Production AI Agents Adopt 'Harness' Security Pattern
Companies are now using API gateways like Kong to deploy secure "agent harnesses"—wrappers that govern AI agent permissions, tool access, and runtime isolation. A recent post details this pattern as a best practice for managing agents that execute code or handle sensitive data, making robust governance table stakes for production AI.
Beyond API gateways, mature security for AI agents involves a layered approach. Key patterns include Just-in-Time (JIT) tool privileges, which grant agents temporary, narrowly-scoped access tokens, and execution sandboxing to contain any code they generate. This is critical as compromised agents can be used to leak data, modify records, or escalate privileges within a network. Framework selection is a key decision for any engineer building agents. For production systems needing flexibility, LangChain is often the default choice due to its extensive integrations and maturity. For multi-agent collaboration, Microsoft's AutoGen is favored in research for its conversational model, while CrewAI is preferred for production workflows that map to clear, role-based tasks. In the NYC startup scene, Y Combinator-backed companies are actively hiring for AI engineering roles. Companies like Model ML (AI for financial services), Shaped (real-time retrieval for agents), and various stealth startups are building teams. Vertical SaaS is a major focus, with startups like Keye using AI for private equity due diligence and Fernstone applying it to insurance brokerage. NYC venture capital is heavily focused on enterprise and vertical AI over consumer plays. Funds like Radical Ventures, Insight Partners, and ff Venture Capital are backing B2B AI companies, with average seed rounds for AI startups in NYC hitting $3.2M. Investors expect to see customer revenue within 12 months, valuing proximity to enterprise clients in finance, law, and other major industries headquartered in the city. The indie hacker path from side project to business is well-trodden. Instagram founder Kevin Systrom taught himself to code at night while working as a product manager before building the initial app. Similarly, Palmer Luckey developed Oculus VR in his garage while a university student and part-time engineer. The common thread is building a functional prototype in off-hours to validate an idea before quitting a full-time job. For consumer and social apps, the battle for Gen Z's attention is fought on TikTok, YouTube, and Instagram. These platforms are the primary channels for product discovery, driven by short-form video, influencer collaborations, and increasingly, social commerce features like TikTok Shop. Authenticity and interactive content like AR filters are key to engaging this demographic. Vertical AI agents are seen by many as the successor to traditional SaaS, potentially outgrowing the market by 10x. These specialized agents are trained on industry-specific data to automate complex workflows in sectors like healthcare, finance, and legal. Companies are building them to handle everything from managing electronic health records to automating compliance tasks.
