Frequently Asked Questions¶
Everything you need to know before (and during) the Impact Lab. Read through this page before Day 2 starts — it'll save you a lot of "wait, what?" moments.
The Basics¶
What is the Impact Lab?¶
The Impact Lab is the hands-on portion of Ship Summit — a one-and-a-half-day curriculum where you build real software with AI tools. You'll work in a team of four, follow a structured learning path, and ship a working product by the end.
This isn't a lecture series. You'll spend most of your time building, discussing, and iterating — with teaching sessions woven in at the moments you need them most.
What's the schedule?¶
Day 1 is conference talks — you'll meet your team but no Impact Lab yet. Soak it in. You'll apply what you learn on Day 1 during the Impact Lab.
Day 2 is your first full day in the Impact Lab. You'll start at 9:00 AM and wrap up around 6:00 PM. The morning schedule varies by track, but from lunch onward all tracks follow the same timing.
Day 3 picks up at 9:00 AM with your final build sprint, then transitions into team demos, cohort voting, and a close-out by the afternoon. Winning teams from each cohort present to the full conference at the end of Day 3 — Thursday.
Throughout both days there are scheduled breaks. Use them.
What are all these skiing terms?¶
We borrowed the vocabulary from ski culture — partly because the domain you're building in is avalanche safety, and partly because it's more fun than "Module 3, Activity 2."
| Term | What It Means |
|---|---|
| Lift | A teaching session — concepts are introduced, mental models are built |
| Run | A hands-on build challenge — your team applies what you just learned |
| Reflection | A team debrief — what worked, what didn't, what surprised you |
| Ski Instructor | Your cohort captain — keeps the group on track, manages time, leads discussions, and collects feedback |
| Basecamp | The on-site support area staffed by vendors and technical specialists |
The flow is always the same: Lift, then Run, then Reflection — repeated four times across the two days. Workshops are interweaved when they make sense for the content.
What am I actually building?¶
Real avalanche safety software. Depending on your track, that might be a backcountry field guide, an observation reporting network, a forecast intelligence platform, or a multi-center operations system.
You don't need to know anything about avalanche safety going in — your AI assistant does, and learning the domain together is part of the experience.
What do I take home?¶
Working, deployed software that people can access in a browser. But more importantly: practical AI development skills you can use the day you get back to work — hands-on experience with professional AI workflows, a feel for how AI thinks, and the confidence to apply these patterns to your own projects.
How Teams Work¶
How big are the teams?¶
Four people per team. If the math doesn't work out perfectly, some teams may have an odd number — just pair up and make do with the people you've got.
Does everyone work at the same pace?¶
You'll read the trail guide content on your own screen, at your own pace — but you should keep your team at roughly the same pace. Our recommendation is to advance screen by screen together so everyone stays on the same page and you can answer questions as they come up. The trail guides have team activities built in, and those only work if the whole team is ready.
Your teammates will have different skill levels and backgrounds. That's intentional. Coach each other. If you understand something that a teammate is struggling with, take a few minutes to explain it. Teaching is one of the best ways to deepen your own understanding.
How should we collaborate during runs?¶
That's up to you. Some teams mob — everyone around one screen. Some pair up. Some divide and conquer. Experimenting with different collaboration styles is part of the learning.
The one rule: each run produces one deliverable per team. One demo, one repository, one product. How you get there is your call.
The Learning Journey¶
How do Lifts, Runs, and Reflections work together?¶
The Lift introduces a new skill. The Run puts you in a situation where you need that skill. The Reflection is where your team talks about what happened.
Here's what makes this different from most workshops: the challenges are intentionally designed so your team hits a wall. That wall is on purpose. The next lift gives you the exact tool to break through it. You feel the pain of not having a skill, and then you get it. That's how skills stick.
What about pacing?¶
Each lift-and-run pair is essentially one time block for your team. The time between them is flexible — if your team works through the lift quickly, start the run. If the lift takes a little longer, that's fine too. Work at your team's pace within that block.
What's not flexible is the reflection. The whole room comes back together to debrief as a cohort, so your team should be ready to regroup when the reflection starts. And don't jump ahead to the next lift — the cohort moves through lifts together, and the design only works if everyone is in the same place. If you finish a run early, pursue the stretch goals at the bottom of each run instead.
Your team CAN work outside of Impact Lab hours if you're excited and want to keep building, but it's not required. If you do, stick with your team so everyone continues to learn together.
Do we have to stay in our assigned room?¶
During lifts and runs, your team is free to break off and work wherever you'd like — a lobby, a lounge, outside, wherever you focus best. Just be back in the room by reflection time so you can be part of the group discussion.
One tradeoff to keep in mind: Ski Instructors and technical support circulate through the cohort rooms. If your team is working somewhere else, you won't have that support coming to you. Your AI assistant still travels with you, though.
What if we're falling behind?¶
That's okay. The goal is learning, not finishing. Understanding what you built and why it works matters more than checking every box.
Focus on the baseline capabilities. Skip the stretch goals. Ask for help. And show yourselves some kindness — you're learning new skills, and that's genuinely hard.
Your AI Assistant¶
Should I ask my AI assistant before asking a person?¶
Yes. Your AI assistant likely knows more about the topics you'll encounter than anyone at the conference — technical questions, domain questions, debugging, avalanche science, whatever. Start by asking your AI assistant.
This is about building muscle memory for a new way of working. When you get back to your job next week, your AI assistant will still be there. The support staff at Ship Summit won't be. If you flag down a ski instructor, the first thing they'll ask is: "Did you ask your AI assistant?"
What's wrong with copy-pasting a huge prompt to build everything at once?¶
It won't teach you anything. We call this one-shotting — dumping a massive prompt into AI and accepting whatever comes back. You'll get output, but you won't understand it, and you won't develop judgment for when AI nails it versus when it needs a nudge.
The value is in the back-and-forth. Work in small chunks. Send a prompt. Look at what comes back. Give specific feedback. That cycle — prompt, evaluate, refine — is the skill that transfers to everything you'll do with AI after this event. The lifts will teach you how.
Getting Help¶
Where do I go when I'm stuck?¶
Three layers of support, in this order:
- Ask your AI assistant. Describe your problem clearly. Your AI assistant is remarkably good at diagnosing issues, suggesting approaches, and explaining concepts. Build this habit.
- Ask your ski instructor. Your ski instructor is the captain of your cohort — part coach, part facilitator, part timekeeper. If your AI assistant can't crack it, they're there for exactly this.
- Go to Basecamp. If your ski instructor thinks it's a technical issue or something a vendor can help with, they may point you to Basecamp — the on-site support area staffed by technical specialists and vendor partners.
The only wrong move is sitting stuck in silence.
Mindset¶
Is this a competition?¶
On Day 3, each cohort votes on the best team demos, and winning teams present to the full conference. That's real, and it's worth going for.
But the team that wins won't be the team that built the most — it'll be the team that grew the most and did something meaningful. The Impact Lab is a learning experience, not a delivery race. A team that builds one well-understood feature has gotten more out of this than a team that one-shots a huge app they can't explain.
What if I'm struggling?¶
Good. That means you're learning. Working with AI in a structured way involves a real learning curve. You will get confused. You will get frustrated. You will wonder why the team next to you seems to have it all figured out. (They don't.)
Show kindness — to yourself and to your teammates. Celebrate small wins. Ask for help. Remember that the real deliverable isn't the software — it's the skill set you're developing and the habits you're forming.