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Happy holidays!
The past week has given me a few days to chew on a busy month of client work and a year of lessons. Across industries and roles I continually see the same friction.. teams aren’t short on ideas or data. They’re short on a clean/clear path from insight to action.
I don’t know if it’s been the time spent building Lego sets with my kiddos or having less meetings (or both), but I was inspired to collect some of what my team and I have been learning and build 2 tools you can use to help you accelerate with AI in January. They’re both built to cut the noise, get alignment, and help you gain momentum in 2026.
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What we’re noticing in the wild
An origination team at an investment firm we’re working with has no shortage of opportunities and data, but have a hard time answering the only questions that matter.. Should we pursue this opportunity? What needs to happen next and who owns it? They don’t lack info, they need a way to triage faster and nail down next steps. The manual effort is small in the moment, but expensive over time because of how often it happens.
Execs at a research company we’re partnering with recently walked us through how time gets scheduled for new research studies. The workflow lives inside a system that’s built for project management, not quick/easy scheduling. They need a simple way to request space, see conflicts, and make handoffs visible so projects aren’t held together by hallway conversations and calendar voodoo. They’ve been trying to muscle through it for years and have hit a wall.
A marketing team at a manufacturing company we’re building with has been debating whether the first release of a new AI product for their B2B customers should include deep links down to the exact page inside a source document or simply cite sources and let the user read the doc if they want. As we’ve talked it through together, it’s become clear that the extra effort to build this would slow the launch and arguably would have minimal impact on the value for the customer and their experience.
Why these stories led me to build 2 simple tools
Across conversations with mid-sized companies in different industries, we keep running into the same patterns.. people spend a bunch of time reorienting instead of advancing the work. Critical workflows live inside systems that aren’t built for purpose or getting into a flow state. Leaders prioritize perfection over momentum.
After enough reps and seeing these patterns over and over, I realized we needed a simple way to help folks understand where their team is really at today and an honest way to choose the next bet that people will actually adopt. So I built 2 simple tools shaped by what we’ve observed:
The AI Sanity Check: A short pulse that helps leaders agree on their real starting point and commit to a measurable change over the next 30 days.
The AI Impact Analyzer: A straightforward scoring lens that makes tradeoffs visible across effort, impact, and ROI so everyone can get aligned.
These were born out of notes, calls, and screen shares. They exist to be used in the middle of real work where clarity and the order you do things in matter most.
The sanity check that keeps you honest
The AI Sanity Check is a short, plain language pulse on your reality. Most teams fall into one of these stages: Absent, Aware, Emergent, and Structured.
These labels aren’t a grade, they’re meant to be a bit of a map. The value is in what you do once you know where you are, because the most common failure we see isn’t a lack of creativity or ability. It’s unclear ownership and wobbly/undefined workflows that make good ideas hard to adopt/realize. When you move from broken to good, you feel it in response times, less back and forth, and in the simple relief of not having to ask where something lives.
The analyzer that gets everyone to “stack hands”
The AI Impact Analyzer ranks use cases by effort, impact, and payback in months, and it does it in a way that everyone can all nod and stack hands like the ‘96 Chicago Bulls (any basketball fans out there?). The Analyzer is a forcing function that highlights what will be hard, what will be useful, and what to measure.
Two rules to keep teams honest.. if perfect data’s required, it’s not a starting point. If a use case can’t be adopted/measured/maintained by real people inside your company, it’s not a good 1st bet.
How this ties back to customer/employee experience
Every backstage improvement eventually shows up front stage (i.e., things you do operationally to improve the employee experience and efficiency, will eventually affect the customer). When your team has clear next steps, customers wait less. When scheduling is simple/visible, handoffs get cleaner and your team doesn’t have to apologize for delay/confusion. When you don’t let perfect be the enemy of great and focus on shipping something valuable that you can learn from.. you’ll build what people will actually use, and the confidence that comes from momentum changes the tone of every conversation.
Wrapping up
If these stories sound familiar and you want a little structure to cut through the noise, try these tools I made and see what they surface for your team. They’re quick/painless and designed to be make things super clear and actionable for you and your team.
Onward & upward,
Drew