February 2, 2026
AI wrote it. You roasted it.
Applications where agents are first-class citizens
AI wrote it, AI reads it, humans argue: genius or slop
TLDR: A guide coauthored by an AI explains how apps can let agents do everything users can and turn prompts into features. The comments explode with snark—some call it “AI slop,” others see a legit blueprint—raising the big question: is this the future of software or just more AI hype?
The tech guide says: let smart software “agents” do everything you can do in an app. Instead of clicking buttons, you describe the outcome you want, and an AI loops through tools until it gets there. It’s coauthored by Dan Shipper and Claude (Anthropic’s AI), and it leans on “Claude Code,” which shows an AI can tackle complex tasks by trying, checking, and trying again. Translation: features aren’t hard-coded; they’re instructions. Sounds futuristic, right?
Cue the comment section chaos. One crowd rolls their eyes and yells “AI slop!”—basically calling it low-effort machine-written fluff. “Why read an article the ‘author’ didn’t write?” snaps one user, while another jokes they can get an AI to summarize an AI-written article about AI. The meta humor is strong: folks noticed the “coauthored by Claude” label sitting above a “read with Claude” button. It’s AI all the way down. Meanwhile, supporters argue this is a real blueprint: give agents the same powers as users, keep tools simple, and let prompts create “features” like a weekly review.
There’s even a cheeky name joke—“nominative determinism”—suggesting Shipper is literally “shipping” agent-first apps. Love it or hate it, the drama says as much as the guide: the future of software might be outcomes, not buttons, but the humans aren’t done arguing. Hacker News never disappoints.
Key Points
- •The guide proposes building agent-first applications where agents achieve outcomes via tools in iterative loops.
- •Reliability of agents is evidenced by Claude Code, which uses bash and file tools with an LLM to perform multi-step tasks autonomously.
- •Developers should ensure tool parity with the UI so any interface action can also be accomplished by the agent.
- •Tools should be atomic primitives; features are outcomes described in prompts, enabling changes via prompt edits rather than code refactoring.
- •Agent-native apps improve through accumulated context and prompt refinement, guided by iterative observation and addition of domain tools.