E295: Why AI Agents Will Quietly Replace 80% of Investment Teams

Feb 2, 2026

Ali Ansari, Founder and CEO of micro1, who built a platform connecting PhDs and specialists to frontier AI labs. He discusses how expert human data now limits model progress. He explains why production AI agents need rigorous evaluation and why coding is the first agent-ready use case. He also covers how micro1 scaled by refocusing on data infrastructure and the new roles humans will play.

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INSIGHT

Humans Power Modern Model Breakthroughs

Human experts, not model recursion, are the dominant driver of current LM progress.
Expert post-training data (preference labels, domain tasks) unlocks real-world capabilities.

INSIGHT

Agents Need Granular Evaluation, Not Binary QA

Agents fail in production because QA treats them like binary software instead of probabilistic systems.
Enterprises must build evaluation frameworks that measure each action and capacity before production.

ADVICE

Use Coding As The Agent Blueprint

Use coding as the killer app template since coding agents already work well in production.
Focus on replicating coding's workflow gains when applying agents to other domains.

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Why are humans — not models — still the biggest bottleneck to AI progress, and what happens when that bottleneck becomes a business? In this episode, I talk with Ali Ansari, Founder and CEO of micro1, about the hidden layer powering today’s AI breakthroughs: high-quality human intelligence. Ali explains how micro1 pivoted from an AI recruiting startup into a critical data infrastructure company for frontier AI labs, why expert-generated data is now the limiting factor in model performance, and what needs to change for AI agents to actually work in production. We also explore how focus, market timing, and ruthless prioritization enabled micro1 to scale more than 30× in a single year.

Highlights:

Why AI progress is still overwhelmingly driven by humans
The shift from pre-training to expert-level post-training data
Why AI agents fail in production despite great demos
Evaluation frameworks as the missing layer for agents
How micro1 serves frontier labs and Fortune 500 enterprises
The hardest pivot: firing customers to focus on the right market
Why market selection matters as much as product quality
How investors are using AI to gain workflow-level edge
Humans as operators of agents, not coworkers
How focus became micro1’s biggest competitive advantage

Guest Bio:

Ali Ansari is the Founder and CEO of micro1, an AI platform for human intelligence that connects highly skilled experts — including PhDs, professors, and industry specialists — with leading AI labs to generate high-quality training and evaluation data. Under Ali’s leadership, micro1 rapidly transformed from an AI recruiting startup into a core data infrastructure provider for frontier models, scaling more than 30× in a year. Ali represents a new generation of AI-native founders building companies at the intersection of human expertise and machine intelligence.

Our Podcast now receives more than 300,000 downloads a month. Are you interested in sponsoring an episode? Please email David Weisburd at david@weisburdcapital.com.

We’d like to thank AlphaSense for sponsoring this episode!

Sponsor:

AlphaSense is the AI-powered market intelligence platform trusted by 85% of the S&P 100, helping investment professionals make faster, more confident, data-driven decisions. Built for hedge funds, asset allocators, private venture capital firms, and investment bankers, AlphaSense uses advanced AI and powerful search across premium proprietary content to surface the insights that matter most—before the market moves. Elevate your research and stay ahead of the competition. Visit https://www.alpha-sense.com/howiinvest/ to learn more.

Stay Connected with David Weisburd:

X/Twitter: @dweisburd LinkedIn: https://www.linkedin.com/in/dweisburd/ Weisburd Capital: https://www.weisburdcapital.com/

Stay Connected with Ali Ansari:

LinkedIn:https://www.linkedin.com/in/ali-ansari-7b240a18b/

Questions or topics you want us to discuss on How I Invest? Email us at david@weisburdcapital.com.

Disclaimer:

This podcast is for informational purposes only and does not constitute investment, financial, legal, or tax advice. Nothing in this episode should be interpreted as an offer to buy or sell any securities or to participate in any investment strategy. All opinions expressed by the host and guests are their own and do not represent the views of Weisburd Capital. Participants may hold positions or have financial interests in the companies, funds, or investments discussed. Any references to specific investments are for illustrative purposes only. Investing involves risk, including the potential loss of capital. Past performance is not indicative of future results, and any forward-looking statements are subject to risks and uncertainties. Any third-party data or opinions have not been independently verified. Listeners should conduct their own research and consult their own advisors before making any investment decisions.

(0:00) Introduction to MicroOne and Customer Demographics (0:55) The Advancement of LM Models and Human Involvement (2:13) AI Agents in the General Market: Opportunities and Obstacles (5:57) AI Versus Human Intelligence in Performance (6:15) Identifying the Killer Application for AI Agents (7:06) AI Investment Strategies: Early Case Studies (8:28) The Journey of an AI Native Entrepreneur (9:21) AI's Impact on Venture Capital and Private Equity by 2030 (10:48) Human Roles in an AI-Dominated Future (12:13) AI Takeover Concerns and Safety Measures (14:17) Professional Growth Advice for AI Entrepreneurs (17:28) MicroOne's Market Focus and Strategic Reorientation (19:00) Insights on Adaptive Leadership in Tech (20:00) Extracting Ground Truth from Customer Feedback (20:54) Closing remarks