Glilot Capital’s internal AI agent has a name and a full-time job - Elliot. It reads deal memos, surfaces founder meeting summaries, coordinates diligence advisors, and routes work across one of Israel’s most prominent VC funds.
Amit Spitzer, Glilot’s CTO and CISO, built it largely on his own, without a dedicated budget, while running the fund’s security operations in parallel.
“We need some super agents, some super tools, some ‘super employee’,” he told me. “That were able to connect to all the tools and all the processes and basically help streamline every manual work that used to be done up until that point.”
Arik Kleinstein, Glilot’s co-founder and managing partner, added that before the agent existed, an investment decision required five to ten diligence calls conducted manually. Now, the firm can screen advisors, make contact, present a company, and schedule calls at a pace that would have been unimaginable three years ago. And since Glilot is a seed and early-stage investor, operating in a market where the window between a promising founder and a closed round can be very short. An ‘employee’ like Elliot can help VC funds find their next gold mine.
Yet for all of its assistance, Kleinstein maintains that the agent cannot do the actual job. “If you invest very early, you invest basically in two things,” he said. “One, the team, and in their imagination. And AI is not a team, and AI doesn’t really have a good imagination.”
The difference between what AI accelerates and what it cannot replace carries broader implications for how the industry should think about the technology it is rushing to adopt. Even I, as a writer, admit to using the technology in my work; transcriptions take seconds instead of hours, and I have tweaked my agents to be harsh in their review of my work before I submit to a (human) editor. It means I have more time for research and deeper conversation with my guests.
In Glilot’s instance, the fund is as committed to AI as any in the market, and it evaluates every investment, in the words of managing partner Lior Litwak, “through a GenAI lens.” But Kleinstein and Spitzer make a sharp distinction between AI as infrastructure and AI as judgment. While AI in our workflows is indeed transformative, the ability to assess an unproven founder's leadership potential remains out of reach — at least for the investing Glilot does.
“All the analytical part, to look at the technology, to look at the markets, to look at the products, all the checklist that every VC is doing… that can be significantly augmented with AI,” Kleinstein said. “But to assess the quality, the leadership, the ability of a founder, many times a first-time founder, never done it before, to actually build a team, that’s something where AI just cannot help you.”
Spitzer adds another dimension to this argument. Describing his CISO position as “part of my soul, not just my experience,” he stated that the people who get the most out of Elliot will not necessarily be the most technical members of the team. They will be the ones who know what to ask, and how. “You still need the experience of the person,” he said. “Because now you need to know what to ask the AI, how to ask it, how to navigate in the path of AI. And that skill is important with AI and before AI, but now it’s making it even more critical.”
That idea of “tribal knowledge” inside an organization or team to carry the qualities needed to thrive in the AI era was discussed in a previous episode of The Spiro Circle. AI may have access to an organization's information, but it doesn't automatically understand which pieces of that information matter, or spot what an experienced human employee would notice that isn't written down.
This reframes the debate about AI and employment and the fear that it will “take our jobs”. Currently, it appears that there will be a big shift in which part of a job it takes, with a recent IIA/Zvriran study on Startup Nation suggesting that while AI isn’t the primary reason companies are reducing their headcounts, the technology is cited by 10% of companies as the cause of hiring pauses - a threefold increase from six months ago.
In Glilot’s case, Elliot absorbs the data-gathering, the scheduling, the pattern-matching across thousands of founder meetings. What it leaves behind is soft skills, such as the ability to sit across a table from someone who has never built a company before, and decide whether to bet on them.
“The emotional part, the charisma, that’s especially important if you’re a very early-stage investor,” Kleinstein concluded. “That’s much more important than any data I can crunch.”
