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Automations

What we have automated at Nakama

Here, scenario by scenario, is what we designed to run Nakama, then the real case of our online cybersecurity service.

Each scenario says what triggers it, which agents do the work, what comes out of it and what is approved before it goes out. They all rely on the complete NakamaOS, the software we install in your company.

A typical day at Nakama, written as an example 6 h 8 h 10 h 12 h 14 h 16 h 18 h 6 h 30 Monitoring 8 h E-mail 9 h 30 Morning brief 11 h Support 14 h Sales 16 h Communication 18 h Figures

Scenario

A typical day at Nakama

A typical day, written as an example, based on what our agents do. An AI agent is a program that reads, sorts and drafts, like an assistant who prepares the work. Each one has a job title and a first name: Nakama, the Chief of Staff, shares out the work; Ada, the Automations Lead, starts the scheduled tasks; the code agents write the software. The day follows NakamaCyber, where developers practise spotting security flaws in code. The real figures appear in the monthly report.

Everything is done by AI agents; nothing goes out without approval. What each agent does: the team.

  1. 06:00Automations Lead — Ada starts the morning security watch for NakamaCyber. Every source cites a security flaw disclosed overnight: it goes to the top of the summary.
  2. 06:30Research Lead — Leo checks the flaw against several sources and turns it into a fact sheet: what it allows, whom it affects, how to fix it.
  3. 07:00Inbox Lead — Mira sorts the overnight inbox, flags a proposal still unanswered after more than five days and, on request, drafts the follow-up.
  4. 07:30Code agents write a new exercise for NakamaCyber based on this flaw: a code snippet in which to spot it, and its fix.
  5. 08:30Support Lead — Iris sorts the support requests for NakamaCyber that came in overnight and, on request, prepares each reply with the customer’s history. The recurring question becomes a help article.
  6. 09:30Chief of Staff — Nakama prepares the morning briefing: the exercise and the follow-up to approve, the support replies, the afternoon demo, an overdue invoice to chase.
  7. 10:30Inbox Lead — Mira sends the follow-up on the proposal, once approved. approved
  8. 11:00Marketing Lead — Noa writes the blog article explaining the flaw, and schedules the LinkedIn and X posts announcing the exercise for noon. approved
  9. 11:30Code agents add the new exercise to NakamaCyber, and the article to the blog. approved
  10. 13:30Meetings Lead — Kai prepares the afternoon demo meeting with an interested company: who is coming, what its team is looking for, past exchanges, the questions to expect.
  11. 16:00Meetings Lead — Kai writes up the demo from the notes: the needs, the doubts, the next step.
  12. 16:30Sales Lead — Theo drafts the proposal from that write-up; it goes out once approved, and the prospect’s record is updated in the CRM (HubSpot). approved
  13. 17:30Knowledge Keeper — Otto files the day in the memory: the flaw and its exercise, the questions from the demo, the proposal. Tomorrow, every agent can find them.
  14. 18:30Analytics Lead — Sage updates the week’s figures, each with its source: sign-ups, support requests, demos, proposals.

  1. E-mail and follow-ups

    • Portrait of Mira, Inbox LeadInbox Lead — Mira
    • Portrait of Nakama, Chief of StaffChief of Staff — Nakama

    When it startsEvery morning for the sorting; the replies, when you ask for them.

    What comes outAn inbox sorted every morning, the list of unanswered messages and, on request, the replies and follow-ups drafted (Gmail, Outlook).

    See the steps
    1. The Inbox Lead reads each message in full and sorts the inbox: what is waiting for our reply, what is waiting for someone else’s, what is for information.
    2. It flags messages still unanswered after more than five days: a proposal, a quote, a question to a supplier.
    3. On request, it drafts the reply or the follow-up, in the house tone.
    4. The Chief of Staff, the agent that shares out the work, hands each request to the right agent: a customer question to the Support Lead, a price request to the Sales Lead.

    approvedEvery reply, before it is sent.

    What it would spare youThe follow-up forgotten at the bottom of the inbox.

  2. Prospecting and sales

    • Portrait of Theo, Sales LeadSales Lead — Theo
    • Portrait of Otto, Knowledge KeeperKnowledge Keeper — Otto
    • Portrait of Mira, Inbox LeadInbox Lead — Mira

    When it startsWith every request that comes in; every Monday, the prospect list.

    What comes outThe written reply to each request, a profile and a first message per prospect, the follow-up list, the CRM up to date (HubSpot).

    See the steps
    1. The Sales Lead prepares the written reply to each request, with what the memory already knows.
    2. It looks up each prospect on the web, on their site and public pages, and prepares a profile and a first message.
    3. The Inbox Lead spots the follow-ups that are due.
    4. The CRM is kept up to date (HubSpot).

    approvedEvery message, one by one. No mass sending.

    What it would spare youThe quote gathering dust that nobody chases.

  3. Support

    • Portrait of Iris, Support LeadSupport Lead — Iris
    • Portrait of Otto, Knowledge KeeperKnowledge Keeper — Otto

    When it startsWith every support request.

    What comes outEvery request sorted, and its reply prepared as soon as you ask; a help article drawn from the recurring question (HubSpot, Zendesk, Slack).

    See the steps
    1. The Support Lead sorts each request and, as soon as you ask, prepares the reply with the customer’s history.
    2. The memory finds what has already been answered.
    3. The recurring question becomes a help article.

    approvedEvery reply and every article, before it goes out.

    What it would spare youThe same reply, retyped every week.

  4. Communication on every channel

    • Portrait of Noa, Marketing LeadMarketing Lead — Noa
    • Portrait of Otto, Knowledge KeeperKnowledge Keeper — Otto
    • Portrait of Leo, Research LeadResearch Lead — Leo
    • Code agents

    When it startsEvery Monday, the week’s programme; every Friday, the article for the Nakama blog.

    What comes outThe week’s programme, the LinkedIn and X posts, the blog article, the podcast episode notes.

    See the steps
    1. The Marketing Lead draws one text per channel from the week, LinkedIn and X, based on the notes, the decisions and the podcast episodes.
    2. The memory finds each fact and its source; the Research Lead checks what comes from the web.
    3. On Friday, the code agents write the blog article from the notes of the week.

    approvedEvery text, before it is published.

    What it would spare youThe LinkedIn page nobody feeds any more.

  5. SEO and site monitoring

    • Portrait of Ada, Automations LeadAutomations Lead — Ada
    • Portrait of Leo, Research LeadResearch Lead — Leo
    • Code agents

    When it startsEvery Monday, at a set time.

    What comes outA dashboard kept up to date, and the fixes ready to go live.

    See the steps
    1. A scheduled task opens every page of the site and notes the titles, the descriptions and the broken links.
    2. The Research Lead follows on the web the searches where the site should appear.
    3. The code agents prepare the fixes, ready to go live.

    approvedEvery fix, before it goes live.

    What it would spare youThe broken link a customer finds before you do.

  6. News watch

    • Portrait of Ada, Automations LeadAutomations Lead — Ada
    • Portrait of Leo, Research LeadResearch Lead — Leo

    When it startsEvery morning, at a set time.

    What comes outEvery morning, a summary with its sources, one line per topic, and ideas for posts and exercises.

    See the steps
    1. Every morning, a scheduled task starts the search.
    2. The Research Lead reads the newly disclosed security flaws and what is being written about AI agents.
    3. It compares the sources and keeps the ones that hold up.

    approvedThe posts and exercises drawn from the watch, before they are published.

    What it would spare youThe news watch you keep putting off.

  7. The week’s figures

    • Portrait of Sage, Analytics LeadAnalytics Lead — Sage

    When it startsEvery Friday.

    What comes outThe week’s review, each figure with its source.

    See the steps
    1. Every Friday, the Analytics Lead records the week’s counters, each with its source.
    2. A figure without a source does not go out: it flags it instead of estimating it.

    approvedEvery figure, before it is published.

    What it would spare youThe report written the night before.

  8. Meetings and calendar

    • Portrait of Kai, Meetings LeadMeetings Lead — Kai
    • Portrait of Remy, Planning LeadPlanning Lead — Remy

    When it startsBefore each meeting, and every Monday to prepare the week.

    What comes outA brief before, minutes after, the week’s time slots (Google Calendar, Outlook).

    See the steps
    1. Before each appointment, the Meetings Lead prepares a brief: who is coming, past exchanges, the open questions.
    2. Afterwards, it writes the minutes from the meeting notes.
    3. The Planning Lead suggests the week’s time slots and the blocks to protect.

    approvedEvery appointment, before it goes into the calendar.

    What it would spare youWalking into a meeting without the file.

  9. Invoicing and admin

    • Portrait of Nakama, Chief of StaffChief of Staff — Nakama
    • Portrait of Sage, Analytics LeadAnalytics Lead — Sage

    When it startsThe first working day of the month.

    What comes outThe text of each invoice and each payment reminder, ready to copy into the invoicing tool; the calendar of admin deadlines, kept up to date.

    See the steps
    1. The Chief of Staff prepares the text of the month’s invoices and payment reminders, and the calendar of admin deadlines.
    2. The Analytics Lead supplies the amounts and their sources.

    approvedEvery invoice, before it is sent.

    What it would spare youThe forgotten admin deadline, the payment reminder you keep putting off. The invoice itself is made in your invoicing tool.

The real case

How NakamaCyber runs

An online cybersecurity service, in production, run by the same agents; one person approves. Developers train there to spot security flaws in code.

  • Build-in-public posts and blog articles

    The Marketing Lead draws from the week the LinkedIn and X posts and the blog articles: what was delivered, what broke, what was learned.

    • Portrait of Noa, Marketing LeadMarketing Lead — Noa
    • Portrait of Leo, Research LeadResearch Lead — Leo

  • Stripe payment follow-up

    Numbers follows subscriptions and Stripe payments, and flags a failed payment; the reminder is prepared.

    • Portrait of Sage, Analytics LeadAnalytics Lead — Sage
    • Portrait of Nakama, Chief of StaffChief of Staff — Nakama

  • Support

    Each request goes to the Support Lead, which prepares the reply with the customer’s history; the recurring question becomes a help article.

    • Portrait of Iris, Support LeadSupport Lead — Iris
    • Portrait of Otto, Knowledge KeeperKnowledge Keeper — Otto

  • E-mails and meetings

    The inbox sorts and prepares replies; every meeting has its brief before and its minutes after.

    • Portrait of Mira, Inbox LeadInbox Lead — Mira
    • Portrait of Kai, Meetings LeadMeetings Lead — Kai

  • The new exercises

    Every morning, a scheduled task picks up the newly disclosed security flaws; every week, the Research Lead picks one, with its source; the code agents write the exercise and its fix.

    • Portrait of Ada, Automations LeadAutomations Lead — Ada
    • Portrait of Leo, Research LeadResearch Lead — Leo
    • Code agents

  • SEO and site monitoring

    A scheduled task rereads the site’s pages and follows the searches where they should appear; the code agents prepare the fixes.

    • Portrait of Ada, Automations LeadAutomations Lead — Ada
    • Code agents

approved Every post, every article, every reply, every exercise, before it goes out.

See NakamaCyberGo to nakamacyber.com

And in your company?

These scenarios run Nakama. For yours, see the use cases and the sectors, or describe your business: the written reply says what can be automated in your company.

Describe what you would hand over See all twelve use cases

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