Employee Onboarding in the Age of AI

Posted on by Brendan

I am four weeks into a new job where I actually boomeranged back to the company I was at 12+ years ago. This is my first time onboarding to a new company in the age of AI since I hadn’t onboarded somewhere since 2022. 

I decided to boomerang back to Seer Interactive for two reasons. First, for its growth and learning culture. It aligns deeply with who I am to my core. And also given the time we’re in with search and broader AI technology, I wanted to prioritize learning over anything else. I knew I’d get it here. 

Second is I wanted variety. What does that mean? To me, it means the variety of what I see (i.e. challenges, problems, opportunities), who I work with, and the pace in which we’re moving. After 11+ years driving organic search strategy in-house, I knew that beat so well it felt like it wouldn’t be much variety. 

It’s been great so far for a lot of reasons but one I want to share today is because of AI. 

Onboarding to a new company that has proper AI infrastructure in place (i.e. Seer) has been amazing. The point I am making is AI clearly drives ROI for employee onboarding. Assuming the company has the infrastructure in place. 

Within the first four weeks, here’s a few AI things that have helped me ramp quickly: 

  • Daily Briefings: my daily briefing agent helps synthesize context, priorities, and what matters across my portfolio. 
  • Client Pulse: Getting up to speed on client sentiment, nuances, historical goals, and current standing quickly versus sifting through old threads and having tons of internal meetings. 
  • Quick sounding board for acronym checks, team structure and basic questions. 

All the above preserves internal team members time, lets me have more strategy conversations with people, and allows me to add value faster. 

So a faster ramp within a company that’s made the right AI investments, doesn’t just benefit the business; it accelerates an employee’s ability to lean into growth, learning, and impact on day one.

How to measure this for anyone who needs to see the numbers? 

  • Time to First Value: think of something like date of first shipped deliverable, test launch, test read. Things that help drive actual impact. Metric: Date of First Shipped Deliverable – Start Date
  • Time to Full Utilization / Standard Output: Days until the hire reaches the target output expected of a tenured peer in that role. Metric: Date Target Output Sustained for 30 Days – Start Date
  • Time and Cost of Existing Employees Training New Hires: When tenured staff train a new employee, the true cost consists of direct time plus opportunity cost (billable or strategic work not completed).

This is a clear AI ROI case to me.

Thoughts on Dots

Posted on by Brendan

This week, OpenAI announced Dots. What they called, “remarkably capable, always-on agents built to handle everything.” And Dharmesh Shah had this to say about it:

I couldn’t agree more. Whether learning, working, collaborating, or parenting, my default mode is connecting dots. Just last week in a meeting, I referenced a report template that tied directly back to an all-hands release meeting. It took a moment for the person I was meeting with to bridge that gap, but once they did, the path forward was instantly clear. Sometimes I spot those intersections faster than others; other times, teammates help me connect them.

One of my personal goals is communicating those synthesis moments more effectively. That’s why tools like Dots excite me. Not just to automate tasks, but to help scale how we synthesize and share context.

I’m going to keep learning and leveraging AI to map those patterns faster and in ways my own brain can’t match alone. My one prediction? “Dots” won’t achieve the household-name stickiness of ChatGPT, but the utility underneath it is the real deal.

Grow Google. Diversify away from Google.

Posted on by Brendan

That’s the whole strategy in six words. Both for Google and for any business that depends on it.

A month after Google I/O and Google Marketing Live, the instinct inside most companies is to react to every announcement. A ton gets announced at I/O; it’s a conference, and not everything sticks. The part of this job I love is the opposite of reacting: studying, thinking critically, and sifting the noise down to what’s actually going on and what businesses should do about it.

Where I landed is Google’s strategy unfolding now and over the next few years, runs on three moves: Protecting/Defending, Diversifying, and Exploring. I believe enterprises should mirror this in ways unique to them.

Most leaders stop at the obvious points: Google has to protect its cash cow, and it’s caught in an innovator’s dilemma. Both are true. But the I/O story is evidence of more than defense; it’s evidence of mobilizing. Protecting has short-term implications. Exploring is the 1-2 year horizon and beyond. Diversifying spans both.

Protecting / defending. Google is holding onto ad monetization for two search intents as long as it can: navigational and transactional. If and when does that break? I don’t know but it only breaks when another platform offers something good enough to make people switch. On transactional, I’m with Paul Graham’s critique, but an irrelevant ad in image search isn’t enough to move people. On navigational, Kevin Indig’s piece on the brand tax nails it and this certainly can’t keep climbing and going on forever.

Diversifying. Expect Google to push advertisers toward YouTube as a Meta alternative, maybe Discover too. Wherever it can open ad inventory across its surfaces. In my opinion, these are always worth a look, some of these may be well-priced, effective placements.

Exploring. The bets that matter most for anyone with products: Universal Cart, the Universal Commerce Protocol (UCP), AI Mode, the new Conversational Attributes schema in Merchant Center, WebMCP, and information agents. (There’s plenty more but those six are the ones reshaping the path from discovery to checkout.) I call it exploring because nobody knows yet what gains traction or how Google monetizes it (i.e. traditional ads, enterprise contracts, subscriptions). What’s obvious: Google is chasing (1) one thing social platforms have more of – time spent and (2) Share or ecommerce search from Amazon. 

So what does this mean for organic search strategy and where you deploy resources? Four principles:

  1. Differentiation: what you invest in is genuinely different from the field of competition.
  2. Experimentation: or it’s a new bet with first-mover or arbitrage upside, on Google or somewhere else. You want a mix of the two.
  3. Prioritization: you can’t chase everything. Pick the right number of bets, and remember they’re bets. AI lets you take on more at higher quality; apply the learnings, then move to the next one.
  4. Cost-effectiveness: for the channel overall and for each strategic investment. What will it cost? How complex is it? How much upside toward the channel’s total upside? How much time should the team spend?

One more thing: organic search can’t run in a silo. On the strategic bets leaders have to get teams talking, finding shared goals and common ground, to drive 1+1=3 outcomes.

There’s AI-driven revenue to capture, and I haven’t been this excited to chase something since I found SEO on Twitter in 2012. Cheers to that.

Workplace Agents vs. Personal Apps

Posted on by Brendan

After two years away from the blog, I’m trying to build the writing habit back into my weekly routine. I am starting with two different product marketing announcements that caught my eye this week:

Taking these posts in isolation, one wants to be your office manager; the other wants to be your personal lifestyle assistant.

I’m particularly interested in Claude’s “quiet” social post. In a world of loud announcements, a low-stakes social post is a genius way to gather real-time signals. They aren’t just announcing a feature; they are testing a hypothesis: Do people actually want AI in their personal lives, or just their work?

The Takeaway: Don’t get distracted by the pace of launches. The real work is following customer behavior and having the guts to ship “quiet” experiments mapped to big bets to see what sticks, like these companies are doing themselves.

Weekly Listen #4

Posted on by Brendan

I stumbled on Kevin Rose’s podcast and decided to watch this one first. I was excited to find this because I watched his first interviews about 12 years ago with tech entrepreneurs and got a lot out of them. I think he called the show The Foundation back then.

One piece they talk about is encouraging failure and learning from failure for kids which I believe is important too. I’ve been enjoying watching my oldest who is 3 during soccer on Saturday mornings. He’s young so he’s failing a lot whether he picks up the soccer ball instead of kicking it or doesn’t understand the drill. Rather than correct him, I just watch him. He’s having fun anyway so that’s another reason I sit back. He doesn’t need my help.

I was thinking the other day at some point that his consciousness will develop and we’ll see how he reacts to knowing about these small failures.