Coach Shawn

This is been a pretty cool week for me. I had the opportunity to do two really fun and interesting discussions with fun and interesting people!

First, I was a guest on Business RadioX - North Fulton where I managed to tie Lego, Lean and Jeff Foxworthy together :) Check it out here: https://businessradiox.com/podcast/northfulton/shawn-yates-on-smarter-processes-and-team-building/

Then, I did a LinkedIn Live with Tricia Warren where we talked about things companies need to get order BEFORE they start their AI journey. We had technical issues on this, so jump to minute 6 to get the goods :) This one is here: https://www.linkedin.com/video/live/urn:li:ugcPost:7379546189819432961/

Both were so exiting! Listen in and let me know what you think!!

� If your team’s boldest “innovation” is changing the status slide color, you might not be ready for AI.

Safe tweaks won’t move the competitive needle. And with AI, your competition is going to innovate even faster. AI magnifies the creativity of teams that explore, test, and learn in fast cycles. If new ideas die in committee or get watered down to “more of the same,” you’ll miss real upside of implementing AI.

Create space to experiment: small bets, short cycles, clear measurable success criteria, and permission to learn from misses without blame.

What I’ve seen work: Quick ideation jams (aka hackathons), creative techniques and processes to unlock fresh thinking, lightweight pilots with a 2–4 week window, and demos that show outcomes—not just updates. Reward the attempt, not just the win.

Ready to spark real innovation instead of slide makeovers? Drop a comment or DM.

This is 9 of 10 in the series! Missed earlier ones? Subscribe at www.predaxis.com and I’ll send all 10 in one issue.

Also I will be following this series up with a LinkedIn Live event to let you ask questions: https://www.linkedin.com/events/doyouthinkyourteamisreadyforai7373514507379167232/theater/

� If success metrics are “we’ll know it when we see it,” you might not be ready for AI.

AI can solve a wide range of problems. You need to be clear on what you are trying to achieve before you get started.

If outcomes aren’t defined, every shiny object and flashy demo “looks good." But in the end, you won't know if you got where you wanted to go. You could even end up with a bigger mess problem than before you started on your meandering AI path.

Set the target before you start looking at products and demos. Define 1–3 measurable outcomes, capture a baseline, and set a time window. Align on what “good” looks like as you start your journey.

What I’ve seen work: Clear problem statement, baseline data, a simple KPI tree (leading + lagging), and ongoing checks that drive decisions. If the metric doesn’t move, adjust the implementation path, not the slide.

Ready to turn vibes into visible wins? Drop a comment or DM.

This is 10 of 10 in the series! Want all posts in one place? Subscribe at www.predaxis.com and I will send them all out in one article.

Also I will be following this series up with a LinkedIn Live event on Oct 1 to let you ask questions: https://www.linkedin.com/events/doyouthinkyourteamisreadyforai7373514507379167232/theater/

� If your leaders think “Agile” means going faster, you might not be ready for AI.

Speed without learning is burnout. Agile isn’t about faster and harder, it’s about adapting, testing ideas in small slices, and delivering value step by step. If “go faster” is the plan, AI will only crank the treadmill.

Build real agility, the ability to bend and change, first: outcomes over output, short feedback loops, and room to experiment (and fail) without blame. Make it safe to pivot when data says so.

What I’ve seen work: Pilot sprints with a clear problem statement, tight success metrics, demo early/often, and retros that change how you work next week—not next year. Leaders model curiosity and protect focus rather than go on witch hunts when something goes wrong.

Want help shifting from “faster” to “smarter”? Drop a comment or DM.

This is 8 of 10 in the series! Missed earlier ones? Subscribe at www.predaxis.com and I’ll send all 10 in one issue.

Also I will be following this series up with a LinkedIn Live event to let you ask questions: https://www.linkedin.com/events/doyouthinkyourteamisreadyforai7373514507379167232/theater/

🛡️ If feedback is scarier than a first date, you might not be ready for AI.

AI accelerates learning and discover cycles. It thrives best where teams learn fast. If people are afraid to speak up, challenge assumptions, or share misses, that’s a big red flag.

You’ll miss patterns, repeat mistakes, and stall out.

Build the safety first: make feedback normal, not risky. Teach leaders how to give and receive it, and use simple, regular cadences so it’s part of the work—not a special event.

What I’ve seen work: Psychological safety habits (leaders go first), short retro after key moments, clear action owners, and closing the loop so people see their input change the system.

Ready to turn feedback into fuel? Drop a comment or DM.

This is 7 of 10 in the series! Missed earlier ones? Subscribe at www.predaxis.com and I’ll send all 10 in one issue.

Also I will be following this series up with a LinkedIn Live event to let you ask questions: https://www.linkedin.com/events/doyouthinkyourteamisreadyforai7373514507379167232/theater/

If your team's favorite problem-solving method is 'just work harder,' you might not be ready for AI.

Brute force isn't a problem solving strategy.

If the fix is always longer hours and heroics, that's a problem. AI is about working smarter, spotting patterns, preventing issues, and improving flow. If you're pushing harder instead of improving the system, AI will only amplify the grind.

Build the habit of improvement first: run small experiments, learn fast, and fix root causes' not symptoms. Make it normal to change the approach, the process and the work itself. Not just doing more of of the same.

What I've seen work: Kaizen-style tweaks, time-boxed experiments, visible metrics, and simple tools like 5 Whys or a quick fishbone to find the real cause. Celebrate learning and make it safe to try better ways - which means making it safe to fail.

Ready to swap hustle culture for smarter systems? Drop a comment or DM.

This is 6 of 10 in the series! Missed earlier ones? Subscribe at www.predaxis.com and I'll send all 10 in one issue.

Also I will be following this series up with a LinkedIn Live event where Tricia Warren and I dive a little deeper into these topics. More details to come in the next day or two!

🤹‍♂️ If “collaboration” means forwarding files around, you might not be ready for AI.

If your team’s idea of working together is an endless game of “who has the latest version” or tag-you’re-it-by-email, you’re not ready for the next level. AI feeds on clean, real-time data. Manual handoffs and disconnected tools just create a big ol’ mess that needs to be sorted out. 🚩

You need truly shared spaces: a single source of truth where updates happen in real time, everyone’s on the same page, and friction disappears. That’s when collaboration turns into progress, and AI can finally lend a hand by tapping into the known authoritative information.

What I’ve seen work: Shared digital workspaces (Google Workspace, MS Teams), regular alignment huddles, and actually ditching the version-8-final-FINAL.xlsx madness for good. Really, it may seem like overkill, but having naming standards as well as folder structure standards will make your life, and your journey to AI, much smoother.
And when the whole team can see what’s happening—boom, the magic starts.

Ready to move from spreadsheet chaos to true teamwork? Drop a comment or DM!

This is 5 of 10 in the series! Missed earlier ones? Subscribe at www.predaxis.com and I’ll send all 10 in one issue.

Also note that I will post the last 5 starting next Monday. Enjoy your weekend!

🔥 If your employees spend more time fixing mistakes than creating value, you might not be ready for AI.

If the team's daily ritual is chasing errors and cleaning up yesterday’s mess, pause the AI hype train for a sec, you're headed for a crash.

AI is basically a supercharger… for whatever system you’ve got. If what you’ve got is poor quality, guess what you’ll get? Poor quality at breakneck speeds.

First you need systems that work and turn out quality. Root out the bottlenecks, errors and overlooked checks. Set up good habits, and let people focus on building, not firefighting. Get your house in order, and only then think about adding AI to turbo charge the mix.

What I’ve seen work: Classic root cause analysis (5 Whys, fishbone, fault analysis), iron-clad standard work, and continuous improvement cycles where every small win frees people up for bigger things. The real magic? Involving the people who do the work they know where the fires start.

Ready to stop fighting fires and start building something better? Let’s talk.

This is 4 of 10 in the series! Missed one? Subscribe at www.predaxis.com and I’ll send all 10 in one issue.

🗺️ If your process map is a blurry whiteboard from 2017, you might not be ready for AI.

If nobody on your team can actually read your “official” process, you’re flying blind. And if you’re thinking about AI, that’s a big 🚩.

You need to know what your actual process is for AI to help you with it. AI needs clear, up-to-date maps to navigate your world. If everything’s living on a dusty old whiteboard? Good luck trying to automate anything.

You’ve got to bring those processes into the light: map them out with your team, make them digital, and keep them updated. When everyone can see (and actually understand) the workflow, suddenly, improvements and automation are possible.

What I’ve seen work: Value stream mapping sessions, digital process charts (Miro, Lucidchart, my favorite - nVeris), and simple sticky-note workshops where people actually own their part. And, the people in the workshop should be the ones who do the work!

Want help flipping that faded whiteboard into a map your team and your AI can use? Let’s talk!

This is 3 of 10 in the series! Missed one? Subscribe at www.predaxis.com and I’ll send all 10 in one issue.

🚧 If every decision needs eight signatures and a meeting to schedule the next meeting, you might not be ready for AI.

Let’s be honest, if your company runs on approval chains longer than a CVS receipt, you’re not alone.

But it’s still a 🚩 if you’re eyeing AI. AI only works as fast as your slowest bottleneck. If decisions are buried under red tape and endless calendar invites, you can’t keep up with the pace of change AI will bring.

You need to clear the runway: Give your people real authority to make decisions. Get crystal clear about who owns what. Then, use frameworks accountability charts, RACI and Agile ceremonies to keep approvals tight and feedback flying.

What I’ve seen work: Teams taking ownership, clear decision rights, and demo's that actually show progress and gather input. When folks feel empowered, everything speeds up and that’s when AI can help you soar instead of stall.

Ready to cut through the tangle and unleash your team? Drop a comment or message me!

This is 2 of 10 in the series! Missed one? Subscribe to my newsletter on www.predaxis.com and I’ll send the whole batch in one issue at the end 🔗

🚦 If your team still uses email as a to-do list, then you might not be ready for AI.

Seriously, if your biggest project management tool is “forward this to the team,” you’re not ready. You're also note alone (we’ve all been there). But it’s a 🚩 if you’re dreaming about AI.

Why? Because AI LOVES structure. When tasks live in endless email threads, things get missed, people spin their wheels, and automation? Forget it.

You have to get the tasks (aka data) somewhere central where everyone, including your new AI, can access it.

What I’ve seen work: On the simple side you have digital Kanban boards like Trello and Kanban flow. On the more comprehensive site you have whole workflow management systems like Jira and Rally.

Either way you are creating workflow transparency. When teams can actually SEE the work, everything gets faster—and THAT’s your foundation for AI wins.

Curious how to make that leap from inbox chaos to Kanban clarity? Drop a comment or DM!

This 1 of 10 in a series, if you miss the others, subscribe to my newsletter at www.predaxis.com - I will send all 10 in one issue at the end.

"If you have ever you use a fishing license as a form of I.D. you might be a red neck" ~Jeff Foxworthy

Am I dating myself be referencing Jeff Foxworthy? Oh well :)

I am going to share 10 "If you .... then YOU might not be ready for AI" statements over 10 days.

Everyone’s talking about AI, but here’s the truth: not every company is ready to get real value from it yet. Implementing AI without the right foundation can make things MUCH worse and be an expensive mistake

Over the next 10 days, I’m sharing a daily series inspired by Jeff Foxworthy’s “If you…” jokes, but with a leadership twist:

Each post will spotlight a common warning sign (and a little humor) that your organization may have some groundwork to lay before diving into AI, automation, or advanced tech.

I’ll also share practical things I have seen work so you can take steps to get your team, processes, and leadership truly AI-ready.

Whether you’re a tech leader, business owner, or just curious about what it really takes to make AI work, you won’t want to miss this!

Follow along, join the conversation, and get ready for some honest insights (and maybe a few laughs). First on Monday 9/8.