OfficeSpeak turns a plain-English description into a small, always-on team of software workers — an office — that passes messages, keeps state, and reacts to the world. No programming needed to try it. Runs on the DisSysLab engine.
Real, verified groundwork already exists — the walkthrough you'll try is one story through a much bigger, working system.
A sample of what's already built and running in DisSysLab's gallery —
see FEATURES.md for the full, categorized list.
News, markets, and social monitoring — the largest cluster: competitor watch, stock and weather monitors, an arXiv radar, inbox triage, situation-room briefings, a Kalshi market watcher.
Everyday assistants — a wardrobe assistant that checks your calendar and the weather, a job hunter that filters postings and runs parallel analysts, a lead qualifier, a ticket router.
Beyond text — backyard bird-song identification from audio, wildlife camera-trap image classification, a loudness monitor for a simple sense-detect-respond example.
Validation fixtures and demos — a three-agent debate panel that reaches consensus, an investment-club office (analysts, manager, accountant), an office made of two other offices.
The properties every generated office gets for free — never specified by the person describing it, never seen as implementation detail.
Correct even with feedback loops in the agent network — not a fixed reply-count cap.
A genuine global-snapshot consistent cut across every concurrently
running agent, including messages caught mid-flight — dsl run --snapshot-interval N.
dsl explain-trace merges every agent's activity log,
ordered by a physical-time-grounded logical clock, into one causal
story — narrated by Claude, not a template.
dsl show-checkpoint — what every worker's memory held,
and what messages were still in transit, at one instant.
Test one computational worker alone on hand-picked inputs to localize a bug — no concurrency in the picture.
No installation, no Python, no terminal. A conversation with Claude on claude.ai builds your office, explains it back — including what it assumed — and lets you correct it in plain English.
▶ Watch the 2-minute tourTurns your description into an actually-running system, with real numbers. Needs a computer with Python, or someone who has one — right now, that can just be us.
▶ Watch the 2-minute tour