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The unseen layer of the agentic web and MCP

One of the biggest large language model vendors is about to be offered as public shares sold on the stock exchange in an initial public offering. Anthropic’s industry emerged from research conducted at Google in 2017 on the generative pre-trained transformer architecture. (GPT is used to create the large language models that now proliferate broadly across the world technology sector.) Simply stated, LLMs generate predictive text, images or code for the future based on things said or indexedd in the past. There is an often quoted idiom that history doesn’t repeat, but it often rhymes with the past. Recently many people have been thinking about the emergence of the LLM industry in light of all the private companies hoping to sell their shares in the near future. I've been thinking and discussing a lot about one of the concepts Anthropic pioneered as a now-standardized web architecture called MCP, model context protocol . (MCP can be thought of like a handshake between agentic syst...

The Web Uniting the Families of Eastern Flight 212

50 years after my father’s plane crash, three journalists tracked our family down. News reports from the aftermath of the crash of Eastern Flight 212 had floated around and came across the desk of the Charlotte Observer, the newspaper that had reported on the crash in 1974. My father’s voice was one of those you could hear in the TV newscaster report. He said “another voice lost in time of an anonymous survivor.” The Charlotte Observer journalists reached out asking if they could interview my father and me about the impact the crash had on our lives and how we reflected back on the time through the years. I knew the story very well. My father had recounted it to me and my brother numerous times. We thought about September 11th differently than most people. We had written a narrative account of what happened that day. So had an Associated Press reporter who resigned from AP with the intent to tell the story of that tragedy that created the “Sterile Cockpit Rule” that forever ...

Creating LLM apps from components

I have a colleague who is trying to study her mother's native language (she is second generation non-resident Taiwanese) and wants to have a tool for transliterating her parents' dialog into English with learning highlights for study as flash cards. This is beyond what Duolingo, Apple Translate and Google Translate were designed to do. It seemed this could be built using several existing tools. We could ask Duolingo, Apple or Google to build it for us. But our use case here might be too niche to make sense to the general population of language learners who use those other tools. Right now she uses a recorder, then ends one step in the process. Then she would look up different words in a dictionary phonetically to find the Chinese character she was hoping to learn. Then she saves those words in a list and practices those terms in her own context. I’ve done this too. I also study Chinese characters for fun. (Han characters, called 漢字 (Kanji) in Japanese, are foundational concept...

Google is moulting

I have worked with multiple search engine companies through the last three decades. It was what my generation’s task was after the personal computer boom that was defined by the work of my father’s generation. (He was a systems engineer for IBM through the transition from “Big Iron” mainframe computers to desktop computers.) So over the years I’ve seen some fascinating technology advancements in how we author the web as web content creators, how we index it and serve it via search engines, and how we scale accessibility for original creative content bringing new audiences to it through web portals, apps and content aggregation tools. Recently, I’ve been seeing a transition portended over a decade ago in a panel discussion about new advancements in spam filtering and search engine optimization. The panel featured the legendary Matt Cutts from Google who was their “head of web spam”. In that decade, anchor-text ranking that had defined the early “Page Rank” sorting on the sear...

Vibe coding to a more frictionless future

Do we need to "develop" apps anymore? Can consumers develop their own apps yet? The recent years of post-pandemic employment slump has been capturing headlines as tech leaders across the board have cut their staffing dramatically to achieve more efficiency in their businesses. Seeing hundreds of thousands of layoffs is a grim reminder of the boom/bust cycle that hangs over high-beta companies that leverage investment to scale up for unforeseeable future market demand. An interesting twist in the headlines over the last year is more of these companies seeking to “flatten their organization structures.” Often these stories have focused on machine learning automation of routine tasks and in some cases delegating creative engineering or product design work to automated tools. Legislators, who earn their salaries from taxing humans, wouldn’t want more mechanized labor in the work force because typically machines don’t pay taxes. But seeking to legislate staff retention is a ...