1. You’re not behind — you’re comparing outputs, not inputs

It’s easy to scroll LinkedIn and feel like everyone else has already automated their entire function. But Diane made a critical distinction: most teams are comparing outcomes without understanding the inputs required to get there.

For AI to truly unlock value, you need three things:

• A somewhat standardized process
• Clean, accessible data
• A consistent problem + consistent output

“How many areas of a startup truly have that trifecta of clear process, standardized data, and consistent output and frequency?”

Not many.

AI is often marketed as plug-and-play magic. But in reality, it thrives in structured environments. If your workflows are chaotic, your data is messy, and your output constantly changes, AI won’t save you — it will amplify the mess.

The takeaway: before chasing the latest model release, ask whether your inputs support the outcome you’re expecting.

2. Stop chasing the latest model. Solve today’s problem.

One of the most freeing insights from Diane: the newest AI release isn’t necessarily the one that solves your problem.

“There’s a difference between the tech that solves your pain and the latest tech.”

It’s easy to fall into the trap of constantly upgrading — new models, new agents, new copilots. But most organizations haven’t fully implemented what’s already available.

Instead of asking:
What’s the most cutting-edge tool?

Ask:
What business pain are we trying to solve right now?

Diane framed AI adoption more like kaizen — continuous improvement — rather than a one-time “AI implementation.” Your workflow today will evolve in three months. That’s not failure. That’s iteration.

The use case implemented today beats the perfect use case you’re still designing.

3. If you don’t know where to start, automate work chores

Diane introduced a simple prioritization lens: the Five Frictions framework. But if you’re short on time, here’s the shortcut:

Start with work chores.

These are the time-consuming, low-leverage tasks that:

• Drain cognitive energy
• Don’t require deep strategic thinking
• Often fall into the “rubber ball” category (drop it, and it bounces)

“Automate work chores first. Everyone will thank you. You will thank yourself.”

Work chores are powerful because:

• The ROI is obvious (time + energy savings)
• The risk is lower than experimenting on mission-critical systems
• They build momentum quickly

Instead of trying to “AI-ify” your entire function, find the repetitive tasks that make you sigh every time you open them.

That’s your starting point.

4. The best AI use cases are tied to real KPIs

One of Diane’s client examples stood out: a fast-scaling fintech company trying to reduce time-to-hire.

Rather than brainstorming random AI ideas, they anchored everything to a business goal.

They realized hiring managers were slowing down candidate feedback. So they built a simple GPT that:

• Took interview transcripts
• Allowed messy bullet points from hiring managers
• Transformed them into high-quality, legally compliant candidate feedback
• Drafted the email for recruiting to send

What used to take days of shoulder-tapping now took minutes.

The result:

• Faster time-to-hire
• Higher candidate experience
• Less friction between recruiting and hiring managers

“Build AI on something — not something on AI.”

That line stuck with us.

If you’re not tying AI to a KPI you’re already accountable for, you’re probably building theater — not leverage.

5. Click-cutters are the compounding interest of AI

Some of the most powerful wins aren’t flashy agents or dashboards. They’re what Diane calls “click cutters.”

These are tiny workflow improvements:

• Automatically converting transcripts to Google Docs
• Auto-filing documents into the right folders
• Reducing copy/paste steps
• Eliminating unnecessary tab switching

“Every little click is cognitive friction.”

It’s not just about saving time — it’s about preserving mental energy. The more micro-frictions you eliminate, the more strategic capacity you create.

Click cutters compound.

Individually, they seem small. Collectively, they change how your day feels.​

6. Bring the tech to the people — not the people to the tech

One of the most practical shifts we discussed: stop trying to force behavior change if you don’t have to.

Instead of:
“Go to Confluence to find the policy.”

Ask:
“How do we bring the policy to where people already work?”

That might mean:

• HRIS integrations inside Slack
• FAQ bots inside your primary communication tool
• Personalized dashboards pushed proactively to execs

“If people aren’t in the habit of going somewhere, it’s often hard to change that behavior. So remove the barrier entirely.”

AI enables hyper-personalized, in-context experiences. And when you reduce the friction between people and information, adoption skyrockets.

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