60-minute session $2,000

Claude for Research Leaders

the leadership layer, not the IC one

For heads of research, research ops leads, and team leads making decisions about how their team uses AI. This session covers the leadership layer: what to standardize, what to leave flexible, what policies actually matter, and what governance looks like when the tools change every six months. Practical, opinionated, and built for the people making the calls.

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Areas of focus

The questions your IC team can't answer.

Your researchers can tell you whether a given prompt works. They can't tell you what AI-at-scale should mean for your team's practice, or how to build governance that doesn't just sound good in a Notion doc. That's what this session is for. Here are the two tracks most leaders want to cover.

Strategic direction

What to decide, what to defend

Deciding what Claude should and shouldn't do in your research practice
Standardizing workflows without flattening individual researcher judgment
Quality guardrails that hold up when researchers use AI differently
What to tell stakeholders (and what not to) about your team's AI use
Hiring and interviewing: what AI literacy looks like in a researcher now
Measuring whether AI is helping your team or just making them feel busier
Positioning research against the "AI can do research" stakeholder narrative
Budgeting for AI tools, skills training, and the time to build systems properly

Operational questions

The stuff that lands on your desk

Rollout: introducing Claude to a team that didn't ask for it
Governance: data handling, PII, and participant confidentiality with AI tools
Building your team's Skills library without it becoming a second job
Shared vs. individual workflows: what goes in the team library, what stays personal
Training new hires on your team's Claude setup in a way that actually sticks
Handling the researcher who hates AI, and the one who uses it for everything
Running AI-assisted research through existing review and ethics processes
When to say no to stakeholders asking Claude to "just run the interviews"

How it runs

A working conversation, not a lecture.

This session is built for heads of research, research ops leads, and team leads. It's a 60-minute working conversation about the decisions only you can make, grounded in your team's actual situation.

Before

A quick context brief.

A week before, you answer a short written brief about your team's size, your current AI state, what your stakeholders are pushing for, and what you're worried about. 15 minutes of your time. It means I show up already aligned with your context.

During

60 minutes on your actual situation.

Just you and me on Zoom (or bring a co-lead if useful). We work through the decisions that apply to your team specifically. Governance, team rollout, standardization, hiring, stakeholder communication, budget defense. You get a specific point of view, not a framework dump.

After

Your own written plan.

Within a week I send you a short written summary of the decisions we discussed, the ones you're leaning toward, and the specific next actions for your team. You use it to drive internal alignment. I'm available by email for two weeks of follow-up.

What you walk away with

Clarity on the calls that only you can make.

Your ICs can figure out Claude. What they can't figure out is what "good" looks like at team level, or how to defend the research function in an AI conversation they didn't start.

A clear point of view on AI in your research practice Something you can actually defend to your CPO, your VP of Design, and your team in the same week.
Decisions on what to standardize and what to leave flexible So your team moves faster without losing the craft that makes research worth doing.
A position on the "AI can do research" narrative A clear counter-argument you can use in stakeholder meetings, grounded in what Claude actually does well and doesn't.
A rollout plan that fits your team's size and maturity Different for a team of 3 with no ops vs a team of 15 with a research ops lead. Tailored accordingly.
Hiring and AI-literacy criteria for researchers What to look for now that "uses AI" is a resume checkbox and means nothing by itself.
Ways to measure whether AI is actually helping your team Beyond "we feel faster." What to track, what to report, and what to discount.

most heads of research tell me they leave this with more clarity than they had from six months of internal AI debates.

Schedule time together

Or, pick a time right here.

Prefer to book without leaving the page? Use the calendar below. If you'd rather talk through whether this is the right fit first, book an intro.

built for heads of research and team leads