# Yuval Passov

Yuval Passov writes about applying AI at work, adapting your career, and building resilient habits. Passov's newsletter is aimed at founders and people working in technology; Passov draws on examples from their work at Google and startup and gaming communities.

- Profile: https://b2binfluencer.marketing/creators/yuval-passov/
- LinkedIn: https://www.linkedin.com/in/yuvalpassov
- Topics: artificial-intelligence, startup, content-marketing, ai-adoption, b2b-content-marketing
- Based on 11 dated posts, latest 2026-10-16

## Summary

Yuval Passov is most useful for founder-focused thought leadership on moving from prompting tools to managing AI agents.

- Best for: A B2B AI product campaign with co-created webinar and article for operations and product leaders.
- Not for: An enterprise security vendor needing technical lead generation, product walkthroughs, or engineer-facing detection rule training.
- Check first: Confirm sponsorship terms, audience data, and whether they show a working agent.

### Takeaways

- Move from typing prompts to managing agents that finish the work.
- Keeping up with AI is a second job you assign yourself.
- A study of AI use becomes a one-hour experiment readers can try.

## Main ideas

- **Keeping up with AI is a second job you assign yourself**: Passov argues that staying useful now means carrying two jobs: the real one and the unpaid work of learning AI. People mostly start on their own rather than because an employer mandated it, they say, and that is the point: the person who experiments independently is the one who stays relevant. The method is deliberately small and repeatable: pick one tool, give it one hour, and see what it actually does for your workflow. In an earlier post, they call the same pattern the AI Accelerator Loop: play with tools, understand how each one changes your specific work, then teach it to your group, which they describe as the fastest way to master it yourself.
- **Move from typing prompts to managing agents that finish the work**: Passov describes a shift from opening a tool, typing a prompt, and repeating the process to overseeing agents that run without being asked. They frame this as the change every founder needs to make: from passive responding to active management, treating AI as an extra worker rather than a waiting room. The practical question is who inside a company owns the agents doing the work, since Passov expects that role to compound. They extend the same idea from software to business models: from charging per seat to charging for a finished outcome.
- **Agility beats tenure and expertise**: Passov rejects the idea that a long stay at one company means settling. Experience alone does not protect anyone, they argue; the security worth having is the ability to change. They tell readers to write their own development plan rather than one for a manager, help people without keeping score, and treat flexibility as the only real security. They also warn that feeling like an expert is a danger sign, and deliberately take outside courses to escape what they call the internal bubble.
- **Protect the asset: intentional imbalance, not perfect balance**: A standing theme of the newsletter is sustaining the person doing the work. Passov argues that attention is limited and something has to give, so the goal is to choose deliberately which area to turn down rather than make a failed attempt at balance. They name guilt as the most dangerous background noise for a founder and favour small repeated habits over large plans—the tasks wait for a stronger version of you.
- **Content for buyers who are years away from buying**: Passov's guest Udi Ledergor, chief evangelist at Gong, argues that pitching a market that is not currently in a buying cycle drives buyers away. Instead, the job is to build memory links so people think of you when they are ready, roughly 12 to 18 months out—being long-term greedy. The three levels of content Ledergor names are exclusive insights from proprietary data, original surveys, and polarizing opinions. Passov credits the framework to the guest and uses the same issue to argue that businesses are moving from selling software to selling completed outcomes.
- **Read the ecosystem, then add your own take**: Passov selects a small number of outside developments—research, investor lists, funding news—and adds an interpretation rather than a neutral summary. They keep returning to where value sits when everyone has the same models: not in the model itself but in the loop between proprietary data, a shipped product, and the next training cycle, and in the messy, specific problems around the model where a generic wrapper competes directly with the labs. They also argue that a harder go-to-market can be the moat, which is why unglamorous sectors get flagged.
- **Sector view: when tools are equal, the hard part wins**: Passov applies the AI argument to specific industries: once everyone has the same tools, the edge moves back to whatever was always difficult. In gaming, that means whether the game holds people; in services, it means delivering a result rather than a licence. These positions come largely through named practitioners and lists, with Passov adding their own framing.

## Work to read

- [20 hours of travel, 1,302 AI use cases](https://passov.substack.com/p/20-hours-of-travel-1302-ai-use-cases)
- [What people really use AI for in 2026](https://passov.substack.com/p/what-people-really-use-ai-for-in)
- [The four burner stove, AI slop and outcomes as a service](https://passov.substack.com/p/the-four-burner-stove-ai-slop-and)
- [My Google Bar Mitzvah: 13 years of reinvention](https://passov.substack.com/p/my-google-bar-mitzvah-13-years-of)

## Brand relationships

- **Google** (employment)

## Partnerships

Passov's newsletter is free to subscribe to, and its issues do not disclose a sponsor, paid placement, or media kit. Google Cloud and Google Labs appear because Google is the employer; Gong appears because its chief evangelist was an interview guest. Links to Google Stitch and a NotebookLM deck sit within that employer context, not a disclosed commercial arrangement. To plan a paid collaboration, ask Passov directly whether they accept sponsorships and on what terms; the published information gives no partnership formats, pricing, editorial terms, or contact route.

## Alternatives

- Cole Medin: For a campaign that needs to prove a working agentic system rather than describe the shift in general terms, Cole Medin is the stronger choice. Their posts are about building an AI software factory: a GitHub issue goes in, a pull request comes out, multiple laps run in parallel, a manager agent checks progress and flags what is stuck, and holdout tests keep the builder from engineering only to visible tests. If the sponsor’s webinar or article needs architecture, coding-agent workflows, reliability practices, or an open-source factory that a technical audience can inspect, Cole’s material is closer to the proof point than Yuval Passov’s broad adoption argument.
- George Brontén: George Brontén is the better alternative if the campaign shifts toward sales and CRM adoption: how to make salespeople act differently, where AI should sit in daily work, and why adding another tool fails when the system only records behavior after the fact. His posts ask what a salesperson will actually work on first in the morning, argue that workflows are the overlooked lever, and test whether a system guides behavior in the moment or just documents it later. A sales-leader audience, or a sponsor selling sales execution software, would get a more direct argument from George than from Yuval Passov.
- John Soriano: John Soriano is worth considering only if the campaign shifts to DTC performance creative. His posts offer a precise diagnostic method for ad creative: compare hook rate, hold rate, CTR, and conversion to find where viewers leave, then re-cut one raw UGC clip into five testable ads by swapping openers, leading with problem or product or proof, changing pace, and rewriting captions. A DTC apparel or e-commerce sponsor that wants a creative testing webinar or article would get a more immediately usable framework from John than from Yuval Passov.

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AI-assisted summary of public posts. Audience demographics are not available. Engagement appears only where we checked recent posts. Method: https://b2binfluencer.marketing/methodology/