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Dalton + MichaelDalton + Michael

Slop vs Craft

As AI tools become increasingly powerful, its easy to output a lot more output... but that doesn't mean the output is good. In this episode of Dalton + Michael, the two discuss the temptation of using the tools to create low quality software/content/startup ideas. They mention some case studies from the past, including SEO content farms as well as the risk of building a "turkey startup." There is also a higher risk for founders that being able to output reasonably sloppy prototypes has the side effect pushing more startups into pivot hell. Having high standards for what you put out in the world is a great signal for what good "taste" looks like. The way to win in a slop war is to not play, and to instead use these new tools to help solve problems for your customers better than anyone else. If you would like to see the "turkey graph" for yourself, here it is: https://x.com/paultoo/status/2028601344534454598 Dalton + Michael is brought to you by @Standard_Cap Dalton Caldwell on X: https://x.com/daltonc Michael Seibel on X: https://x.com/mwseibel

Dalton CaldwellhostMichael Seibelhost
Mar 1, 202618mWatch on YouTube ↗

At a glance

WHAT IT’S REALLY ABOUT

Avoid the slop war: build craft, retention, and real user value

  1. They define slop as products that look good in demos, fundraising, or top-line graphs but fail to solve users’ problems or create lasting satisfaction.
  2. They argue powerful tools like Claude Code can accelerate slop by making it easy to ship lots of features and plausible prototypes without conviction or user value.
  3. They use historical cycles—SEO content farms, early App Store junk, and parts of crypto/ICOs—to show slop can create short-term gains but typically ends as a “turkey startup” when platforms or incentives shift.
  4. They frame “taste” as honest judgment and high standards: resisting self-deception, prioritizing positive-sum value creation, and being proud to put your name on the work.
  5. They recommend avoiding symmetric “spam harder” arms races and instead winning by focusing on retention, real utility, and the hard-to-fake metrics that reflect genuine user benefit.

IDEAS WORTH REMEMBERING

5 ideas

Don’t enter a symmetric “slop harder” arms race.

If competitors are spamming features/content to juice graphs, matching them drives you toward garbage output and fragile growth; find a strategy that avoids competing purely on volume and manipulation.

Slop is often recognizable if you stop self-deceiving.

After rest or outside feedback, you usually “know” the work isn’t that good; craft requires the discipline to acknowledge that and raise the bar rather than pile on more features.

Use the competitor’s product before fearing it.

Fundraising buzz and external signals are misleading—actually trying the product is the fastest way to assess whether it delivers real user value or is mostly hype/slop.

Top-line graphs can be gamed; retention forces reality.

Push notifications, deceptive emails, and dark patterns can inflate DAUs or revenue short-term, but retention work starts with: is the product truly helping and do users feel that value?

Platform-gaming slop creates “turkey startups.”

SEO farms, early App Store gimmicks, and many crypto plays can look like they’re “winning” early, but collapse when algorithms, policies, or market sentiment change.

WORDS WORTH SAVING

5 quotes

You wanna stay out of a symmetric battle for who can slop harder.

— Dalton Caldwell

Slop is products that don't actually help the user.

— Michael Seibel

Slop is where you're sort of actively self-deceiving that your thing is good when you kinda know it's not that good.

— Dalton Caldwell

In the first 10% of the race, you look like you're winning... you can sometimes just forget that you have 90% of the race to run.

— Michael Seibel

Graphs that go up where no value is created, come down. They've, they have a life of a turkey.

— Michael Seibel

Definition of slop vs craftClaude Code/vibe coding as an accelerantSelf-deception and honest product judgmentSEO spam farms and platform gamingEarly App Store gimmicks and dark patternsCrypto/ICOs and incentive-driven low-quality outputRetention vs top-line growth metrics (DAUs, revenue, graphs)Pivot hell and low-conviction iteration

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