The Great AI Cleanup
AI's creating a mess, and people are getting rich fixing it.
The first wave of AI-powered startups is discovering a painful truth: moving fast with AI means breaking things in brand new ways.
AI-Generated Code Is Creating a Gold Rush for Human Developers
Startups that raced to build with AI are now paying top dollar for people to clean up the high-velocity mess.
The first wave of AI-powered startups is drowning in its own code. A developer on Reddit shared they were hired by a YC-backed company specifically to untangle its 'AI slop' – the messy, duplicated, and architecturally weak code generated at lightning speed by their team. This isn't an isolated incident; it's the beginning of a market for human developers who specialise in cleaning up after their AI copilots.
The real story here is that AI optimises for the immediate prompt, not long-term maintainability. It delivers functional code without architectural foresight, rapidly accumulating a technical debt that can cripple a young company. This creates a powerful demand for human craftsmanship – the ability to see the bigger picture, refactor duplicated logic, and impose a coherent structure on AI's chaotic but prolific output. We are seeing the birth of the AI-slop consultant.
This isn't an anti-AI story, it's about a new, necessary symbiosis. The workflow is shifting from pure human coding to AI-led generation followed by intense human refinement. The most valuable skill is no longer just writing code from scratch, but knowing how to expertly edit, audit, and architect the firehose of AI-generated solutions.
The New Hiring Playbook
We're finally moving past resumes and vibes to what actually matters: verifiable proof of work.
GitHired: Ditch the resume, analyse the code.
Stop guessing if a developer can code and start seeing if they can build. GitHired throws out the resume and analyses a candidate's actual GitHub contributions to rank their skills.
Stop 'Vibe Hiring' Your Developers: How to hire developers who actually build.
The smartest founders are skipping vibe checks and using a 'production diagnostic' instead. Give candidates a small, real-world project to prove they can ship, not just talk.
Your Tools Are Getting Smarter
AI is moving from a novelty to a utility, solving specific problems with focused, elegant tools.
Typeless for iOS: An AI ghostwriter that lives in your keyboard.
This isn't just dictation, it's an intelligent keyboard that removes your 'ums' and 'ahs' and refines your rambling into polished text. Crucially, all processing happens on-device, so your thoughts remain yours.
Voice Studio Companion: Drag-and-drop AI voiceovers for your Mac.
This macOS app puts an AI voice actor in your menu bar, letting you generate high-quality voiceovers and drag them directly into your editing software. It leverages ElevenLabs' tech for broadcast-quality results in seconds.
The 'Explain to a Junior' Prompt: The simple prompt that unlocks deeper bug detection.
A simple prompt-"explain this code to a junior developer"-forces AI to shift from a superficial reviewer to a meticulous analyst. This framing uncovers hidden bugs, flawed logic, and edge cases that a standard review would miss.
Quick hits
A2UI: Finally, a safe way for your AI to 'draw' an interface.
Google released an open protocol that lets AI agents build rich, interactive UIs without executing risky code.
GitJin: A digital zen garden for your chaotic code.
Finally, a dashboard that declutters the GitHub homepage and loads at lightning speed by focusing only on what you actually need.
WalletWallet: Digitise your entire physical wallet, for good.
This brilliant, free tool turns any barcode for any loyalty or membership card into a pass for your Apple Wallet.
My takeaway
AI's true value isn't in generation, but in the new workflows it forces us to create.
We were promised a world where AI did the boring work, but it's creating a new kind of work: refining, integrating, and fixing its high-speed output. The most valuable professionals are not just using AI; they are building the systems to manage its chaos. This shift from pure generation to sophisticated refinement is where the real opportunities are emerging.
This is a massive opportunity hidden in plain sight. The friction AI creates is the signal pointing to the next valuable problem to solve. What process can you build to tame the chaos?
Where in your own work is AI creating more noise than signal?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().