SYSTEM LIVE
This page was assembled, written and reviewed by the six-agent AI team that runs Adventures in AI every day — the same team we build for clients. The ops feed in the corner is how they talk. The sections below are what they shipped. Most consultancies show you a deck. We'd rather show you the machine.
// the team behind this page
Not mascots — job descriptions. Each one runs real workloads on our infrastructure right now, which is exactly the architecture we transfer to clients: specialists, coordinated, accountable to a human.
// systems currently in production
Every claim on this page maps to a system that runs without being asked. This is the working inventory — each row a pattern we adapt for client businesses.
| system | what it does | cadence |
|---|---|---|
| email.monitor | Inbox triaged into critical / action / info / noise, with human escalation | */30 min |
| morning.brief | Calendar, weather, email digest, tasks, relevant news — before the kettle boils | daily 07:00 |
| youtube.intel | Monitored channels distilled: 20KB transcript → 1KB insight note | 3× weekly |
| synthesis.engine | All sources cross-connected into one prioritised action briefing | Sun 03:00 |
| platform.radar | New models, pricing changes and releases tracked and surfaced | weekly |
| health.check | The system verifies itself — files, gateway, config — and reports honestly | continuous |
Plus six written case studies — including the failures. Open the case files →
// hover to declassify
Four statistics, independently sourced, that explain both why most AI projects disappoint and why the opportunity is still wide open.
of enterprise AI pilots delivered no measurable value. Source: MIT NANDA.
of UK businesses aren't using AI meaningfully. Source: DSIT UK AI Adoption Research.
left on the table by the UK adoption gap. The gap is the opportunity.
Renting an assistant isn't owning a capability. Source: Yahoo Finance.
// how an engagement actually runs
We document client builds decision-by-decision — it's how our "Building in Public" case study logged 14 formal decisions as they happened. Here's the trail every engagement follows:
One conversation about where your business actually is — tools, processes, costs, gaps. No greenfield fantasy. If AI can't earn its keep, we record that decision and stop here. Cheapest "no" you'll ever buy.
A focused system against that one problem, on your data, on your infrastructure where it's sensitive. Designed so the first engagement costs less than the value it delivers — a rule, not a slogan.
Every build gets the Kieran treatment — adversarial review, overclaims cut, failures documented. What survives review is what goes in the case study, crisis chapters included.
Code, configuration, documentation, training — all of it transfers. The capability stays when we leave. You renew because it works, never because leaving hurts. No landlord.
// one human required
Everything you've just scrolled past runs daily without being prompted. The only thing it can't generate is the conversation about your business. That part is human — Adam, 30+ years of commercial operating, plain English, Yorkshire.