032 AI for Operators

Hi there, 

Welcome back to AI for Operators. Here’s what we’ve got for you this week:

• The Operator: Off this Week

• The Essay: The AI Despair Spiral (And How to Climb Out) by Diane Sadowski-Joseph

• The Jobs: Senior AI roles with salaries up to $260k

• The Links: 12 links, including MoltBot, how to create AI project managers, CFOs, and a GTM team, and management as an AI superpower

• The Events: Two new AI workshops to sign up for

(Brought to you by Diane Sadowski-Joseph Co-Founder of Clarinet)

I see companies getting stuck in the AI Despair Spiral when trying to adopt AI when these three things happen:

• AI Swirl — endless debates about which tools to use, where to start, what to prioritize. Round and round. Nothing ships.

• AI Slop — your team is producing more, but none of it's better. Managers drowning in outputs they can't QA fast enough.

• AI Debt — half-built automations, abandoned pilots, a graveyard of "we should revisit that" projects.

If you're stuck in this spiral, you're not alone. 75% of organizations are right there with you. (Source: Middle Market Center; AI Magazine (10/2025); Mckinsey)

The teams getting traction have flipped the spiral into a flywheel — a continuous cycle of building, learning, and scaling. Here's how:

BUILD: You don't have to DIY everything.

There's pressure to figure it all out yourself. Tutorials exist for everything. You can watch a webinar and AI can be your co-pilot!

But trying to learn how to do something while also trying to execute fast is a conflict of interest. And most AI-native teams? They have dedicated people whose job it is to build this stuff. That's the part nobody mentions.

It's hard to focus on renovation when the house is on fire. Sometimes the right move is paying someone to stand up a few proven workflows so your team has breathing room to learn.

LEARN: Prompt your humans, not just your AI.

The AI slop problem is both a tech issue to a delegation problem.

People can now generate five pages of content in 30 seconds - none of which works well. That means you have to be even clearer about outputs when you give a task to a human.

When you assign work to someone who'll use AI, specify three things: Who is this for? What decision should it enable? What does good look like?

Leadership exercise: Give AI the exact same instructions you'd give a person. If the output is rubbish, your delegation may need some work. 

SCALE: Shorten your planning cycles.

If you’ve ever gotten carsick you know the advice: focus on one spot in the distance. Don't watch things whipping by out the side window.

Same principle. You can't plan quarterly when the tools change monthly. Bi-monthly cadences make pivoting feel like steering, not whiplash.

Start scaling now: Pick one AI-related problem to solve in the next 60 days. Not three. One. It's better to have something done than a bunch of ideas that never leave the starting line.

About Diane and Clarinet: Diane is an AI adoption and organizational transformation leader who’s advised 50+ companies on AI adoption and trained 100,000+ professionals over her career. She speaks and writes on human–AI collaboration and responsible implementation, and previously helped scale LifeLabs Learning. She’s now Co-Founder and Head of Product at Clarinet, where she leads the company in partnering with organizations to learn, build, and scale with AI in high-ROI, human-friendly ways.

Some AI strategy and implementation roles that caught our eye:

Business Systems Architect, AI at Figma

• Lead design, implementation, and governance of AI-powered internal systems

• Comp: $149k - $260k

AI Strategy Lead at CollegeVine

• Partner with colleges and universities to deploy AI agents to streamline their operations

• Comp: Not listed

Senior Manager, AI Strategy at Autodesk

• Define Autodesk’s long-term AI strategy for AECO, partnering with product, research, and industry teams

• Comp: $148k - $239k