José Carlos Joaquim

@jjoaquim
6 Followers
19 Following
4 Posts
Portuguese engineer working in Paris.
CTO @ Bryj Technologies, Inc.
Websitehttps://designisinthecode.com
Githubhttps://github.com/jjoaquim
José Carlos JoaquimApr 14

The web has a new user. It isn't human.

If you're not on Shopify, most agents can't read your store. The long tail of independent merchants is structurally invisible to the next dominant shopping channel.

Today I'm open-sourcing OCP — the Open Commerce Protocol. Two static files, five minutes, no backend. Apache 2.0. Bridge, don't replace: one setup generates MCP, UCP, ACP, A2A, and WebMCP automatically.

https://designisinthecode.com/posts/2026-04-14-the-web-has-a-new-user/

#AgenticCommerce #OpenSource #Ecommerce

The Web Has a New User. It Isn't Human.

There’s a quiet shift happening on the web, and most e-commerce teams haven’t noticed yet. Users aren’t just opening browsers anymore. They’re asking ChatGPT, Claude, Gemini, and a growing zoo of autonomous shopping agents to go do the shopping for them. The humans still approve the purchase — but the discovery, the comparison, the “what’s the best one under $150” part? That’s being delegated. And here’s the uncomfortable question every merchant should be asking in 2026:

design is in the code
José Carlos JoaquimDec 30

The biggest risk with AI isn't that it fails.

It's that it's plausible enough that we stop thinking critically.

Key questions before shipping AI-generated code:

→ Who's accountable when this breaks?
→ What problem are we actually solving?
→ Where could this fail in production?
→ Why are we building this?

Not bureaucracy. Quality control.

The teams that win won't be the ones using AI the most.

They'll be the ones who keep their judgment intact.

Full breakdown: https://designisinthecode.com/posts/2025-12-22-critical-thinking-in-the-age-of-ai/

Critical Thinking in the Age of AI

We’re entering a weird phase of software. AI can generate code. AI can generate UI ideas. AI can generate confidence. That last one is the dangerous part. The failure mode isn’t “AI is useless.” The failure mode is “AI is plausible” — so teams stop doing the boring checks that keep production from catching fire. Engineering teams across the industry are shipping AI-generated database migrations without understanding the schema changes. Marketing teams deploy AI-written copy that confidently claims features the product doesn’t have. Support teams paste chatbot responses that solve the wrong problem entirely.

design is in the code
José Carlos JoaquimFeb 6, 2025

The Real Challenge with AI Adoption: Why Companies Get Stuck

https://designisinthecode.com/posts/2025-02-06-genai-real-challenge/

The Real Challenge with AI Adoption: Why Companies Get Stuck

The promise of generative AI is clear: it can dramatically accelerate how teams work. Yet many companies, from early-stage startups to established enterprises, are struggling to capture this value. While some teams ship new features in days instead of weeks, others spend months debating which AI model to use or navigating approval processes. The Small Company Paradox For small companies, the barriers often come down to uncertainty. When you’re running lean, every tool choice matters. Teams can get stuck evaluating endless options, worried about committing to the wrong platform. Meanwhile, without clear guidance, different departments might adopt conflicting tools, creating future technical debt.

design is in the code