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A rules-based pattern is emerging for helping agentic workflows produce better results. Examples include GreatScottyMac’s RooFlow and, Geoff Huntley’s specs and stdlib approaches.
Brendan Humphrey on Vibe Coding, aligns with my own thinking on vibe coding:
…these tools must be carefully supervised by skilled engineers, particularly for production tasks. Engineers need to guide, assess, correct, and ultimately own the output as if they had written every line themselves.
Smashing Create PR with vibe coding output amounts to an attack on the PR process:
Generating vast amounts of code from single prompts effectively DoS attacks reviewers, overwhelming their capacity for meaningful assessment
But there is still some value:
Currently we see one narrow use case where vibe coding is exciting: spikes, proofs of concept, and prototypes. These are always throwaway code. LLM-assisted generation offers enormous value in rapidly testing and validating ideas with implementations we will ultimately discard.
GitHub Copilot: The agent awakens - Just when you thought it was Cursor/Claude Desktop/Roo/Cline, m$ reminds you they’ll eat your lunch.
The “First AI Software Engineer” Is Bungling the Vast Majority of Tasks It’s Asked to Do - It took longer than a human, and failed at the vast majority of tasks.
Out of 20 tasks we attempted, we saw 14 failures, three inconclusive results, and just three successes,” the researchers found — a meager success rate of just 15 percent.
Today we’re excited to introduce Devin, the first AI software engineer.
Devin is an autonomous agent that solves engineering tasks through the use of its own shell, code editor, and web browser.