Brett Willms

Laetro

CEO, Co-Founder

Indeed.com

Developed Indeed.com/Lead and Indeed Work Happiness Score.

VP Marketing, Experience

Google

Director of Marketing, Google Fiber

Bitty, Inc.

Bitty automatically builds mobile websites for small businesses using information and assets  available across the web.

Co Founder

Gusto (formerly ZenPayroll)

Named Gusto.com. Built the Brand. Developed core marketing engine incl. Gusto for Accountants.

CMO, Growth

Leads strategy, brand, customer acquisition and retention programs for Google Ads & suite of small business products.

Director of Small Business Marketing, Americas

Leads strategy, program development and operations of digital performance marketing / new customer acquisition for Google Ads & suite of small business products.

Director of Digital Customer Acquisition, Small Business (O-Force)

Country Marketing Manager, Canada

Let's get creative with AI.

I've been creating things, every minute of every day, ever since my mom turned around in the front seat of the car and said, "Let's play a game". She explained, "Every time you notice something neat in the world, notice what's missing. Notice how things could be even better. Imagine what you would create if you could create anything, and we'll daydream about it together. This is inventing." I fell in love with inventing at that moment, and have never stopped.

Malcolm Gladwell said it takes 10,000 hours to become an expert at something. I've been inventing deliberately, non-stop, for over 40 years. I have thousands of inventions and have brought hundreds to the world: a collaborative online market research platform that's still around today, Canada's first performance advertising network, a machine that makes websites in 10 minutes, Google's (and Gusto's) approach to customer acquisition, and Google Partners – Google's largest money-making marketing program ever, now generating billions annually.

Above all, I love inventing ways to help others flourish. Like the Indeed Happiness Score – a program we created at Indeed to help people be happier at work, and let everyone know where all of us are actually happiest working.

What would make you happiest at work?

For me, it's having the freedom to create. And in today's AI revolution, I see an unprecedented opportunity to give everyone that same freedom.

So, I'm building Laetro AI. The all-creative AI platform transforming how brands produce marketing assets. By orchestrating the latest state-of-the-art creative AI models, we enable marketers to generate their entire suite of marketing materials faster and more efficiently than ever before, while maintaining their unique brand style and tone.

What makes us different is our commitment to both creativity and fairness. We've built an ecosystem where professional creatives are compensated for contributing their unique styles to our AI system, creating a library of authentic, ethically-sourced creative approaches. Brands can either tap into these curated styles or develop their own unique AI style, ensuring their marketing materials remain distinctively theirs.

All with no quality compromises, just pure creative potential realized.

Whether you're a brand looking to revolutionize your creative process or an innovator excited about the future of AI-powered creativity, I'd love to connect. Let's explore how we can make the creative process more efficient, more inspiring, and more human together.

Let's ride!

The new way for brands to get Creative.

Good Content

At Good Content, we help B2B technology companies turn great ideas into high-quality published content. Our approach empowers experienced human writers with advanced AI tools to produce better content in less time, without sacrificing nuance or brand voice. We can also support thought leadership content with original research. 

Services include:

Market Research 
We turn public conversations into usable insight. By ethically collecting and analyzing data from publicly available sources, we help you identify what your audience is actually saying, not just what industry analysts report. From emerging concerns to unexpected use cases, our research surfaces data points and voice-of-customer language you can use in campaigns, pitch decks, and media outreach.

Thought Leadership
Original thinking deserves original content. Our goal is to get unique points of view out of your experts’ heads and into the world. We create long-form editorial assets that combine SME interviews, data-backed analysis, and incisive editorial framing. Deliverables may include eBooks, white papers, keynote talking points, and contributed articles.

Copywriting
Foundational content still matters, and it needs to be done well. We deliver the blog posts, case studies, landing pages, and product copy that support ongoing conversations with prospects and clients. Whether you're launching a new product or maintaining a regular cadence of marketing content, we match your brand voice and make sure every asset serves a clear business goal.

AI Enablement
We help marketing teams analyze their content operations to identify where AI can add the most value for your team. That might mean recommending off-the-shelf tools, refining your editorial workflow, or building lightweight AI solutions to accelerate production. We also offer a customizable version of our own platform, Good Bloggy, which supports the creation of longer-form copy drafts.

Founding Writer 

WonderingAbout.AI

WonderingAbout.AI is where I write about the human side of AI adoption. From shifts in creative industries to classroom policies and everyday tools, my goal is to look at the real-world impact of AI beyond business strategy and into daily life.

My work on this blog includes hands-on research. Depending on the topic, I may collect datasets (ethically, of course), build experiments, interview experts, or simply talk with people dealing with AI-related change firsthand.

Also, I'm always looking for guest posts. DM me if you have an idea.

Founding Editor

Good Bloggy

I built Good Bloggy because I was tired of writing long-form content in chat windows.

Like many AI power users, my workflow involved feeding an outline to a language model—often one section at a time—along with any previously written material. It worked… kind of. But the process was painfully manual. Each round of prompting meant copying, pasting, reformatting, and scrolling endlessly through cluttered chat threads just to keep things coherent. And line-editing was virtually impossible in chat UIs not built for writers.

So I built the tool I wished existed.

Good Bloggy runs on Claude 3.7 Sonnet and offers a clean, familiar writing interface with tools designed specifically for long-form AI-assisted content. Features include:

A standard text editor with formatting, not a chat box

Section-by-section generation without having to paste in prior context

Instant AI rewrites with one click

Auto-generated meta tags and social copy

All your content, neatly organized—no more losing your place in a sea of messages

It’s built with Python, Django, PostgreSQL, and Bootstrap, and hosted on Heroku. I also dislike monthly subscriptions, so Good Bloggy offers usage-based pricing. 😄

Explore it at goodbloggy.com

Co-Founder

The Argonaut US

Before founding Good Content, I was Director of Content Strategy at The Argonaut, where I led account strategy and content production for a portfolio of B2B tech clients including Adobe, ChargePoint, Confluent, Drift, and others.

Over time, I grew annual content-driven revenue from $200K to $2M, building a scalable process for producing high-quality assets that supported every stage of the buyer journey.

I personally led the development of 200+ unique content pieces—everything from blogs, eBooks, and messaging docs to videos, podcasts, and landing pages. To support that volume, I built and managed a nimble team: one full-time copywriter/strategist and a bench of three freelance writers, all focused on delivering strategic content that moved the needle.

Collaborating with cross-functional teams across Studio and Operations, I oversaw complex, multi-asset campaigns requiring both high-touch client service and standout visual design. I worked closely with clients to develop detailed content plans tailored to their goals—ensuring we didn’t just make content, we made impact.

Director of Content Strategy & Services

Senior Copywriter/Content Strategist

Copywriter

Bridging Human Creativity and AI Efficiency | B2B Content Strategist and AI Writing Expert

I bridge the gap between content strategy and execution for B2B technology companies, helping them turn great ideas into high-impact blogs, case studies, eBooks, and thought leadership content.

Over the past 15+ years, I’ve seen firsthand that while developing a solid content strategy is important, execution is where most programs struggle. A multi-channel B2B campaign may require 20+ high-quality assets, each traditionally taking weeks to produce. The result is typically bottlenecks, delays, and missed opportunities.

At Good Content, the B2B writing and research agency I founded, we empower human writers with AI tools and automated editorial systems, so we can move faster without sacrificing quality. All our processes are human-led, and we always disclose how and when (and if) AI is used in projects.

But writing great content is only part of the picture. Increasingly, technology audiences want thought leadership that’s backed by original research, not just opinion. When clients don’t have proprietary data of their own, we help fill that gap.

First, we collect data (carefully and ethically) from publicly available sources, such as Reddit posts, blogs, job listings, and other digital media. Then, we apply machine learning models (e.g., clustering, sentiment/emotion analysis) to uncover trends, behaviors, and patterns worth talking about.

The resulting data and insights can be featured in white papers, keynotes, blog posts, and sales content. They can also be shared with journalists.

How I support B2B tech clients:

Premium, human-crafted content for high-stakes assets
AI-accelerated editorial systems that speed up production without sacrificing voice
Custom research + ML analysis to power data-backed thought leadership when internal data isn’t available

Whether you’re looking to scale a content program, explore how AI fits into your strategy, or develop insight-rich thought leadership that earns attention, I’d love to connect.

Areas of expertise:

B2B Content Strategy & Execution
AI-Enhanced Editorial Systems
Thought Leadership Development
Custom Research Using Public Data
Sentiment & Emotion Analysis for Content
SME Interviewing & Long-Form Writing
Brand Voice Preservation at Scale

Karen Spinner

Four weeks ago, I made a commitment to explore whether StackDigest, the newsletter digest, discovery, and analytics tool I built for Substack users, could grow from project to product.

I spent that time listening carefully to users, adding features, and taking a hard look at whether anyone would really consider paying to use it.

Early last week, StackDigest reached 165 beta users, and I decided it was time to take the next step: a product launch. At that point, I arranged for a legal and compliance review as part of my due diligence.

And, unfortunately, I received some bad news. Scaling up my tool would have put me at risk of violating Substack's TOS. The only sensible course of action was to shut it down.

However, while this ending to the StackDigest story was disappointing, I also learned a ton about production-grade systems design, machine learning, user-led development, and founder-led content.

I also made lots of new friends on Substack, many of whom used the tool and provided invaluable feedback, and incidentally grew my newsletter to almost 900 subscribers. 

I've written a post-mortem of the project, which I've linked in the comments. My goal for the next project? Do the legal and compliance review much earlier, and make some new and different mistakes.

Writer & Content Strategist | Research Automation + Machine Learning | Data-Driven Brand Journalism

The people who spot AI text best aren't who you'd expect.

Research from UMass and Microsoft tested how well humans detect AI-generated articles from GPT-4o, Claude, and o1.

The findings surprised me, because I've always assumed that heavy reliance on AI for writing tasks can blind you to AI-style quirks (e.g., the boiling-frog effect).

Instead, people who use ChatGPT daily for writing tasks spotted AI-written copy with 92.7% accuracy.

These daily users recognized the patterns, such as the overused words ("delve," "tapestry," "crucial"), the formulaic hooks and constructions, and the lists of exactly three things, because they'd seen them hundreds of times.

Meanwhile, people who rarely or never use AI often failed to detect it, achieving only 56.7% accuracy. Basically, a coin flip. They were also very confident in their wrong answers.

There's a broader lesson here that goes beyond AI detection. You don't develop judgment about something by avoiding it. You develop it through engagement.

In other words, distance doesn't create insight. Usage does.

p.s., I found this research paper while testing Future Scan, my new research trend analysis tool. And I created the graphic with Nano Banana.

New project announcement: Future Scan (prototype)

Last week I was researching LLM jailbreaking trends for a story I was writing…and I hit a wall. Google buried the research I needed under endless Reddit threads. And searching public research libraries yielded thousands of possible results.

Neither helped me answer a simple question: What are researchers who think about jailbreaking (and other AI security issues) looking into right now?

That frustration pushed me to try something new. Using the same semantic-search and clustering techniques I built for StackDigest, I put together a prototype tool I’m tentatively calling Future Scan.

🔍 What it does
Future Scan analyzes thousands of research paper abstracts from arXiv, which is a free, open-access repository for physics, math, computer science, and AI/ML. It then:
*Clusters papers into themes using cosine similarity
*Surfaces emerging patterns
*Highlights shifts that would take weeks to spot manually
*Reduces the noise so you can focus on what's changing

After testing it locally with abstracts from 11,000+ AI/ML papers, I pushed it to production for testing with 30,000 abstracts...and 10 friends from Substack who volunteered to be beta users. Feedback is already coming in! 🎉

📌 Why I’m building it
Writers, researchers, and investors shouldn’t have to rely on social-media hype cycles to understand what’s happening in research-heavy fields. With the right data and the right ML techniques, we can get a clearer view of the ideas shaping the future.

And while my prototype focuses on AI/ML research, the same method could work for any domain where people need to spot real research trends without drowning in PDFs: medicine, biology, social sciences, etc.

I've linked to the landing page as well as an article with a bit more backstory in the comments. (The video attached to this post was captured last week in my development environment.)

Please DM me if you'd like to give it a try. If initial testing goes well, I'm hoping to add another 10 beta users next week.

The Turing test traditionally asks: can you tell if this message is from an AI? But new research from the University of Konstanz asks something different: can you tell if this entire conversation is AI-generated?

Researchers collected authentic Reddit discussions, then had GPT-4o and Llama 3 generate fake versions on the same topics. Study participants saw both side-by-side.

The results are a little scary. 

AI-generated group conversations were mistaken for real human discussions 39% of the time.

When evaluating Llama 3 conversations specifically, participants identified them as AI-generated only 56% of the time, barely better than random guessing.

Think about the implications.

We've been focused on detecting fake articles, fake reviews, fake essays. 

But what about fake communities? Fake discourse? Entire simulated social environments?

If AI can convincingly generate multi-user discussions, we're dealing with synthetic social proof at scale.

The researchers call it "The Collective Turing Test." I'd call it a wake-up call.

p.s., I found this research paper while testing Future Scan, my new research trend analysis tool. And I created the infographic with Nano Banana.

I’m excited to share some initial thoughts on Future Scan from Daria Cupareanu, one its very first beta testers.

Perhaps the most interesting thing I learned during this round of testing is that Future Scan could be a good fit for researchers in corporate and university labs and analysts at B2B tech companies planning for cutting-edge AI/ML developments.

I’ve left a link to the landing page—with new messaging—in the comments. I’m currently putting together the next cohort of beta testers. 

If you’d like to try it or just have questions, please send me a DM.

Founder @AI blew my mind | Founder @DO-IT App | Helping you turn AI into a practical advantage 🚀

Karen Spinner just launched the research tool I’ve been missing.
It’s called Future Scan - and she’s now looking for researchers in universities and company R&D teams to try it out and share feedback so she can keep shaping it into something useful for them.

I’ve been using it to stay on top of AI trends and find relevant papers fast for AI blew my mind. 

But for actual research teams, I can see it being even more valuable: surfacing themes, spotting patterns across papers, and cutting down the manual work of finding what matters.

It’s in closed beta, so if you want early access, DM her.

And if you know someone in research who’d benefit from a tool like this, feel free to pass this along or share the post.

This is a wonderful roadmap to Substack publications that are breaking new ground. Also, if you’re a marketer, partnering with newsletters to create sponsored content can be a surprisingly effective alternative to traditional content syndication.

The New Titans of Media

The future of media is shifting fast — and creators are becoming the defining force in how people choose to get information.

Legacy publications are closing. Many are losing relevance. Startups and VCs are increasingly choosing to break stories with creators instead of traditional outlets. That alone tells you everything.

To help you navigate this new landscape, we just published our latest essay — plus the first market map of its kind, covering 90+ Substack creators across the most important technology categories. 

We've broken down the creators and their media channels into the following categories 👇

- Marketing & GTM
- Engineering
- Post Legacy Media
- Startups & Venture
- Product
- Careers
- Climate
- Consumer
- FinTech
- Finance 
- Semiconductors
- AI

Technology media is being rebuilt right now — and these are the creators leading the way.

👉 https://lnkd.in/eX56Ucpi

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Brett Willms

Karen Spinner

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The Battle

Brett Willms

Karen Spinner

Followers

Posts

Engagements

Likes

Performance Score.css-goub6s{font-size:var(--chakra-fontSizes-md);font-weight:500;color:var(--chakra-colors-gray-600);display:block;margin-top:var(--chakra-space-1);}Karen Spinner's LinkedIn Performance

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