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The AI Question Product Teams Aren’t Asking: Can Customers Keep Up?
AI is making it easier than ever to build faster. Features ship overnight, prototypes spin up in hours, and suddenly everyone assumes experience and expertise are optional. But almost nobody's asking the harder question: what happens when you build faster than your customers can actually absorb?
Todd Blaquiere, Ryan Cantwell, and Joe Ghali dig into that gap. Customers still have the same limited ability to learn new workflows and adapt to constant change, regardless of how fast your team can ship. That mismatch is creating innovation fatigue and turning a lot of teams into feature factories, where velocity doesn't translate into value.
The conversation gets into what's actually driving this mismatch: customers still stuck learning your last release, too many things shipped at once with no clear priority, and poorly timed features that land when customers are already heads-down dealing with something else entirely. They also dig into what this means for product roles, including whether customer readiness is about to become a fourth element of product-market fit.
If your team is shipping more than ever but seeing less traction, the problem might not be what you're building. It might be when, and how fast. Pull up a chair and join the conversation on the porch.
Time Stamped Notes:
Introduction and Setting the Stage
[00:00] Customer absorption problem – Todd introduces customer absorption capacity as a new constraint.
[00:29] The central AI question – If AI lets us build faster, can customers keep up?
[01:25] A shifting constraint – Engineering speed is no longer the main bottleneck.
Challenges in Product Development
[02:35] Innovation fatigue – Features ship successfully but customers aren’t adopting them.
[03:13] Signs of overload – Enablement lags releases and customers ignore announcements.
[04:15] Why products fail – Traditional causes like poor discovery are revisited.
[05:28] Output vs value – More features don’t matter if customers can’t absorb them.
Understanding Customer Absorption
[06:18] Too much too fast – Customers struggle when releases pile up.
[07:47] Fire hose analogy – Shipping too quickly overwhelms users.
[08:13] Why adoption stalls – Customers still learning previous features.
[09:00] Bad timing – External pressures distract customers from new releases.
Role of AI and Product Management
[12:41] AI accelerates development – Prototyping and building happen faster than ever.
[15:45] Absorption vs adoption – True value comes when features become part of workflows.
[18:49] Empathy and readiness – Teams must consider customers’ capacity for change.
[21:09] Development shrinks – Coding becomes the smallest part of the product process.
Future of Product Management Roles
[23:54] Roles converge – PM, UX, and engineering responsibilities begin blending.
[25:29] Engineers and product thinking – Engineers take on more ownership.
[28:23] Tech debt risk – Faster shipping may increase technical debt.
[31:08] Faster expectations – Customers expect quicker responses to feedback.
[32:11] Role risk debate – The team discusses which roles may shrink or evolve.
[36:36] A new focus – Product teams must optimize for absorbed value.
Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch
Join our email list and never miss an episode at theproductporch.com
View all episodes
By Ryan Cantwell, Todd Blaquiere, Joe GhaliAI is making it easier than ever to build faster. Features ship overnight, prototypes spin up in hours, and suddenly everyone assumes experience and expertise are optional. But almost nobody's asking the harder question: what happens when you build faster than your customers can actually absorb?
Todd Blaquiere, Ryan Cantwell, and Joe Ghali dig into that gap. Customers still have the same limited ability to learn new workflows and adapt to constant change, regardless of how fast your team can ship. That mismatch is creating innovation fatigue and turning a lot of teams into feature factories, where velocity doesn't translate into value.
The conversation gets into what's actually driving this mismatch: customers still stuck learning your last release, too many things shipped at once with no clear priority, and poorly timed features that land when customers are already heads-down dealing with something else entirely. They also dig into what this means for product roles, including whether customer readiness is about to become a fourth element of product-market fit.
If your team is shipping more than ever but seeing less traction, the problem might not be what you're building. It might be when, and how fast. Pull up a chair and join the conversation on the porch.
Time Stamped Notes:
Introduction and Setting the Stage
[00:00] Customer absorption problem – Todd introduces customer absorption capacity as a new constraint.
[00:29] The central AI question – If AI lets us build faster, can customers keep up?
[01:25] A shifting constraint – Engineering speed is no longer the main bottleneck.
Challenges in Product Development
[02:35] Innovation fatigue – Features ship successfully but customers aren’t adopting them.
[03:13] Signs of overload – Enablement lags releases and customers ignore announcements.
[04:15] Why products fail – Traditional causes like poor discovery are revisited.
[05:28] Output vs value – More features don’t matter if customers can’t absorb them.
Understanding Customer Absorption
[06:18] Too much too fast – Customers struggle when releases pile up.
[07:47] Fire hose analogy – Shipping too quickly overwhelms users.
[08:13] Why adoption stalls – Customers still learning previous features.
[09:00] Bad timing – External pressures distract customers from new releases.
Role of AI and Product Management
[12:41] AI accelerates development – Prototyping and building happen faster than ever.
[15:45] Absorption vs adoption – True value comes when features become part of workflows.
[18:49] Empathy and readiness – Teams must consider customers’ capacity for change.
[21:09] Development shrinks – Coding becomes the smallest part of the product process.
Future of Product Management Roles
[23:54] Roles converge – PM, UX, and engineering responsibilities begin blending.
[25:29] Engineers and product thinking – Engineers take on more ownership.
[28:23] Tech debt risk – Faster shipping may increase technical debt.
[31:08] Faster expectations – Customers expect quicker responses to feedback.
[32:11] Role risk debate – The team discusses which roles may shrink or evolve.
[36:36] A new focus – Product teams must optimize for absorbed value.
Help keep the Product Porch lights on by giving at https://www.patreon.com/TheProductPorch
Join our email list and never miss an episode at theproductporch.com