The Boring Infrastructure Phase
AI's magic trick is over. Now we build the plumbing.
We've all been impressed by AI's magic tricks. Now comes the boring, but essential, part: building the infrastructure to make it actually reliable.
AI Coding Assistants Finally Get a Memory
Shadcn's latest update is less about new components and more about giving your AI a brain that doesn't hallucinate.
AI coding assistants are brilliant goldfish. They have zero object permanence, treating every interaction as their first and forcing developers to constantly re-explain the entire context of a project. The new shadcn/ui CLI and MCP Server aims to fix this by giving AI a direct, accurate memory of your specific UI components, preventing it from hallucinating code that doesn't exist. It’s a huge step toward making AI a genuinely useful pair programmer.
This signals a much bigger shift in the industry. The initial amazement with generative AI's magic tricks is over, and the hard, boring work of building the plumbing has begun. We’re moving from prompting chatbots to building structured, reliable systems that give AI constrained, accurate knowledge. This isn't about replacing developers; it's about building tools that don't need constant adult supervision to be effective.
The real story is that making AI useful requires guardrails. For developers using shadcn, this means faster, more accurate frontend work. For the rest of us, it’s a pattern to watch: the future of AI isn't just about bigger models, but about creating specialised memories that make them practical for real-world jobs.
Your New AI Interns
A new wave of AI tools are less like creative partners and more like hyper-focused interns for specific, tedious jobs.
Plus AI Presentations API: Your automated presentation designer
Plus AI hooks directly into PowerPoint and Google Slides to generate entire presentations from a simple prompt or document. It’s aiming to kill the soul-crushing effort of slide design for good.
Net30: Your AI accounts payable clerk
This tool uses AI to find the most profitable way to pay vendor invoices by maximising card rewards and early payment discounts. It turns your accounts payable department into a secret profit centre.
Scaloom: Your automated Reddit marketer
Scaloom automates posting across multiple subreddits and uses an AI to reply to comments 24/7. It's a tool for scaling Reddit marketing without getting instantly banned.
AI-Powered Playgrounds
Beyond automating old jobs, AI is creating entirely new ways for people to build and personalise their digital world.
Nothing Playground: Vibe-code your phone's personality
This AI creator studio for Nothing phones lets you generate mini-apps and customise hardware features with text prompts. It’s a wild glimpse into a future of user-driven phone personalisation.
Tigsaw: Your website's AI architect
Tigsaw lets non-developers add AI-powered banners, forms, and other dynamic components to a website without writing code. Early reviews say it's promising but still a bit buggy.
X Auto Reply Assistant: An AI assistant for your X replies
This Chrome extension uses models like Claude and Llama 3.1 to generate natural, context-aware replies on X. It’s a specialised tool for anyone trying to manage a high volume of interactions.
Quick hits
Casio Moflin: Your new emotional support floof
A fluffy AI robot pet with evolving feelings, designed for cuddles and comfort when you need a hug without the vet bills.
LangLime: The Duolingo-killer for people who are serious
This app ditches the gamified tourist phrases for self-guided lessons on real-world texts, aiming for actual fluency over maintaining a streak.
Partisyn: Instagram for your PC build
Finally, you can tag every single component in your gaming rig with interactive dots instead of typing a novel in the comments.
My takeaway
The real work in AI isn't building the models, it's building the memory.
We're seeing a pivot from general-purpose chatbots to specialised agents that have deep, persistent knowledge of a specific domain, like a design system or a company's finances. This is the only way they become reliable enough to automate real work. Without it, they're just clever toys that make impressive but untrustworthy suggestions.
This forces us to be more deliberate about what we want AI to know and, more importantly, what we want it to forget. It’s less about creating a superintelligence and more about creating a super-intern you only have to train once. The goal is no longer just intelligence, but reliable, context-aware performance.
What's the one tedious task you wish an AI with perfect memory could just handle for you?
Drop me a reply. Till next time, this is Louis, and you are reading Louis.log().