# Dave Schools

Dave Schools is a B2B marketer building Singulate, an email marketing platform focused on AI-assisted segmentation and personalized campaigns. His posts explain how to use data and messaging strategy to make personalization more relevant—and how to avoid generic, unchecked AI-generated copy.

- Profile: https://b2binfluencer.marketing/creators/dave-schools/
- LinkedIn: https://www.linkedin.com/in/daveschools
- LinkedIn followers: 12,949
- Median of last 8 posts: 26 reactions, 4 comments (checked 2026-11-02)
- Topics: artificial-intelligence, b2b-marketing, email-marketing, agentic-ai, go-to-market
- Based on 8 dated posts, latest 2026-09-11

## Summary

Most useful for practical guidance on AI-assisted email personalization, anti-slop rules, and where automation should stop.

- Best for: B2B agency teams running email and lifecycle campaigns wanting a practical AI personalization workshop.
- Not for: Paid endorsement campaigns with guaranteed impressions and performance targets for sales-engagement vendors.
- Check first: Confirm partnership terms, audience composition, and any comparable workshop attendance results.

### Takeaways

- Personalize only sentences that need it and check generated copy against contact data.
- Use examples to guide output and prefer ordinary segmentation where AI adds no value.
- A company-reported split test across 46 campaigns reported more clicks for Singulate's version.

## Main ideas

- **AI slop is a cost and quality problem, not a matter of taste**: The recurring argument is that AI-generated email copy has become cheap, fast and everywhere, and that most teams treat the problem as stylistic when it is really operational. The fix is framed as a set of constraints a team can apply to live campaigns: prompt one or two sentences at a time rather than the whole email, never send AI messaging on autopilot without checking outputs against the contact's actual data, write the exact sentence and only swap in the personalized parts, avoid giant essay prompts because model variability makes them unreliable and expensive at scale, use ordinary segmented dynamic content where AI adds nothing, run a prompt over personalization tokens to clean and condition messy data, and give the model two or three examples of good output to keep it on the rails.
- **Data is not the bottleneck, creativity is**: Dave Schools argues that personalization fails less because teams lack data than because they lack a messaging strategy for using it. The two halves are stated explicitly: data is one side, how you instruct the agent to use that data is the other, and improving personalization keeps moving results until you reach the scale of Amazon or Netflix.
- **Personalization is a build with five named decisions**: Rather than a single prompt, personalized email is presented as five choices a team has to make deliberately: the use case, kept specific; the model; the data to personalize against, such as form fill, industry or job title; the messaging strategy that turns that data into something worth reading; and where the personalized snippet sits inside the email. Three follow-up steps are kept short: A/B test it so you can measure whether it works, make sure it does not sound like AI slop, and confirm it integrates with the existing stack.
- **Automation with a human hand on the controls**: The stated position is that both extremes fail: the blast email is dead, but full autopilot personalization only produces slop and then creates more cleanup work. The proposed middle is agentic tools that build branded email quickly while keeping transparency, flexibility and direct edit control, with the platform deciding how to execute a messaging strategy the user has set. It is presented as a balance question, not a feature list, and the practical version for a reader is deciding which steps in their email workflow to automate and which to keep manual.
- **When everyone has the same AI tools, be weird**: This is the marketing philosophy under the anti-slop work: as AI tools spread, output converges into a sea of sameness, so differentiation through humor, shock, raw human storytelling and intensity becomes more valuable, not less. The blunt conclusion is that playing it safe and predictably will not work in B2B marketing.
- **Action at the speed of chat**: Outside email, the same thesis is applied to personal AI assistants: the change is not that tasks get faster, it is that the time it takes to note a task down is now roughly the time it takes to get the whole thing done. Dave Schools frames this as a paradigm shift in personal workflow rather than a product claim, because an assistant with logins and tools completes things directly instead of leaving a reminder.
- **Running the go-to-market in public**: A steady stream of posts doubles as a running account of how Singulate is built and sold, naming the tools and channels rather than describing the motion abstractly. This is useful for a reader trying to judge whether the ideas come from hands-on operator experience or from commentary.

## Work to read

- [AI slop is the fast food, candy, and soda of B2B marketing](https://www.linkedin.com/posts/daveschools_ai-slop-is-the-fast-food-candy-and-soda-activity-7488975167587606528-b8xU)
- [1.4 million emails, 46 campaigns, one split test on personalization](https://www.linkedin.com/posts/daveschools_we-went-back-through-a-sample-of-14-million-activity-7523062887083417602-UZTY)
- [Building your own AI email personalization agent: five decisions](https://www.linkedin.com/posts/daveschools_building-your-own-ai-email-personalization-activity-7500248694223470592-OoTX)
- [Announcing Singulate Studio](https://www.linkedin.com/posts/daveschools_today-were-announcing-singulate-studio-activity-7518343947895730176-5_rM)
- [A critical juncture in email: not blast, not autopilot](https://www.linkedin.com/posts/daveschools_were-at-a-critical-juncture-in-email-with-activity-7519004714169061378-glGx)
- [Saving $2,182 by chatting with personal AI assistants](https://www.linkedin.com/posts/daveschools_i-saved-2182-chatting-for-a-few-total-minutes-activity-7516903151816318976-DyhK)
- [Exit Five Drive takeaways: "now is the time to be weird"](https://www.linkedin.com/posts/daveschools_clod-activity-7504178021885493249-M83f)

## Brand relationships

- **Singulate** (employment)
- **HubSpot** (disclosed_partnership)

## Partnerships

No partnership offer is documented in the material reviewed for Dave Schools. His posts promote Singulate, the email marketing platform he is building, and explain its approach to AI-assisted personalization and segmentation; they are product and market commentary rather than a published sponsorship package. The evidence contains no media kit, no rate card, no stated content formats a brand could buy, and no partnership inquiry route. That is a gap in what has been reviewed so far, not a finding that he never takes on sponsored work; no such statement appears in his material. A brand planning a paid partnership should treat the commercial terms as unconfirmed until a direct route and terms are located.

## Alternatives

- Ari Yablok: Choose Ari Yablok when the agency wants the workshop framed as governance and oversight of AI work rather than as email mechanics. The posts argue that the answer to agents doing human work is not a separate tool that governs agents, but extending the control plane that already governs people to cover agents too, across every work surface, with the same policy and the same monitoring. That is the right frame for a marketing-operations or ops-leadership audience that has to decide who is accountable for agent output and how it gets reviewed. The Exit Five Drive write-up adds a broader B2B marketing craft angle — human connection, story, and marketing that does not announce itself as marketing — which is useful for a session that needs to argue why anti-slop matters commercially.
- Olivia Ward: Choose Olivia Ward when the agency's clients sit in travel, tourism, or place marketing and the workshop should be about how destination content gets surfaced by AI and how a brand earns trust there. The posts lay out three AI travel trends — hyper-personal itinerary planning, AI used for logistics as well as inspiration, and low trust, with only 6% of users reporting they fully trust AI answers — and give optimization steps against each. A conference recap adds the position that the job is teaching the robots rather than competing with them, and that tourism data needs context when it is presented to stakeholders. That maps onto a destination team's actual decisions in a way generic email advice does not.
- Jake Surrey: Choose Jake Surrey when the practical method the team needs is for paid media rather than email. The posts give two worked examples — a paid search build where Claude's output contained misaligned negative keywords that would have blocked important keywords, and a large CRO audit combining the GA4 API with Clarity data where a data anomaly was caught midway and would otherwise have distorted the recommendations. The argument that follows is that AI should not optimize campaigns directly any more than Google or Meta should, and that a human with full account context should make in-platform changes, with trust-but-verify on AI output. That is the same human-in-the-loop discipline the email anti-slop position rests on, applied to paid search and CRO.

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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/