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Description
This package is an adapted version of the standard I used to hold teams to at Bain and as a Director at Deloitte — how a team thinks, communicates, and makes decisions when the ground keeps shifting under them. AI is doing that to most organizations right now. This works with a team, a function, or a leadership group that's trying to adopt AI tools without losing the judgment and rigor that made the team good in the first place. While this can run as 1:1 coaching, it's built for a group: a team split on how much to trust AI-generated work, a leadership group unsure how to redraw roles as AI takes over parts of them, or an organization that's adopted the tools but hasn't changed how it makes decisions. We'll work through the managerial challenges I've seen come up most, including: - Keeping a team's standards intact when AI makes it easy to produce something that looks finished but hasn't been checked - Deciding what a person still needs to verify by hand, and what's safe to hand fully to the tool - Redrawing roles and review processes as AI changes who does the first draft of the work - Choosing an adoption approach for the team — and being honest about what each approach trades off - Building the habit of questioning AI output the way you'd question a first-year's first draft - Recognizing where generative AI specifically demands a different kind of oversight than past tools did This can run as a single half-day session or extend across several sessions, depending on the team and the problem. The more I understand about your organization and where the friction actually is, the more I can shape the sessions around a live planning problem, a team-culture reset, or a structured retrospective on how AI adoption has gone so far.
What you'll get from this package
Dedicated time for your team to work through a real organizational issue tied to AI adoption
A shared standard for what still needs human review, and what doesn't
Practice surfacing and discussing the tensions AI is creating on the team, out loud
A clearer read on how to redraw roles and review steps as AI changes the work
Talk to a team member
Schedule a call with a Leland team member who can help you explore your options.
Schedule a call
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Get help with AI Fundamentals, AI Ethics & Responsible AI, and .
Offered by Ashwin S.
Joined June 2024
4.96
Build AI solutions from prototype to production
I coach people who want to build something real with AI, not just get better answers out of a chat window. I run a software business that I built this way myself. No engineering team. That means I have made most of the mistakes already, and I can usually tell within a few minutes why someone's project is stalling. A few things I can help you build: • A working product or internal tool. MBB Prep runs AI case simulations, a large drill library, and a web app I built and shipped without engineers. If you have a product idea and no technical team, this is the conversation I know best. • Content and document pipelines. I generate presentation decks, formatted documents, and PDFs programmatically at volume, with quality checks that catch errors before anything reaches a customer. Most people stop at the first draft. The value is in the checking layer. • Research and data workflows. I run a weekly scraper that pulls listings from multiple sources and returns a clean, formatted spreadsheet. Same pattern applies to competitor tracking, market research, or any task you currently repeat by hand every week. • A house style a model can actually follow. I built a written system that keeps my scripts, sales copy, and coaching explanations in one consistent voice across everything I publish. If your AI output all sounds the same as everyone else's, this is the fix. • A single problem you are stuck on. Bring the project. We will scope it, work out whether a model can realistically finish it, and build the first working version together. • I will also show you where these tools fail. Output that looks polished is often quietly wrong, and business logic and maths are where it goes wrong most. So I will show you how to check a result before you rely on it, when to push back on what a model gives you, and where your own judgment still has to do the work. My consulting background is the useful half here. Structuring the problem before you prompt it is most of the work, and it is the step almost everyone skips.
$1,999
6h–14h of coaching