What do you need for UCP? There are two levels of UCP readiness. The first is the minimum viable manifest — the bare requirements to pass validation and appear in the UCP directory. The second is the agent-ready setup — what it actually takes for an AI agent to browse, cart, and check out at your store without friction. Think of this as your UCP checklist — the minimum requirements plus the recomm
How I Built a Bitcoin-Only Digital Store (No Stripe, No PayPal) What happened when I deleted my payment processor and embraced financial sovereignty I still remember the day Stripe froze my account. A client disputed a $200 payment and before I could even respond, my entire balance was locked. Three weeks of emails. Two verification requests. And ultimately, a 30-day hold while they "investigate
A Haystack pipeline can be perfectly wired and still unsafe. The retriever returns documents. Every component did its job. But if untrusted text moved through the pipeline as ordinary context, the trust boundary was lost. That is the problem this post is about. Not bad Python. A valid component connection only says: this value fits the next component It does not say: this value is safe to influen
"OK, I understand the RPS formula. But is our RPS — actually — high or low compared to our industry?" Right after I published the RPS-definition guide last week, this was the most common question I got back from EC operators. They want to know where they sit, not just how to compute the number. Knowing your RPS is $1.20 means nothing if you don't know whether that's the industry median, the top qu
I run a flower shop in Munich and recently migrated my entire e-commerce setup to Medusa v2. The shop, the One thing that was completely missing: a connection to Lexware Office, which is the most popular accounting software So I built LexBridge - an open-source Medusa v2 plugin that automates the entire invoicing workflow. What it does When a customer places an order, the plugin: Looks up the cust
Comparison: Haystack 2.0 vs. RAGatouille 0.3 for Building High-Accuracy RAG Pipelines for Developer Docs Retrieval-Augmented Generation (RAG) has become the standard for building LLM-powered tools that answer questions using private or domain-specific data. For developer documentation (dev docs) — which includes technical jargon, versioned APIs, code snippets, and structured reference material —