Your AI Pair Programmer Needs a Workflow
And FAANG teams are already building them.
The gap between what AI can do and what we do with it is getting wider. The fix isn't a better model, it's a better playbook.
FAANG Teams Are 'Vibe Coding' 30% Faster Than You
The secret isn't a better AI, it's a better process
Engineers at FAANG are using a method called 'vibe coding' to develop 30% faster. It’s not about letting AI write production code unchecked. It’s a disciplined, seven-step process that turns high-level ideas into functional code through a structured conversation with an AI assistant.
This signals a fundamental shift in software engineering. AI acts as a force multiplier, handling boilerplate and initial drafts, which lets engineers focus on architecture, logic, and security. The most important skills are no longer just writing code, but prompt engineering and rigorous human oversight. The 'vibe' is this new, iterative feedback loop where the human guides the AI with precision.
This isn't plug-and-play; it requires a structured workflow and clear internal guidelines. For any team looking to get serious about AI, the lesson is clear: efficiency gains come from mastering the art of collaboration, not just installing the latest tool. It's time to build a process around your AI, not just throw prompts at it.
The New AI Command Line
The next wave of tools isn't just about AI magic; it's about building the practical interfaces and infrastructure to actually use it.
Grok 2.5 OSS: The open-source LLM with a 128K context window
xAI's open-source beast is here. Its massive 128K context window and radically lower cost make high-end custom AI feasible for teams without a FAANG budget.
VibeFlow: The low-code lovechild of n8n and Convex
A low-code platform turning prompts into full-stack apps. It aims to make backend logic visual and transparent, merging rapid prototyping with scalable architecture.
ChatGPT Marketing: Your new secret weapon for AI visibility
The next frontier of SEO is optimising for AI. This tool promises to align your brand's digital signals so you become ChatGPT's favourite answer.
The Aesthetic Layer
As the backend gets smarter, the pressure is on for the frontend to be more than just functional—it has to be an experience.
Pixxel: Your screenshots deserve to be styled, not scrolled past
A free Chrome extension for styling screenshots. It instantly adds rounded corners, shadows, and custom backgrounds, turning boring captures into professional assets.
KiForm: A form builder that aims for a beautiful UX
This form builder bets on a beautiful user experience to increase completion rates. It's challenging the clunky incumbents by focusing on speed, simplicity, and design.
RetroUI Pro: Ditch the design monotony with neo-brutalism
A UI kit for React and Figma that embraces neo-brutalism. It's a deliberate rejection of minimalist sameness, offering a bold aesthetic for brands that refuse to blend in.
Quick hits
DevDiary.me: Your new coding GPS
This tool auto-documents your development journey, creating a searchable, personal knowledge base so you never lose a hard-won solution again.
Informed: Your news, your voice
This app uses AI to clone any voice you want to narrate your daily headlines, pushing content personalisation into wild new territory.
Branvia: Your small business's AI photo studio
It turns a single product photo into dozens of professional, stylistic variations, levelling the visual playing field for e-commerce.
My takeaway
The real bottleneck in AI adoption isn't the technology, it's our workflow.
We're seeing a flood of powerful tools that promise incredible capabilities. But as the FAANG 'vibe coding' process shows, without a disciplined human-in-the-loop system, these tools just generate sophisticated noise faster. The value isn't in the AI's first draft; it's in the structured collaboration that follows.
This forces us to redefine what a developer does, shifting focus from writing boilerplate to designing systems and asking the right questions. We need to stop asking 'What can this AI do?' and start designing the workflows that make what it does useful. The most successful teams will have the best human-AI process.
What's one repetitive task in your workflow you could systematise for an AI collaborator?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().