent builders is lowering the barrier to entry for creating sophisticated applications. Platforms like Bubble and Softr enable the development of full-stack web and mobile apps with visual editors, while tools like Lindy AI and Gumloop are designed for creating and automating agentic workflows with numerous integrations. These platforms are increasingly being used to build everything from consumer-facing products to internal enterprise tools. New York City's AI startup scene is rapidly expanding, with a significant increase in venture capital funding and a growing number of job opportunities. The city's strength lies in "Applied AI," with startups leveraging AI to solve problems in established industries like finance, healthcare, and media. Companies such as EliseAI, which develops conversational AI for property management and healthcare, and Minimal AI, building autonomous agents for e-commerce customer support, are actively hiring engineers in NYC. For enterprise engineers looking to transition, the path of the indie hacker offers a blueprint for building and launching side projects. One software engineer, while working a full-time job, built two AI side projects that generate a combined $100,000 a year. Productivity for such endeavors hinges on creating strict time boundaries, setting small weekly targets, and focusing on consistent, incremental progress. Many successful indie hackers emphasize validating an idea and getting user feedback before spending months on development. The vertical SaaS market is being redefined by AI, moving from simple workflow digitization to intelligent decision automation. In the financial sector, AI is being used to automate complex tasks like insurance underwriting and financial forecasting. For instance, some SaaS companies have seen a 90% reduction in monthly reporting times and a 48% drop in human errors by implementing AI-driven workflows. This shift is creating opportunities for founders with deep industry-specific knowledge to build highly defensible businesses. When it comes to fundraising for AI-native applications, NYC VCs are increasingly focused on real-world applications and revenue generation. The most compelling pitches demonstrate how a product couldn't exist without AI, rather than simply layering AI on top of an existing workflow. Technical founders are advised to clearly articulate their AI's functionality, training data, and performance metrics. Investors are also keen on seeing how AI can create new revenue models, such as charging for outcomes rather than per-seat licenses. For consumer and social apps, viral growth is often driven by integrating AI to create highly personalized user experiences. Strategies such as AI-powered recommendations, in-app content suggestions, and behavioral push notifications can significantly boost engagement and retention. Another key to user acquisition is to meet users on the platforms they already frequent, like TikTok and Instagram, with compelling, shareable content. Engineers in NYC are already making the leap and building innovative AI products. Geneva Ng, a software engineer at InstaLILY AI, is focused on turning data into actionable stories for users. Other engineers are building foundational AI infrastructure to accelerate future projects and move faster on deploying AI-driven improvements. The rise of AI developer tools is also empowering individual engineers to build and deploy side projects with greater speed and efficiency.