# Charlotte Ketelaar

Charlotte Ketelaar is the CEO of Capwave, which they describe as building AI tools for venture capital firms. Their LinkedIn posts focus on AI agents, startup go-to-market strategy, and how investors can use AI to organize information and make decisions.

- Profile: https://b2binfluencer.marketing/creators/charlotte-ketelaar/
- LinkedIn: https://www.linkedin.com/in/charlotte-ketelaar
- LinkedIn followers: 13,205
- Topics: artificial-intelligence, venture-capital, ai-agents, ai-adoption, go-to-market-strategy
- Based on 18 dated posts, latest 2026-08-31

## Summary

Charlotte Ketelaar is most useful for practical arguments on AI agents, data readiness, and venture investment decisions.

- Best for: A B2B SaaS brand selling data readiness or agent deployment tools for a webinar and article series.
- Not for: A mass-market consumer app wanting short-form video with guaranteed views, clicks, or installs.
- Check first: Confirm audience demographics, engagement results, prior webinar outcomes, and commercial terms before committing.

### Takeaways

- The agent is the last thing you build, not the first.
- They built 50 AI agents in 10 days as a solo CEO.
- Compute is now the constraint that prices every AI business.

## Main ideas

- **The agent is the last thing you build, not the first**: Ketelaar argues that the gap between buying agents and running them in production is widest in enterprise software, and that the cause is the data agents receive, not the agents themselves. Fewer than 20 percent of companies say their data is ready to be reasoned over. When context is split between an unupdated CRM, a forty-tab spreadsheet, meeting transcripts, and one person's memory, even a strong agent acts on numbers that stopped being true months earlier. The practical instruction: consolidate data first, then buy the agent.
- **Buyers will pay more for one specialized agent than for a stack with AI bolted on**: Ketelaar argues that enterprise buyers will not pay a premium for a product that is 60 percent bundled AI features, but will pay substantially more for an agent that owns a single workflow end to end. The 60 percent figure serves as a diligence checkpoint, not a debate: does the buyer pay for a feature suite or an outcome, and can the agent complete the workflow without an IT committee meeting? Products that fail those tests are incumbents in a compressing market.
- **Test every hire against what an agent can already do**: Ketelaar argues that 2023 hiring plans — a head of sales, two account executives, a customer success lead at $2M ARR — were defensive and that those reflexes no longer hold. Before opening a requisition, ask whether an agent can do the job by the end of the next quarter: yes means build the agent, maybe means wait and reassess, and no means hire and write a precise job description. The underlying priority is capital efficiency over headcount, the credential investors reward.
- **Compute is now the constraint that prices every AI business**: Ketelaar argues that compute has moved from a footnote to the center of the venture conversation, with consequences for AI-native cost structures rather than the models themselves. The figures point to three implications: third-year gross margin assumptions reset because infrastructure does not commoditize like models; an infrastructure depreciation cliff arrives into late 2027; and leverage shifts to whoever controls power, transformers, fab capacity, and memory rather than whoever ships the wrapper. The post calls the capex thesis consensus, not contrarian, and challenges readers to produce a gross margin model that survives 2027.
- **Run the scenarios or you have a prayer, not a portfolio**: Writing for investors, Ketelaar argues that every venture-backed AI company is now benchmarked against a company that loses money at scale and has not settled its own future, so marks depend on a path nobody controls. They recommend building a sensitivity table on the largest AI position and running all three outcomes, with the middle case as the deciding test. If that scenario breaks the thesis, the position is not a portfolio.
- **Venture decision-making is a memory problem**: Ketelaar's product argument starts with a comparison: the best chiefs of staff are not assistants but institutional memory, holding why a team passed eight months ago, which founder a partner liked after one dinner, where conviction started rising, and the small detail everyone else forgot. Most venture firms, the argument goes, are drowning in meetings, transcripts, inboxes, and founder updates, and almost none of it compounds. Capwave aims to be an intelligence layer that remembers how a firm thinks — prioritizing deals, preparing meetings, tracking conviction, flagging inconsistencies before diligence — rather than another CRM.

## Work to read

- [Building 50 AI agents in 10 days as a solo CEO](https://www.linkedin.com/posts/charlotte-ketelaar_most-ceos-would-hire-a-team-of-10-to-automate-activity-7448369112378044416-gVOl)
- [Most companies bought agents without fixing the data underneath](https://www.linkedin.com/posts/charlotte-ketelaar_everyone-is-buildingbuying-ai-agents-almost-activity-7463538402693595136-QmWL)
- [Compute costs as the constraint on AI margins](https://www.linkedin.com/posts/charlotte-ketelaar_six-months-ago-compute-was-a-footnote-today-activity-7460301597345001472-sYmF)
- [The 60 percent rule as a diligence checkpoint](https://www.linkedin.com/posts/charlotte-ketelaar_gtm-aiagents-fundraising-activity-7452366181023387648-9IaA)
- [A hiring test before opening any new role](https://www.linkedin.com/posts/charlotte-ketelaar_five-people-in-the-right-room-is-worth-a-activity-7453405383651528704-H_Gd)
- [Stress-testing AI portfolio marks against OpenAI scenarios](https://www.linkedin.com/posts/charlotte-ketelaar_venturecapital-openai-aiinvesting-activity-7449464271434047488-vik1)
- [The chief of staff as institutional memory](https://www.linkedin.com/posts/charlotte-ketelaar_the-best-chief-of-staffs-are-not-assistants-activity-7465730849267879936-4BTg)
- [Leaving the tech bubble: what most firms actually need](https://www.linkedin.com/posts/charlotte-ketelaar_sometimes-leaving-the-bubble-is-the-most-activity-7464643182656589824-P0RR)

## Brand relationships

- **Capwave** (employment)

## Partnerships

Charlotte Ketelaar’s posts don’t publish a sponsorship policy, rate card, media kit or disclosed paid brand partnership. Their commercial content promotes Capwave, the AI tooling company they lead for venture capital firms, and invites readers to engage with it; it describes no third-party collaboration or terms. A B2B SaaS company considering a collaborative webinar or article series on AI agents and go-to-market strategy would need to negotiate formats, deliverables and compensation directly. The practical first step is to pitch Ketelaar on LinkedIn, outlining the proposed series, its audience, what the company would supply and what it would expect in return. Ask directly whether they’re open to sponsorships.

## Alternatives

- Greg Spence: Choose Spence when the campaign goal is to fix sales execution and revenue operations, not get AI agents into production. Two posts argue that hiring more salespeople on top of a broken model only adds payroll, meetings and noise. They lay out the alternative: GTM strategy before job descriptions; account-management standards for the largest customers; enablement before ramp pressure; forecasting and KPI governance so "pipeline" means the same thing to everyone; and a CRM people can actually use. Spence reports building and scaling national sales organisations four times, including taking C-Suite Network from zero to 11 BDRs with playbooks, compensation design and data analysis already in place. Partners selling to sales and revenue leaders, or pitching a rebuilt revenue engine, get a more exact practitioner voice here than in Ketelaar's agent-deployment frame.
- Bronson Harrington: Choose Harrington when the buyer is a law firm or professional-services practice and the campaign is about local organic growth and web infrastructure. One post argues that law firms are adopting AI for contracts and documentation while still relying on slow agency retainers for client acquisition. It describes restructuring legal-sector search work into a tiered lifecycle — foundations, growth, domination — and launching BRONSON around custom web frameworks and technical link routing. A second post analyses nearshore hiring economics, breaking down a LATAM listing that bundled SEO strategy, video production, outbound prospecting, CRM administration and automation into one contract at roughly $1,200 a month. Partners selling marketing infrastructure or managed search into legal services get directly usable material here.
- Lindsay Timcke, MBA: Choose Timcke when the partner sells AI governance, controls, audit or risk tooling, and the audience is risk, audit, finance and IT leaders rather than founders and operations staff. One post argues that internal audit is about to meet a population it cannot sample; controls in an agentic environment act jointly like a circuit rather than a checklist; and a monitoring agent needs its own identity, credentials the watched agent cannot see, and a different model family to avoid correlated failures. A second argues that AI will dissolve deterministic work in Finance and IT and that the surviving function is a risk-first architecture. Partners campaigning to govern agents that are already running get a more exact match here.

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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/