Lightsage raises $4M to optimise software for AI agent buyers

A seed round backs the thesis that AI agents are becoming autonomous software customers, demanding an entirely new growth discipline.

By Disrupts Editorial Team Sun, 20 September 2026 AI level 2 of 5

AI level 2 of 5: drafted by our AI editorial assistant from the company's announcement; fact-checked, edited and signed off by Mark Walker, Editorial Director. What the levels mean

A dimly lit, futuristic automated warehouse features multiple black autonomous robots navigating on a floor with glowing red circuit patterns, flanked by tall shelves filled with red-lit inventory, under a prominent red circuit board design

San Francisco startup Lightsage has closed a $4 million seed round led by Nexus Venture Partners to build what it calls an Agent-Led Growth (ALG) platform, infrastructure that helps software companies win over AI agents, not just human users. The funding round draws in a notable cohort of angel investors from the developer-tooling and B2B software world, including former Salesforce CTO Steven Tamm, Postman CEO Abhinav Asthana, and Apollo CEO Matt Curl.

The thesis is straightforward but structurally significant: coding agents such as Claude Code, Codex, and Cursor can already discover software products, select libraries, install SDKs, and call APIs without any human involvement. If those agents choose a competitor's tool, the vendor may never know why, because the entire evaluation and adoption journey leaves no conventional analytics trail. Clicks, sign-ups, and demo bookings are the currency of human acquisition funnels. Agent traffic produces none of them.

From product-led growth to agent-led growth

The investor and operator class that built the previous era of software growth, through product-led growth (PLG) strategies that let developers self-serve their way to enterprise contracts, is now backing a successor discipline. ALG is premised on the idea that the agent, not the developer, is increasingly the first real customer. Whether an SDK is well-documented, whether an API authenticates cleanly, and whether an MCP server returns errors in a format an agent can parse: these are the new conversion metrics.

Lightsage addresses this by running large-scale simulations across coding agents and answer engines, assigning them real tasks that require navigating documentation, selecting tooling, and completing integrations. When an agent fails, whether at the discoverability, documentation, authentication, or API layer, the platform identifies the break point. Teams can fix it, rerun the workflow, and measure the improvement.

"We are moving from an internet where AI tells people which software to use to one where AI increasingly uses the software itself," said Jun Liang Lee, CEO and co-founder of Lightsage. "That changes what growth means. Visibility still matters, but the real test is whether an agent can understand your product and get to a successful outcome."

The convergence angle: martech meets agentic AI

The macro read-across here extends well beyond developer tooling. The marketing technology industry, a sector worth hundreds of billions globally, was built on instrumenting and optimising the human customer journey: search, click, session, conversion. If agents begin to displace humans as the primary discovery and evaluation layer across B2B software, infrastructure, and payments, that entire analytical stack faces structural obsolescence.

Abhishek Sharma, partner at Nexus, framed the stakes plainly: the internet created an enormous industry around understanding the human journey. "AI is now shifting that agency from humans to agents," he said, "which can discover, evaluate and act on a customer's behalf."

For cross-sector investors, the implication is broader still. The rise of agentic AI is not merely a software-UX question, it is a capital-allocation signal. Revenue-attribution models, growth-equity underwriting assumptions, and the valuation multiples applied to PLG-era SaaS businesses all rest on the premise that human behaviour generates observable, attributable signals. A world in which a meaningful share of product adoption flows through autonomous agents rewrites those assumptions. Lightsage is a small, early bet on that rewrite, but the roster of operators backing the round suggests the thesis is gaining traction among those who built the previous paradigm and now expect to navigate the next one.

Lightsage says it will use the funding to deepen evaluation, analytics, attribution, and optimisation capabilities across APIs, SDKs, CLIs, MCP servers, and agent skills. Developer tools are the initial focus; payments and B2B infrastructure are named as subsequent targets.