Is the AI spending spree about to come back and bite product managers? Companies are encouraging teams to experiment with AI, but who's keeping track of the costs, and is all that investment paying off? In this episode, Joe Ghali, Todd Blaquiere, and Ryan Cantwell dig into the hidden costs of AI, why promised productivity gains don't always translate into business value, and what happens when the CFO starts asking tough questions about AI ROI. We also discuss how product managers can balance experimentation with financial responsibility without putting the brakes on innovation.

Before the AI bill comes due, pull up a chair on the porch and find out how to make sure your AI investments are worth it.

The AI Reckoning: What's Coming?
[02:16] Why growing AI adoption could lead to some uncomfortable financial surprises.
[03:16] Early warning signs that companies may be losing control of AI spending.
[04:11] Five hidden AI costs that could catch organizations off guard.
[07:27] Have product managers forgotten how to account for the costs of technology?

AI Costs and Financial Accountability
[09:31] Why treating AI as overhead can hide its impact on product profitability.
[10:18] How AI usage costs should influence the pricing of customer-facing products.
[11:26] What previous technology revolutions can teach us about the AI boom.
[12:33] Why managing AI expenses may require lessons from cloud cost management.

The Pressure to Experiment
[13:08] How pressure to experiment can encourage AI investments without clear outcomes.
[14:25] Why product leaders are watching consumption costs and potential price increases.
[16:19] Which AI expenses product managers should be responsible for managing.
[18:42] The tension between encouraging AI experimentation and controlling its costs.

Are AI Efficiency Gains Worth the Investment?
[21:13] How rapidly improving AI tools complicate investment decisions and experimentation.
[22:19] Why financial scrutiny could make us better product managers.
[23:20] How to justify human involvement and connect AI efficiency to business value.
[24:51] Why saving a few minutes doesn't always create meaningful productivity gains.

Preparing for the AI Reckoning
[26:15] Why AI adoption isn't an outcome and what product managers should measure instead.
[26:52] How product management fundamentals help justify AI investments and spending.
[27:38] Why experimenting with AI doesn't eliminate financial responsibility.

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Are you producing better work with AI, or just producing more polished garbage? In this episode of the Product Porch, we tackle AI slop, what it looks like, why it's so easy to miss, and how it can quietly undermine your credibility as a product manager. We explore how AI can shift work onto others, weaken critical thinking, and create a false sense of confidence in bad decisions.

If you're using AI to work faster but want to make sure you're still doing your best work, pull up a chair on the porch. It's time to clean up the slop.

What Is AI Slop, and Why Should You Care?
[02:13] Why polished AI-generated work can look impressive but lack real substance
[03:38] AI didn't invent bad work; it just made producing it faster
[05:08] Why AI makes poor-quality work harder to recognize

The Hidden Costs of AI Slop
[07:04] Are you really saving time or just passing work to someone else?
[08:09] The "meat proxy" problem: When humans become messengers between AI tools
[08:58] How relying on AI too much can weaken your product management skills
[11:16] Where AI can genuinely save time without replacing human judgment

Where AI Slop Shows Up in Product Management
[15:00] The danger of trusting AI output you don't know how to evaluate
[16:09] Why AI-generated product strategies can sound convincing but lack substance
[16:34] How hidden assumptions can lead to wildly inaccurate market research
[20:56] Why more documentation doesn't necessarily mean better product decisions

How to Recognize AI Slop Before It Hurts Your Credibility
[23:56] Excessive length is often the first warning sign of AI slop
[25:30] Watch for content that misses its audience or mixes conflicting messages
[27:26] Why your credibility suffers when you can't defend your own work
[29:06] If AI writes it, you're still responsible for reading every word
[30:11] Why AI-generated marketing copy often focuses on features instead of benefits

How to Fight Back Against AI Slop
[33:02] Better AI-generated product requirements start with better customer understanding
[37:24] Break big decisions into smaller steps that stakeholders can validate
[38:37] Establish clear rules for when human judgment needs to take over
[40:21] If you can't explain it simply, do you really understand it?
[41:34] Keep writing yourself to preserve your ability to recognize good work

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Join us on the porch for our series on Product Manager Power Skills. These are the skills that help good product managers become great ones. They stay valuable across tools, processes, and product types, and building them can help you grow your impact and your career.

How do you make progress when you don’t have all the answers? In this episode, Ryan Cantwell, Todd Blaquiere, and Joe Ghali explore comfort with ambiguity and why it’s a power skill product managers can develop. They talk through why uncertainty feels uncomfortable, how jumping to solutions creates a false sense of certainty, and what it takes to move forward when the problem and the path are still unclear.

The conversation gets practical with stories about unclear expectations, pressure to have every answer, and leadership moments that build or break trust. Ryan, Todd, and Joe explain how to turn “I don’t know” into a plan, identify the most important unknowns, and use tiny acts of discovery to decide what to do next. They also discuss how leaders can help their teams admit uncertainty without feeling unprepared.

If you want to feel more confident working through uncertainty, pull up a chair on the porch and identify one thing you could learn before choosing your next move.

Building Comfort with Ambiguity
[02:29] Prefer structure? Comfort with ambiguity is a skill you can learn
[05:07] Handling uncertainty doesn’t mean accepting chaos
[05:46] A clear goal helps when the path is unclear
[07:02] Unclear expectations may be what’s making you uncomfortable

Making Progress Without Every Answer
[08:40] Label assumptions before they become accepted facts
[09:11] Plan your next move without predicting the whole game
[13:27] Why feeling you should know everything holds you back
[16:03] Build confidence by finding the next question to answer

Avoiding False Certainty
[17:48] Show you’re prepared, even when you don’t know the answer
[19:44] A feature and a deadline won’t make the uncertainty disappear
[22:02] Don’t let discovery become an excuse to delay decisions
[22:22] Use customer and market context to find your bearings

Helping Teams Handle Uncertainty
[25:05] Say “I don’t know” without losing the room’s confidence
[25:33] Turn unexpected questions into opportunities to learn
[29:17] Is your response to uncertainty adding pressure or building trust?
[31:11] Help teams admit knowledge gaps by admitting your own

Turning Unknowns into Action
[32:28] Make unknowns visible so you can decide what needs attention
[32:54] Focus learning on the assumptions with the biggest consequences
[33:14] Share small discovery tasks instead of finding every answer yourself
[35:41] Build a discovery backlog to give learning direction and priorities

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