GTM in the Age of Enshitification

Have you noticed that your feeds, inboxes, and search results feel more crowded, but not more useful?

There is more content. There is more activity. There is more engagement. And there is, somehow, less of the thing you want.

There is a word for this feeling: enshitification. It is an objectively great word. Possibly the best word anyone has come up with in the last decade. But the dynamic it refers to is, as you might expect, shitty.

Roughly speaking, enshitification is what happens when systems that were supposed to serve you start serving something else instead. Often money. Often metrics. Often some PowerPoint slide labeled “engagement.”

AI did not invent enshitification. Humans were doing just fine on their own. But AI has made it cheaper, faster, and easier to enshitify anything digital. That is bad. But it is also, in a slightly perverse way, useful.

Because once you understand how enshitification works, you can respond to it deliberately instead of just vaguely resenting your inbox.

What Enshitification Actually Is

The term originally referred to a fairly specific pattern in platform businesses. You can think of it as a three-act play.

Act One. The platform is very nice to users. It is generous. It is helpful. It does what you want.

Act Two. The platform starts extracting value from users to benefit business customers. Ads increase. Friction appears. You are still mostly happy, but you notice things.

Act Three. The platform extracts value from everyone to benefit itself. You are no longer happy, but you are still there.

That definition still holds. But the interesting thing is that the same dynamic now shows up almost everywhere, even outside of platforms.

At the core is something simpler.

We want outcomes that are hard to measure. Things like relevance. Usefulness. Trust. Understanding. These are annoying concepts because they do not fit neatly into a dashboard. From a RevOps perspective, these are terrible KPIs. Zero stars. Would not recommend.

So instead we use proxies. Likes. Comments. Clicks. Opens. Watch time.

This is not a mistake. You cannot run an organization without metrics. The mistake comes later.

The problem starts when the proxy quietly stops being a signal and starts becoming the goal.This is Goodhart’s Law. When a measure becomes a target, it stops being a good measure. Not because anyone is evil, but because the system adapts.

Enshitification is what happens when systems optimize for what looks like value in a dashboard instead of the underlying value itself. The system is not broken. It is doing exactly what it was trained and incentivized to do.

Everyday Examples You Have Definitely Seen

Once you notice this pattern, it becomes hard to unsee. I apologize in advance for cursing you with Enshitification-Vision.

Social feeds. Comment to get the thing.

You have seen the post.

“I’ve put together a valuable resource. Comment ‘PLAYBOOK’ and I’ll send it to you.”

The stated goal is reasonable. Share something useful with the right audience.

The proxy is engagement. Comments signal interest. Algorithms reward comments.

Outbound links quietly reduce reach.

So the link is withheld. Engagement is forced. Sometimes the resource is fine. Usually it is forgettable.Feeds fill up with engagement theater. Trust erodes. Everyone understands what is happening. And yet the format spreads anyway, because it still works just well enough to justify itself.

MFA (Made-For-Advertising) websites.

In theory, a website exists to answer a question or solve a problem.

The proxy is traffic and ad revenue.

Made-for-advertising sites are engineered almost entirely around that proxy. Thin content. Rewrites of what already exists. Increasingly, AI-generated summaries that are just good enough to rank.

You get an answer. Technically. You do not feel informed. You feel like you skimmed something hollow.

Again, the proxy is satisfied. The goal is not.

Email. A communication tool that became a volume game.

Email was originally designed to let people communicate directly with other people.

The goal was simple. Send a message. Receive a response.

Then came spam.

The proxy became scale and deliverability. Opens. Clicks. Response rates. Over time, inboxes filled with messages that were technically relevant, occasionally personalized, and largely ignorable. Personalized in the sense that it knows your first name and job title, but not why you might care.

The experience degraded so consistently that entire industries sprang up to filter, block, and route around the mess. Promotions tabs. Spam filters. Cold email folders.

Just like with social feeds, the audience didn’t leave email. They adapted. And the system kept working, just well enough, to encourage more volume rather than better communication.

Why Marketing and Sales Fall Into This So Easily

Marketing and sales are governed almost entirely by proxies.

Teams are rarely rewarded for clarity, trust, or genuine understanding. They are rewarded for open rates, CTR, MQLs, and pipeline volume.

Optimizing for those metrics is not a moral failure. It is rational behavior inside the system. Especially when someone has promised a board a number that needs to exist in about 90 days.

And opting out is rarely an option. Refusing does not fix the system. It mostly just makes you invisible.

AI Accelerates Enshitification

AI is a turbo enshitifier.

It makes proxy optimization cheaper, faster, and easier. Tactics that once required coordination and effort are now trivial to repeat.

That has predictable effects. Volume smooths variance. Patterned behavior spreads faster. The floor drops. Noise increases.

Importantly, this doesn’t mean the game disappears. It usually gets shittier while remaining economically relevant. The audience doesn’t leave just because the experience degrades.

So the system continues. Not because it’s good, but because it still works well enough.

What AI changes is not the existence of enshitification, but the speed at which it compounds.

Fortunately, the same robots that helped make this mess are also very good at cleaning up parts of it. Make of that what you will.

How to Cope with Enshitification

1. Align proxies to the real objective. Write the objective in plain language. Put it next to the metric everywhere it appears. Treat the proxy as a reminder, not a substitute.

2. Constantly reevaluate proxies. Proxies decay. AI can also create better ones. An MQL used to be a form fill and a few firmographic fields. Today, AI can enrich leads with real-world context and intent.

3. Use AI to play the bad games efficiently. This is not an endorsement of AI slop. It is an argument for containment.Email is a good example. Automated prospecting and personalized outreach can help you play the shitty email game more efficiently. They can handle enrichment, research, first drafts, and follow-ups at a fraction of the cost.That doesn’t make email good again. But it does mean you don’t have to spend your best human time grinding away in a degraded channel.Capture the remaining value (which is still significant) with minimal effort. Do not spend your best thinking on degraded tactics.

4. Reinvest saved time in better games. If AI saves time, do not immediately remove it from the plan. Use it to explore what you would do if your core channels stopped working. Robots are good brainstorming partners for this kind of thing. Spend time answering that question before you are forced to.

5. Return to first principles. What problem are you solving. For whom. And why they should care.

A More Useful Way to Look at Your Own Work

Enshitification is not a moral failing. It is a predictable outcome of optimizing imperfect proxies.

AI makes this dynamic faster and harder to ignore.

The interesting question is not whether you are participating. You almost certainly are.

The interesting question is which parts of your work are driven by proxies, and which parts still aim at real value.

And that is usually where a better GTM starts.