30 years of disappointment. The AI Agent I met in 1997

In 1997 I was twenty-five years old, two years out of art school with a degree in product design and two years into building websites professionally. I was at Oyster Partners, designing for people like MTV, the Office for National Statistics and Rockstar Games. The web was three or four years old as a public thing. The grammar of interaction was: user clicks link, server returns page. Read-only, slow, visually not yet interesting, though we were trying.

My then CEO walked in and told me about a piece of technology we were going to start using and rolling out for clients. It was called AgentWare i3, made by a Cambridge company called Autonomy, founded the year before by Mike Lynch. The pitch was electrifying. AgentWare wasn't search. It was a server-side platform of intelligent agents. The marketing at the time used the phrase "the equivalent of having a personal secretary" - software that would watch what you read, learn what you cared about, and dispatch agents on your behalf.

Software that would watch what you read, learn what you cared about, and dispatch agents on your behalf..

That phrase cut right through me. To me it described the most exciting idea of the future and I was being told that it was there - right in front of me!

There was a 'Personalised Content Push Server'. There was 'News Alert' running in the background, there was 'Guardian Server' - a 'sentinel at the gateway' and most excitingly there was something called 'DailyMe' that would assemble an overnight briefing tuned to a profile the system had inferred about you.

I could imagine would feel like when it actually worked. An entity that knew me, briefed me, advised me, anticipated me. A world in which I was being served by something that had inferred me. I understood, in that moment, that this was the most exciting idea I had ever encountered.

And then I saw a demo, and something in me just died.

The Disappointment

What I was shown was a command line. Someone typed at a terminal, ran the system over a database of published documents, and said, Look how good this is. And I genuinely couldn't tell. I couldn't see it. I couldn't feel it. The output was a list of results. The thing that had been described as a personal secretary turned out, in practice, to be a good search engine for published content. And it didn't really feel like it was serving me. It felt like it was serving the organisation that had bought the licence.

The web in 1997 was read-only. You couldn't tell what someone had read, because reading didn't leave a trace anyone could see. There was no behavioural exhaust, no analytics, no smartphone in a pocket logging where anyone had been. The agent, in its own marketing, was supposed to learn what you cared about. But there was no input surface. No place where your interactions, your movement, your behaviour, your interests could be piped into the system. The pipes weren't there. The technology was sat on sparse data, and on sparse data it could do nothing.

I started to understand that the bottleneck wasn't the agent. The bottleneck was the data the agent was supposed to know us through. And in 1997 the data of who we were largely didn't exist in any digital form an agent could see. My own life was the proof. When I later went to gather what I came to call my "data totem" - everything an institution held about me, intending to confront the question of what I was made of in their eyes - it all arrived on paper. Some of it, (about 120 pages from the bank), was hand-written. The substrate that personal agents were supposed to run on was not just inaccessible; it was, in the most literal sense, not yet in the machine.

The promise of agents working on our behalf has always been limited not by the intelligence of the agent but by the accessibility of the data the agent needs. Every wave of agent enthusiasm - 1997's, and the one we're in now - runs into the same wall, and the wall is that we don't have access to who we are. The personal data situation has been, and remains, the biggest bottleneck.

That insight is what set me off on a thirty-year project, though I didn't know it at the time.

The Response

In 2001, I sold my personal data on eBay. People remember it as a stunt or a provocation, and it was kind of both, but underneath it was a serious design question: if agents are coming, and they need data, who owns this stuff, what's it worth, where is it, and how do we connect the pipes? I was running the experiment the industry should have been running but wasn't.

In 2010, I bought the entire UK Companies House dataset, built a Hadoop pipeline to render it accessible through Google. I took £9m worth of public data and liberated it. For free. I ended up in a meeting with a Cabinet Minister (Francis Maude) about it - but that is another story for another time. It wasn't really about companies. It was about the principle that the data we collectively need to be legible to ourselves should be in our hands.

In 2020, my team built me a Chrome extension that injected my own Monzo banking data into Google search results - so that when I searched for my bank balance - it turned up a search result. It was a small thing, almost a toy, but it was the same question in another form: what happens when my data shows up where I am, working for me, without an institution in the middle?

Each of these projects was, in its way, a probe at the same wall. The wall the 25-year-old me had hit when he saw the AgentWare demo and realised that the most exciting technology he had ever encountered was a remarkable engine running on vapour.

Now...

As I write this, I'm currently working for the UK Government Digital Service in the AI Studio - helping to usher Agents and Agency into the citizen-government experience. And I realised that the question I am exploring is the one I formed in 1997.

What does an agent need to be useful to a person, rather than to an organisation?

What does the surface look like - the place where the citizen's life enters the system and the system's actions enter the citizen's life? What does it mean for that surface to be legible, contestable, and theirs?

The technology has caught up. Large language models have given us, finally, the brain Lynch was claiming to have in 1997. Smartphones, APIs, MCP, and a quarter-century of behavioural data have given us the input surface the read-only web couldn't. The pipes exist. The substrate exists. The question now is whether the experience layer - the design layer - can be built so that agents serve the individual rather than, once again, the organisation.

In my spare time, I have been building and operating a set of my own agents - small, personal, unglamorous things that run on a different principle - but they are incredible. They are curious, punctual, respectful - work continuously in the background and never get tired! They know me and are flexible enough to make and adjust plans around me. But most of all - they are largely invisible. I have been exploring what the new interfaces will be for agents and I'm starting to come to the conclusion that there aren't any. They kind of disappear.

The Truth

But, here is the bitter joke of the thirty-year arc: the world did, in the end, find a way to get our data into the machine. It built applications, devices, interactions and interfaces designed to hold our attention precisely so that data could be harvested from us. The attention economy is what happened when the bottleneck I observed in 1997 was finally broken - and it broke in the worst possible way. I wanted the data to be there. I didn't want it to come like this. What I'm finding now, though, in the agents I live alongside, is the first hint of a different settlement. They don't take my attention. They are attentive. The shift is small as a preposition and large as a world: from technology that takes attention from us to technology that pays attention to us.

From an attention economy to an attentive economy?

That is the agent I was expecting to meet in 1997.