Every few years, web creation gets a reset button. Today, we pushed it.
Vibe-coding — the AI-driven way to build by describing — has been fun to demo, but until now, it lacked a real engine underneath. Without infrastructure, it’s a sandbox, not a site.
Today, we’re launching Vibe for WordPress — an AI-native frontend builder running on WordPress’s battle-tested backend. Real hosting, real CMS, real ownership. From idea → AI builds → you launch.
In Today’s AI Simplified:
Founder’s Insight: The next leap in AI creation isn’t about flashier models, but foundations. This week, I share how turning experiments into infrastructure changed how we build.
AI News: MIT’s new SEAL framework puts AIs on “learning on their own”, moving us closer to self-improving models. Google introduced Gemini Enterprise, a new AI platform that unifies workplace tools and data. And OpenAI just partnered with Broadcom to build custom AI chips.
What’s New at 10Web: We just launched Vibe for WordPress — the first AI-native frontend builder powered by the full WordPress backend. It brings vibe-coding freedom to real infrastructure: prompt, refine, and launch. From idea to deployment, all in one flow.
Vibe-coding without real infrastructure is just a toy.
Vibe-coding is cool. I love it. It sets new standards of how web is built.
But without a solid, battle-tested backend, infrastructure and content management, it doesn’t ship. It demos.
That’s why there’s still a huge gap: 200M entrepreneurs, only ~20% have a website. The rest are stuck between “fun to try” and “hard to launch.”
Meanwhile, WordPress is a silent giant powering 43% of the web.
Battle-tested. Open. Flexible.
But building on it? That’s still reserved for devs, agencies, or those with serious patience.
We’re changing that today.
After months of building, breaking, and rebuilding, we’re launching Vibe for WordPress: an AI-native vibe-coding builder with a real backend engine.
Idea → AI builds → You shape by chatting → Launch with confidence.
MIT’s new SEAL (Self-Adapting Language Models) paper just dropped. This approach allows LLMs to improve themselves.
Instead of waiting for humans to fine-tune it, SEAL trains itself. It writes its own “study notes,” tests the updates, and keeps only what works. The loop repeats until the model actually learns from experience, not just from more data.
Researchers are calling SEAL a milestone in “continual learning”; a way to make LLMs that don’t freeze after training.
Developers are excited about practical uses: smaller AI models that adapt locally on-device, improving privacy and personalization.
Critics are warning about catastrophic forgetting; each self-edit might erase older knowledge if not managed.
Philosophers of AI are reigniting the “agency” debate: if a system rewrites itself, where does authorship or accountability live?
It’s early research, but the implications run deep. Imagine LLMs that keep learning from your company’s data in real time — safely, privately, and without retraining from scratch.
Google unveiled Gemini Enterprise, its new AI platform for businesses — pitched as the “front door” for enterprise AI. The goal is move beyond scattered AI tools and create one connected system that understands company data, automates work, and scales safely across teams.
Key features include:
Unified AI Interface: A chat-style hub that acts as a single point of entry for all enterprise AI tasks.
No-Code Workbench: Lets teams automate workflows and build custom agents without engineering support.
Prebuilt Google Agents: Ready-to-use assistants for research, analytics, and customer insights.
Central Governance: A unified dashboard to monitor, secure, and audit all deployed agents.
Cross-Platform Integration: Works natively with both Google Workspace and Microsoft 365 environments.
Companies like Figma, Klarna, Mercedes-Benz, Banco BV, and Morrisons are already using Gemini Enterprise to accelerate analytics, automate workflows, and personalize customer engagement.
OpenAI has announced a multi-year deal with Broadcom to design and deploy 10 gigawatts of custom AI accelerators, marking its biggest hardware initiative yet.
Under the partnership, OpenAI will design the chips, while Broadcom develops and deploys them starting in 2026, with completion targeted for 2029. The systems will use Broadcom’s Ethernet networking, positioning them as an alternative to Nvidia’s InfiniBand setup.
Broadcom CEO Hock Tan called the collaboration a “pivotal moment in the pursuit of AGI,” noting that it merges OpenAI’s frontier-model expertise with Broadcom’s networking and semiconductor design. Tan noted that generative AI could soon represent a “much larger part of global GDP”, driven by breakthroughs in custom chips and energy-efficient data centers.
Meet Vibe for WordPress
10Web just dropped something new, stepping into the next phase of web creation — Vibe for WordPress, the first AI-native vibe coding builder fully integrated with WordPress.
If drag-and-drop builders were the training wheels of website creation, Vibe is the full electric bike. You get the creative freedom of vibe coding (no grids, no rigid templates) paired with WordPress’s battle-tested backend: plugins, hosting, security, SEO, and full code ownership included.
What makes it special?
Prompt-to-Website Generation: Type a few sentences and get a complete, hosted WordPress site.
Frontend Freedom: Build any layout, animation, or interaction without drag-and-drop limits.
AI + Code Collaboration: Chat, change, or dive straight into code — it’s all one fluid workflow.
All-in-One Stack: Managed hosting, CDN, SSL, backups, and performance optimization built in.
Open Source: Your code, your control — no vendor lock-in.
Vibe is perfect for agencies shipping sites in days, indie founders launching MVPs over a weekend, and business owners creating professional sites without developer overhead.
