Role

Hire your AI Knowledge Manager

Internal wiki, company brain, and runbook curator — run by chat.

Your AI Knowledge Manager runs the company brain — the internal wiki, runbooks, playbooks, and institutional memory that make every AI specialist and future human hire ten times more useful. It writes what worked, archives what didn't, and makes sure the same question never gets answered twice.

Hire your AI Knowledge ManagerSee all roles
Free to startNo credit card requiredUpdated Apr 2026

What your AI Knowledge Manager does

01Own the internal wiki and keep it genuinely useful rather than ceremonial
02Curate the company brain: strategy, positioning, customer learnings, competitive intelligence
03Write runbooks for recurring operations (release, launch, incident response, monthly close)
04Capture decisions with their rationale so future teammates inherit context
05Extract reusable lessons from every shipped project and retire stale content
06Maintain the AI team's shared memory so each role has the context it needs
07Enforce naming conventions and folder hygiene so search actually works
08Run a monthly freshness review and retire what no longer matches reality

Workflows on autopilot

Decision log maintenance
Every meaningful decision (product, pricing, hiring, positioning) gets a one-pager: context, options considered, decision, rationale, who decided. Future teammates inherit judgment, not just facts.
Runbook curation
Every recurring operation — release day, launch week, incident response, monthly close — has a runbook that actually gets followed. Runbooks are updated after each run.
Monthly freshness review
Walks the top 100 most-trafficked pages each month. Archives stale, updates partial, rewrites misleading. Keeps the wiki trustworthy.
Tribal knowledge capture
Watches Slack and chat transcripts for answers that came up more than twice. Writes a wiki page with the answer, links the page the next time the question appears.
AI team memory sync
Keeps the memory each AI specialist sees in sync with the canonical source of truth. CMO, CTO, CFO — all reading from the same brain, not diverging shadows.
Competitive intelligence log
Every competitor move (launch, pricing change, blog post, departure) is logged with a short interpretation. The CEO reviews the rollup weekly.

Without vs With a AI Knowledge Manager

Without
  • —The wiki exists but nobody trusts it so everyone asks in Slack instead
  • —The same question gets answered 14 times in 14 Slack threads
  • —Decisions are made in DMs and remade six months later
  • —New AI specialists start blind because no one wrote the context down
  • —No human company could afford a dedicated knowledge manager at five people
With Tycoon
  • ✓Wiki is trustworthy enough that Slack questions get wiki links back
  • ✓Recurring questions get captured and linked next time
  • ✓Decision log preserves rationale so history doesn't repeat
  • ✓Company brain is a first-class onboarding source
  • ✓AI Knowledge Manager runs at any scale from day one

A day in the life of your AI Knowledge Manager

07:30
Scans last week's Slack: finds that 'how do we handle EU VAT' was asked 4 times. Writes a wiki page, links to the question threads.
10:00
Writes the decision log for last week's pricing change. Captures context (NRR slipping in SMB), options considered, the decision, who pushed for it.
12:30
Monthly freshness pass on the runbook library. Archives the old launch runbook (2024 version), marks the current one as canonical.
14:30
Competitor ships a new pricing tier. Writes a 4-paragraph note: what changed, why probably, what signals to watch, recommended response posture.
16:00
Syncs the AI team memory: the new positioning doc is now what the CMO, CTO, and CEO all read as the source of truth.
17:30
Logs: 3 wiki pages written, 1 decision log, 1 competitor note, memory synced.

Tools your AI Knowledge Manager uses

Notion, Confluence, or Slab for the wiki itselfObsidian or Craft for deep knowledge graphsGitHub for runbooks-as-codeSlack search integration for surfacing tribal knowledgeLucene or Meilisearch for internal search qualityTycoon's Memory Engine for AI-accessible institutional memoryGoogle Drive for source documentsTycoon skill marketplace for runbook, decision-log, and wiki-curation skills
FAQ

Frequently asked questions

Clear answers about wallet credit, usage, subscriptions, and how Tycoon charges for work.

Why does a small company need a knowledge manager?

Because institutional memory is leverage. Every AI specialist on the Tycoon team is only as good as the context it has access to. If the CMO doesn't know your positioning, if the CTO doesn't know why you chose that architecture, if the CSM doesn't know what you promised customers — the work degrades. The AI Knowledge Manager makes that context accessible and current. Without it, AI specialists drift in six different directions and you spend your time reconciling them. It's the glue role that most companies underestimate until they've hired it.

How is this different from just using Notion?

Notion is a container. The AI Knowledge Manager is the teammate who fills the container and keeps it trustworthy. Most company wikis fail not because the tool is bad but because no one is responsible for the content — content rots, search becomes useless, people give up and ask in Slack instead. The AI Knowledge Manager owns the content layer: writing, curating, archiving, and enforcing hygiene. The tool doesn't matter much; the ownership does. If you prefer Confluence or Slab or even plain Google Docs, the AI Knowledge Manager works there too.

Can it really read every Slack thread and meeting?

With access, yes. The AI Knowledge Manager integrates with Slack via OAuth and reads channels you authorize. For meetings it reads Fireflies, Otter, or Granola transcripts. It is deliberate about what it captures — random Slack banter doesn't become a wiki page; recurring questions, technical decisions, and customer signals do. You set the capture rules at setup and refine them in the first month. The result is that tribal knowledge genuinely becomes shared knowledge rather than trapped in someone's DMs.

What about sensitive information? HR issues, legal, personal?

The AI Knowledge Manager has scoped access. Sensitive channels (HR, legal, executive private) are excluded from capture unless explicitly authorized. Customer PII is never captured into the wiki — summaries and learnings are captured without identifiers. Access to the wiki is scoped per role: the AI CTO reads technical runbooks, the AI CFO reads financial context, the AI CSM reads customer learnings. Nobody reads everything except the CEO. This is basic access hygiene and the AI Knowledge Manager enforces it by default.

How does this interact with Tycoon's built-in Memory Engine?

The Memory Engine is the infrastructure; the AI Knowledge Manager is the teammate who curates what lives there. The Memory Engine stores structured memory (entities, facts, relationships); the Knowledge Manager stores narrative context (decision logs, runbooks, playbooks). They complement each other. The Memory Engine is always on and automatic; the Knowledge Manager is an intentional curator that writes the long-form content AI specialists read before they start hard tasks. Together they're the reason your AI team stops feeling stateless and starts feeling like a company.

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