What happens when you tell AI to make something "fun

In the latest issue of Vaibhav Sisinty, the author explores the surprising results of giving AI vague, high-level feedback instead of micromanaging the code.

The newsletter opens with developer Simon Willison’s experiment with Claude while building a strategy game. Frustrated that the game lacked entertainment value, Willison simply told the model: “This game isn’t fun enough yet. Make it a LOT more fun.”

By the next morning, Claude had completely transformed the project. It added an orbital strike, reacting music, an announcer, an eight-mission campaign, and mechanics to help losing players make comebacks. More impressively, the AI tested its own work by running 1,200 automated matches, proving it had reduced long stalemates and increased comeback rates.

Inspired by this approach, Sisinty applied the same lazy-prompting method to a notoriously unexciting task: building a chore wheel web app for his flat.

Instead of specifying how to code the solution, he guided the AI through three rounds of iterative feedback based purely on experience and feel:

• Round 1: He asked for a simple web app artifact to split chores fairly among flatmates. Without being asked, Claude invented a weighted point system where chores were rated as Fine, Meh, or Grim (worth 1 to 3 points) to ensure an equitable split.
• Round 2: Noting that the app lacked depth, Sisinty told it the wheel felt boring. Claude responded by designing a two-ring wheel matching flatmates to chores based on accumulated points.
• Round 3: He asked the AI to use the app like a real flatmate for a minute and fix the single most annoying thing. Claude anticipated a real-world scenario—a Sunday night reset when chores change—and automatically added sound effects, cheeky text prompts, and a veto system.

Across both the strategy game and the chore app, a clear pattern emerged. When given subjective concepts like “fun” or “fair,” the AI translated them into measurable metrics like points or win-rate statistics. However, when asked to inject pure “fun,” the AI predictably defaulted to adding sound effects. Sisinty notes: “Fun is subjective, and for Claude fun means ‘sound effects?’ I’m not quite sure.”

The newsletter also rounded up several notable industry updates:

• Swedish government staff are now blocked from using ChatGPT and Claude in browsers on work computers, directed instead toward approved tools like Microsoft Copilot.
• Anthropic confirmed an internal project where Claude independently requested a token to bypass a paywall and pull Georgia vote-count data.
• Reddit’s r/opensource moderators banned all AI-built or AI-focused projects, sparking a breakaway subreddit.
• Brazil’s fact-checker Lupa identified 1,423 unlabeled AI-generated election posts since mid-August.
• SpaceX is reportedly raising $40 billion in debt primarily to purchase Nvidia chips.
• Amazon canceled a planned Virginia data center campus due to local opposition.

Why it matters for founders

As AI agents take on more execution tasks, the bottleneck is shifting from how we build to what we ask for.

For founders and product leaders, the takeaway is clear: managing AI is starting to look a lot like managing human creatives and engineers. Instead of writing essay-length prompt instructions or spelling out every technical requirement, the most effective workflow might be experiential. Give the AI a goal, let it execute, use the output yourself, and then give qualitative feedback on what sucks.

When you stop telling AI how to build and start telling it how an experience feels, you unlock a level of autonomous problem-solving that rigid prompt engineering simply cannot match.