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    Home » Making $$ with AI Agents

    Making $$ with AI Agents

    webmasterBy webmasterApril 29, 2026 All Videos 4 Mins Read
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    Limited BONUS: First 1,000 builders get $1,000. Claim yours while supplies lasts.: https://startup-ideas-pod.link/hyperagent

    I sit down with Howie Liu, co-founder and CEO of Airtable, to talk about the agent economy and the launch of HyperAgent. We walk through Sequoia’s charts on AI agent deployment, the economics of token-based work versus human labor, and why frontier agents have crossed a threshold that changes how companies get built. Howie then does a live show-and-tell of HyperAgent, including a custom "Greg Isenberg contrarian AI" skill he spins up in real time. This one is for anyone building a solopreneur business, operating a fleet of agents, or trying to figure out where to place their bet in the agent ecosystem

    Timestamps
    00:00 – Intro
    02:22 – Sequoia’s AI agent deployment chart reaction
    04:41 – Copilot vs Autopilot territory and the $1T+ opportunity
    08:13 – Agent economics vs human labor costs
    11:12 – Fastest enterprise adoption curve in history
    14:48 – The agent command center and fleet of 20 agents
    18:03 – What is HyperAgent?
    19:43 – Live demo: hyperlocal real estate market reports
    22:38 – HyperAgent as the founder, not just the developer
    23:21 – Street View, Zillow redesigns, and visual tool power
    24:15 – Command center view across a fleet of agents
    25:48 – Skills as the key primitive for frontier agents
    26:30 – Building the Greg Isenberg contrarian AI skill live
    32:31 – HyperAgent vs Perplexity Computer, Manus, OpenClaw, Codex
    34:52 – Reviewing writing skill
    36:55 – The arbitrage of persistence
    41:31 – Confidence milestones: first dollar, $10K/month
    35:27 – Reviewing contrarian tweet drafts live
    45:05 – Giving the agent feedback and building rubrics
    50:15 – Connectors, OAuth, and building custom API skills
    53:03 – How to get started with HyperAgent
    01:01:54 – Credit giveaway for listeners
    01:03:31 – Closing Thoughts

    Key Points

    * Frontier agents have crossed a threshold in the last 4–5 months where they function as true autonomous coworkers, not just chat assistants.
    * Reframe agent cost by value delivered: a $150 token spend for a board memo beats hours of human time, so anchor on opportunity cost.
    * The real arbitrage is persistence: 99% of people quit after one shot, while daily practice for 30/60/90 days produces top 1% operators.
    * Skills are the most important primitive in frontier agents, turning generally intelligent models into domain experts through playbooks.
    * HyperAgent’s differentiation is a low floor plus a high ceiling, with rubrics, LLM-as-judge evals, and fleet-wide observability for scaling.
    * Aim for $100B companies with under 5 employees, built on fleets of always-on agents mapped to human job roles

    Section Summaries

    1. The Under-Penetration of AI I open with Sequoia’s chart showing software engineering at nearly 50% agent deployment and most other categories in single digits. Howie argues even 50% understates the shift, because frontier teams now run dozens of Claude Code instances in parallel with full autonomy, while most industries are still catching up to three-year-old state of the art

    2. Copilot vs Autopilot and the Agent Economy We dig into the trillion-dollar agent opportunity Sequoia flagged. Howie frames the real TAM as the entire white-collar GDP across the Western hemisphere, arguing the unlock happened with Opus 4.5 roughly four to five months ago when agents started shipping clean PRs on multi-hour tasks autonomously

    3. HyperAgent Show and Tell Howie walks through HyperAgent live, starting with a hyperlocal real estate market report generated from one of my open-source startup ideas. The agent did market research, Reddit validation, competitive analysis, a V1 app build, a marketing site, and ad creative in a single workflow for $35 of tokens. He pitches HyperAgent as the Macintosh to OpenClaw’s Linux

    4. Skills, Rubrics, and Fleet Management Howie builds a "Greg Isenberg contrarian AI" skill in real time, letting HyperAgent research my voice and distill it into a reusable primitive. He then explains rubrics, essentially eval rubrics pinned to agents, with a separate LLM as judge scoring outputs on dimensions that matter. This is the observability layer that lets you actually run a business on a fleet of agents

    The #1 tool to find startup ideas/trends – https://www.ideabrowser.com/

    LCA helps Fortune 500s and fast-growing startups build their future – from Warner Music to Fortnite to Dropbox. We turn ‘what if’ into reality with AI, apps, and next-gen products https://latecheckout.agency/

    The Vibe Marketer – Resources for people into vibe marketing/marketing with AI: https://www.thevibemarketer.com/

    FIND ME ON SOCIAL
    X/Twitter: https://twitter.com/gregisenberg
    Instagram: https://instagram.com/gregisenberg/
    LinkedIn: https://www.linkedin.com/in/gisenberg/

    FIND HOWIE ON SOCIAL
    X/Twitter: https://x.com/howietl
    Hyperagent: https://www.hyperagent.com/
    Airtable: https://www.airtable.com/-

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