Last week, someone at Anthropic made a packaging error. A build of something called Conway — an internal project for an always-on AI agent — leaked out into the wild. Within hours, screenshots were circulating on Twitter showing an extensions system, webhook endpoints, and a Chrome integration that looked nothing like the Claude chat interface we all know.
Anthropic played it down. A release packaging issue caused by human error, they said. Not a security breach. Sure. But the cat is out of the bag, and what it reveals is far more interesting than the leak itself.
From Prompt-Response to Always-On
Every AI product you use today works the same way: you type something, it responds, you go back and forth until you get what you need. It is fundamentally a conversation. Conway is something different. It is an agent environment that stays running. It has webhook endpoints — public URLs that external services can call to wake the agent up when something happens. It has an extensions system where you can install custom tools, UI tabs, and context handlers. It uses Chrome autonomously to handle multi-step tasks on the web.
This is not a chatbot that got fancier. This is the architectural blueprint for AI that operates like a team member — one that never logs off, never forgets its context, and responds to events in the real world without waiting for you to type a prompt.
I find this significant because I have been building exactly this kind of system for myself over the past few months. My own AI assistant, Saul, already runs scheduled tasks, publishes content, monitors data, and sends me summaries — all without me being in the loop for every step. It works. But it is held together with cron jobs, Python scripts, and API calls that I have wired up manually. Conway suggests Anthropic wants to make this kind of continuous AI operation a first-class product, not a weekend project for the technically inclined.
The Enterprise Is Already There (Sort Of)
A Belitsoft report published this week, drawing on Salesforce’s 2026 Connectivity Benchmark data, says the average enterprise now runs 12 AI agents. Twelve. Expected to hit 20 by 2027. But here is the kicker — half of those agents operate in complete isolation. They do not talk to each other. They do not share context. They are twelve separate hammers looking for nails.
This is exactly the problem Conway appears to be solving. The extensions architecture, the webhook system, the persistent state — it is all about creating a single agent environment that can integrate with everything, rather than deploying a dozen disconnected point solutions. The shift is from “we have AI tools” to “we have an AI operating system.”
What This Means If You Run a Finance Function
I spend most of my professional life inside PE-backed finance teams, and the implications here are not abstract. Think about what a CFO’s week actually looks like: cash flow monitoring, covenant compliance, board pack preparation, variance analysis, vendor negotiations, investor reporting. Every single one of those workflows involves gathering data from multiple systems, applying judgment, producing an output, and sending it somewhere.
An always-on agent does not replace the judgment part — not yet, anyway — but it can collapse the gathering, formatting, and distribution steps into something that just happens. The board pack data is already pulled and formatted before you sit down on Monday morning. The covenant calculations are running continuously, not quarterly. The cash position is reconciled and summarised before the daily stand-up.
This is not speculative. I have automated parts of this already. But Conway-style infrastructure would make it dramatically easier to set up and maintain, which means it stops being something only a CFO who can write Python does and starts being something any competent finance team can deploy.
The Uncomfortable Bit
There is a tension here that I think most people in the AI space are not being honest about. If you make agents always-on, event-driven, and capable of taking action autonomously, you have fundamentally changed the trust model. A chatbot that gives bad advice is annoying. An always-on agent that takes bad action at 3am is a different category of problem entirely.
Conway’s architecture seems to acknowledge this — the extensions and webhook systems suggest granular control over what the agent can and cannot do. But the history of enterprise software tells us that permissions and guardrails are only as good as the people configuring them. And in most mid-market PE-backed businesses, the people configuring them will be a mix of finance staff, IT generalists, and maybe one overstretched CTO. The governance question is not solved by better architecture alone. It requires new operational disciplines that most organisations have not even started thinking about.
Where This Is Going
Here is what I think happens next. Anthropic ships Conway — or something very like it — within the next quarter. Google already has its own agent infrastructure play with Gemma 4 and Vertex agents. OpenAI is pushing GPT-5.4 with desktop task automation that scored 75% on real-world benchmarks. Microsoft just shipped Agent Framework 1.0. The always-on agent is not a research project anymore — it is a product category that every major AI company is racing to own.
For CFOs and finance leaders, the practical question is not whether to adopt this technology, but how to build the internal capability to govern it. That means understanding what your agents are doing, why, and with what authority. It means having someone on the team — or on retainer — who can configure, monitor, and audit these systems. And it means accepting that the competitive advantage will not go to the company that deploys the most agents, but to the one that gets them working together coherently.
The Belitsoft numbers tell us enterprises are already halfway there on deployment. Conway tells us the infrastructure for always-on operation is coming. The missing piece is the operational maturity to make it work safely and effectively. That, more than any model benchmark, is where the real work is.
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