At work
Leaders have to go first.
What of this transferred to a unit of around 300 people, and what did not. An observation, not an offer.
- Technology is the smaller part. In an organisation, approvals, confidentiality and change matter; what did not transfer was the private degree of freedom.
- Business Brain — the same notebook principle for the unit: a repository of linked Markdown files, one context file per folder, skills and prompts for recurring tasks, driven from the code editor with a coding agent.
- Knowledge from the ticket system, wiki, architecture repository and specialist sources is connected; a custom command-line tool returns only the data that is needed.
- Deterministic check scripts guard rules and quality; humans review minutes and tickets before they count.
Legacy system as knowledge base: 250 requirements
Agents derive requirements from the legacy base and reconcile them with the team's current state; all content is draft until the expert review.
Spec to running app in eight person-days
Eight functional and domain building blocks with around 160 input fields in about eight person-days; requirements become visible as running features immediately and can be reviewed by experts right away.
From transcript to ticket
Five to ten minutes after the meeting, minutes and tickets are on the board, no duplicates, correct parent ticket.
Critical risks current within a week
Around 100 active risks checked, around 90 tickets commented with proposals; within a week the owners had updated or closed a good half of them, and a good three quarters of the critical red risks.
Transcribed locally, audio never leaves the device
A cleaned transcript with timestamps shortly after the meeting ends; an eight-hour session day is transcribed in under two hours of compute — the audio stays on the device.
Two months to a team project
Two months from private experiment to kick-off; after the first few months there is a Business Brain, first use cases and change support.
One twelfth of the tokens via CLI
The same board query with 40 cards costs around 1,400 instead of around 17,000 input tokens — about one twelfth for the same information.
1,700 items in one management view
Around 1,700 items consolidated into one delivery status, around 130 epics and features measurable within it — running after a good week, cross-source for the first time.
One meeting, several versions, one to-do list
Distribution-ready documents and a hand-over-ready to-do list across all meetings — from a two-day off-site a good 20 to-dos with owner, date and timestamp, plus minutes and a detailed analysis for almost 30 participants.
Knowledge becomes wiki pages and decks
A wiki page including diagram in about five minutes; across decks, wiki and document store, around 80–90% less time per artefact.
Weekly status from around 15 contributions
A weekly mail draft with embedded dashboard excerpts for three product lines — transparency without an extra meeting.
Ask Mathias: a digital twin
A sparring partner that pushes back and a twin that pre-sorts questions — wired as a pilot in the Business Brain; the test series is still open.
Ticket backlog: an hour, not a day
Backlog built in about an hour instead of a working day — a good four fifths less time; around 60 linked tickets in the first run, one epic round across around 20 products in about an hour.
Knowledge base checks itself, no language model
Traceable knowledge that is checked daily — around 1,650 existing notes across eight brains were back-filled with source and check date for it.
Guided setup: four fifths was waiting
A working workspace; the target is setup in under an hour — the pilot took almost seven, around four fifths of it waiting for individual approvals.
Birthday greetings on time, weekends included
Punctual, personal greetings even on weekends and holidays; plus a morning overview of what each meeting needs.
14 interviews, analysed anonymously, change personas derived
14 interviews across roles condensed into change personas with concrete change needs in a short time — with little resource effort.
Many writers, no overwriting
One shared, versioned knowledge base — over 3,000 commits from around two dozen identities in the team brain since the start.
Email drafts that learn my voice
Drafts that need less rework with every mail sent; the learning comes from comparing with the real result.
Trace instead of gut feeling
Measurable effort instead of gut feeling — the baseline showed zero percent navigation: the agents knew the paths from context and did not follow the knowledge graph.
Build once, use everywhere
Consistent rules and tools across nine workspaces — the second reconciliation run finished without a single file deviation.
Proving AI value continuously
An evidenced portfolio instead of individual success stories — almost 30 use cases, a good 40 percent of them mature.
Meeting versus project knowledge, with trust light
An analysis note with evidence and a reasoned trust level — the reliability of an AI result becomes measurable instead of felt.
Domain and system knowledge in one place
Around 20 domain knowledge sources mapped, around two thirds of them directly usable by AI; first knowledge maps exist for several products, and the first productive domain query returned two relevant supreme-court rulings, cross-checked and filed with sources.
Enablement: open review, office hours, FAQ agent
A recurring rhythm for transparency and enablement — and a lower bar for asking.