Showing posts with label roadmap. Show all posts
Showing posts with label roadmap. Show all posts

The i18n Issue

Mike's Notes

This is a copy of the March issue of Ajabbi Research.

It is about the history of the effort to make Pipi available in any language, localisation, or script requested by users (i18n).

Ajabbi Research is published on SubStack on the first Friday of each month, and subscriptions are free.

Each issue is a broad historical overview of a research topic, serving as an index to dozens of previously posted related articles. There are now over 650 articles/posts.

This copy of the issue will be updated with additional information as it becomes available. Check the Last Updated date given below.

Eventually, each issue will be reused on the separate Ajabbi Research website as an introduction to a research area comprising multiple research projects.

Resources

References

  • SIL.
  • Unicode

Repository

  • Home > Ajabbi Research > Library >
  • Home > Handbook > 

Last Updated

19/04/2026

The i18n Issue

By: Mike Peters
Ajabbi Research: 6/03/2026

Mike is the inventor and architect of Pipi and the founder of Ajabbi.

This is the story of the effort to make Pipi available in any human language and script. The steps taken have been part of Pipi's development since 2005, spanning 5 versions.

The NZERN Pipi 2003-2005 Development Plan started it all.

Pipi 4 (2005-2008)

The story starts with Pipi 4. It was a big, successful system that supported community-driven Ecological Restoration in NZ. Here is a history of that Pipi version.

Initially, the large websites that Pipi generated were in English only.  Then, as botanical and zoological information was added, Latin, English, and Maori names were used. Eventually, provision for Chinese was planned to support the Chinese community-led conservation programmes. There were no separate language data structures in the 850-table Pipi 4 database; instead, some entities had additional columns for each language.

English

  • The 25,000 pages of websites that Pipi generated were initially in English.

Latin

  • Scientific names used in biological data were written in Latin.

Maori

  • Over time, it was realised that support for the Maori Language, Te Reo Maori, was required. To start, bilingual volunteers provided lists of words for regional areas, towns, etc.

Chinese

  • There was an Auckland-based Chinese Community-driven initiative to reach older residents who didn't speak English about conservation.

    Pipi 6 (2017-2019)

    When Pipi was rebuilt from memory, based on the limited experience with Pipi 4, foundational work was done to prepare Pipi for better multilingual support. This would require extra databases.

    Metadata using international codes was added to every database table to enable future language usage. The codes used were ISO 639-3, Country, Unicode, and CLDR/LDML

    ISO 639-3

    ISO 639 gives comprehensive provisions for the identification and assignment of language identifiers to individual languages, and for the creation of new language code elements or for the modification of existing ones (Terms of Reference of the ISO639/MA). - ISO 639-3

    *** 

    It defines three-letter codes for identifying languages. The standard was published by the International Organisation for Standardisation (ISO) on 1 February 2007. As of 2023, this edition of the standard has been officially withdrawn and replaced by ISO 639:2023.

    ISO 639-3 extends the ISO 639-2 alpha-3 codes with an aim to cover all known natural languages. The extended language coverage was based primarily on the language codes used in the Ethnologue (volumes 10–14) published by SIL International, which is now the registration authority for ISO 639-3.[2] It provides an enumeration of languages as complete as possible, including living and extinct, ancient and constructed, major and minor, written and unwritten. However, it does not include reconstructed languages such as Proto-Indo-European.

    ISO 639-3 is intended for use as metadata codes in a wide range of applications. It is widely used in computer and information systems, such as the Internet, in which many languages need to be supported. In archives and other information storage, it is used in cataloging systems, indicating what language a resource is in or about. The codes are also frequently used in the linguistic literature and elsewhere to compensate for the fact that language names may be obscure or ambiguous. Wikipedia

    Examples

    • Eng (English
    • Fra (French)

    ISO_3166-1_alpha-3

    ISO 3166-1 alpha-3 codes are three-letter country codes defined in ISO 3166-1, part of the ISO 3166 standard published by the International Organization for Standardization (ISO), to represent countries, dependent territories, and special areas of geographical interest. They allow a better visual association between the codes and the country names than the two-letter alpha-2 codes (the third set of codes is numeric and hence offers no visual association). They were first included as part of the ISO 3166 standard in its first edition in 1974. - Wikipedia

     Examples

    • ABW  (Aruba)
    • AFG  (Afghanistan)
    • AGO  (Angola)

    Unicode

    Unicode (also known as The Unicode Standard and TUS) is a character encoding standard maintained by the Unicode Consortium designed to support the use of text in all of the world's writing systems that can be digitized. Version 17.0[A] defines 159,801 characters and 172 scripts used in various ordinary, literary, academic and technical contexts. - Wikipedia

    Examples

    • Latn (Latin)
    • Lina (Linear B)
    • Hebr (Hebrew)

    CLDR/LDML

    The Common Locale Data Repository (CLDR) is a project of the Unicode Consortium to provide locale data in XML format for use in computer applications. CLDR contains locale-specific information that an operating system will typically provide to applications. CLDR is written in the Locale Data Markup Language (LDML). - Wikipedia

    Example

     <?xml version="1.0" encoding="UTF-8" ?>
    <ldml>
      
        <version number="1.1">ldml version 1.1</version>
        <generation date="2024-03-06"/>
        <language type="en"/>
        <territory type="US"/>
      
      <!-- other locale data sections follow -->
    </ldml>

    Localisation (L10N)

    Language localisation (or language localisation) is the process of adapting a product's translation to a specific country or region. It is the second phase of a larger process of product translation and cultural adaptation (for specific countries, regions, cultures or groups) to account for differences in distinct markets, a process known as internationalisation and localisation. - Wikipedia

    ***

    Pipi internally automatically stores and uses 3-letter language codes, 4-letter Unicode and 3-letter country codes to define Locales.

    Examples

    • eng-Latn-NZD (New Zealand English)
    • eng-Latn-USA (United States English)

    Customers can configure the options for their own websites.

    Examples

    • en-NZ
    • en-uk

    More information

    Pipi 7 (2020)

    Small, simple, static HTML mockups of websites were created to test how different languages could be used. Experiments with HTML and CSS were conducted to display text on a website in Left-to-Right (LTR) and Right-to-Left (RTL) word order.

    Pipi 8 (2021-2022)

    System-wide i18n and L10N namespaces were implemented throughout Pipi to enable reliable automation and rapid scaling across multiple languages.

    Pipi 9 (2023-2026)

    Joining up all the built systems to self-generate documentation and a front-end User Interface (UI).

    Experiments were conducted to determine how to integrate i18n support with Pipi's other features. It was confirmed that the Pipi core is written in British Standard English and checked by Grammarly.

    A source-target data model structure was created to store i18n scripts. It was greatly influenced by the system used by Wikipedia (MediaWiki) and OpenOffice.

    Experiments were done using 23 languages and writing scripts to test the CMS Engine (cms), data storage, UI layout, etc.

    String Translation

    Community translation will require a dedicated workspace.

    Account Settings

    Each Pipi is built in 1 language and script. Each account can have many languages. An account has many deployments, each in only one language. A deployment can have many workspaces.

    Localisation

    API Endpoints

    All API connections include a choice of API version and language/script.

    Script Font

    Noto from Google was chosen as the default font for Ajabbi due to the number of scripts it supports.

    KeyMan

    SIL provides an open-source KeyMan that enables keyboards for 2500 different languages to be added to websites. Pipi will use a Keyboard Engine (kyb) to provide this integration. This will be built as part of Pipi 10.

    Url Naming Pattern

    Many experiments were conducted to determine a URL structure that could accommodate websites in many languages. Wikipedia was the main influence.

    Examples

    • eng.example.com
    • example.com/eng/
    • en-uk.example.com
    • example.com/en-nz/

    Documentation

    Documentation and Learning material will need to be provided in many languages. The data models are ready for this. As the British English documentation is completed, it could be auto-translated into US English using Grammarly and into the 9 world languages using Google Translate. It would then need to be checked by volunteer users. This is speculative and will require trial and error to confirm.

    Language Prioritisation

    English > 9 world languages > 7000 local languages + localisation.

    Priority will be given to English, which will then serve as the source for translation into 9 world languages.

    • Arabic
    • Bhasa Indonesian
    • Chinese
    • French
    • German
    • Japanese
    • Hindi
    • Portugese
    • Russian
    • Spanish

    Carefully edited material in those languages can then be translated into any of the other 7,000 languages by volunteers in response to user requests.

      Model-driven UI

      The User Interface Description Language (UIDL) was an EU-funded project that was abandoned in 2010 after 10 years of excellent work. It was to enable accessibility on different screens and devices. The research results were reverse-engineered to build a User Interface Engine (usi) that would run in reverse to generate accessibility solutions for Pipi. The CSS Engine (css) replaced some redundant components of the UIDL project. Additional engines for localisation and personalisation were created.


      Pipi CMS Engine (cms)

      For a first teaching customer, a decision was made early on to autogenerate a separate website for each language (English, Māori, NZ Sign Language, and AAC picture language). This was the simplest solution for the CMS and the users.

      Creating UI for each natural language, including sign languages (i18n), requires user requests and volunteer testers.

      Sign Language

      The scheme was dreamed up to embed NZ Relay Video Interpreting on any webpage and in user workspaces. This is an ongoing experiment, driven by deaf people.

      Picture Language

      Professor Stephen Hawking used AAC via a computer-generated voice. There are many forms of AAC, including picture language. Providing this as a UI is being explored, with other AAC to follow. Important for the millions of people with Cerebral Palsy and Motor Neurone Disease.

      Invented Languages

      This system will be able to provide support for Klingon, Elvish, and other invented languages from books and movies, upon request and with volunteers prepared to do the work. This could be useful for fan communities.

      Dead Languages

      This system will be able to provide support for long-dead languages often studied by linguists and historians, such as Ancient Egyptian, Sumerian, Sanskrit, and Ancient Greek, upon request, with volunteers prepared to do the work. This could be useful for museums and faith communities.

      Workspace personalisation

      The workspace settings will eventually offer complete personalisation of the UI in other languages. This will use a personalisation form in account settings.

      Future Ajabbi Foundation Sponsorship

      Once Ajabbi has established ongoing sponsorship for Ortus for providing open-source BoxLang, the Ajabbi Foundation will generously sponsor open-source SIL KeyMan on an ongoing basis.

      Whats next

      Pipi 9 is available only in English. However, users can request any other language through their profile. Pipi 10 (2027-) will feature those multiple languages.

      The most useful and inspiring resource has been SIL Global.

      Dedication

      Every child has the right to be educated in the language of their people and of their birth. This is dedicated to those working tirelessly to record, strengthen or revive human languages.

      A roadmap for accelerators

      Mike's Notes

      It's getting busy, so I need a roadmap for accelerators now.

      Resources

      References

      • Reference

      Repository

      • Home > Ajabbi Research > Library >
      • Home > Handbook > 

      Last Updated

      02/06/2026

      A roadmap for accelerators

      By: Mike Peters
      On a Sandy Beach: 27/03/2026

      Mike is the inventor and architect of Pipi and the founder of Ajabbi.

      Lots of opportunities are coming in.

      This is a roadmap for using coaching, workshops, incubators and accelerators to develop, test and validate the Ajabbi Mission Business Model and the Pipi closed-core and Pipi open-source applications.

      Ultimately, it's a record of what is learned, so it doesn't include missed opportunities or declined applications. There are a few missing items from some time back that are yet to be added.

      Free is good (cloud credits, bro bono, software, training), but no funding or investment is being sought.

      The roadmap is sorted by deadline, so that I remember to do them. The first row of the table is a key.


      Date Roadmap

      deadline

      Start-End

      Status

      Title

      Description

      What

      To come.

      • To come

      Learned

      • To come

      To do/done

      • To come

      Resources


      deadline

      2017-2020

      Completed

      Steve Blank

      "Steve Blank (born 1953) is an American entrepreneur, educator, author and speaker. He created the customer development method that launched the lean startup movement. His work has influenced modern entrepreneurship through the creation of tools and processes for new ventures, which differ from those used in large companies."

      What

      Learning from the very best.

      • Reading his books and blog
      • Watching videos
      • Using all the free courses and tools

      Learned

      • How to use a Business Model Canvas
      • How to use a Mission Model Canvas
      • How to do customer discovery
      • How to run experiments to validate assumptions

      Done

        • Read and tried everything
        • Build Pipi Experiment Engine

        Resources

        deadline

        2020-2023

        Completed

        KiwiSaaS

        "Our community is free to join, and it's where we can safely share our knowledge and experiences with each other. Paying it forward is what drives kiwiSaaS growth."

        What

        Online workshops and random monthly one-on-one meetings with other founders.

          Learned

          • To keep going and when to change course
          • It is OK to make mistakes
          • Will get lots of insights from being open
          • The importance of listening to others

          Done

          • Get stuck in

          Resources

          January 2024

          January - October 2024

          Completed

          Startup Aotearoa

          "Startup Aotearoa ignites New Zealand’s entrepreneurial spirit by providing personalised one-to-one coaching to early-stage startup founders. Delivered nationwide through local regional providers,"

          What

          Mentoring from Mr G led to testing the ICP at Waimumu Southern Field Days 2024 on

          • Developers at Agritech companies
          • Agricultural suppliers

          Learned

          • Developers are the ICP
          • There is a real problem to solve
          • Find a teaching customer

          Done

            • Pivot ajabbi.com to developers
            • Host a teaching customer requiring 3 languages

            Resources

            April 2024

            May - November 2024

            Completed

            Creative HQ's On the Business workshop series

            "This 'On the Business' workshop series gives you the dedicated time and resource to help you grow your business. We'll provide tools, frameworks and hands-on..."

            What

            Remote workshops using Miro canvas.

            Learned

            • To come

            Done

            • To come

            Resources

            February 2025

            February 2025 - March 2025

            Completed

            NZTE Export Essentials SaaS 4-part workshop.

            "Learn what best-practise exporting involves when you sell SaaS offshore."

            What

            Workshops with individual follow-up sessions.

            Learned

            • To use the tools available to test assumptions.

            Done

            • To come

            Resources

            February 2025

            February 2025 - March 2025

            Completed

            NZTE Position for Growth workshop.

            "Our Position for Growth workshops help you define what problem you solve for"

            What

            Workshops with individual follow-up sessions.

            Learned

            • To use the tools available to test assumptions.

            Done

              • To come

              Resources

              25/03/2026

              April 2026 - March 2028

              Application Withdrawn

              Google AI Accelerator

              "With this program, you can get access to startup experts, your Google Cloud and Firebase costs covered up to $200,000 USD (up to $350,000 USD for AI startups) over 2 years, technical training, business support, and Google-wide offers."

              What

              Collaborate with DeepMind to run wild ML integration experiments to go where no developer has gone before.

              • Pipi > IaC > GCP
              • Pipi > VM > BoxLang > Workspaces
              • Pipi > MCP > DeepMind Gemini
              • Pipi > Scientific Workflows > TPU

              Learned

              • Invited to apply by a Google chap who was assisting behind the scenes using an unlisted pathway. I then discovered that free credits begin on the day of application approval, so I will reapply when ready to start in July to make the most of the 24-month window of opportunity.

              To do

              • Increase Pipi DevOps speed (x1000) by completing work on automating the data centre (x10), workspace rendering (x10), and IaC to GCP free tier (x10). This will enable fast, multiple automated experiments.

              Resources

                26/05/2026

                July - November 2026

                Application underway

                Sprout Accelerator

                "The Sprout Accelerator takes a cohort of agrifood innovators on a 3-month adventure to discover, articulate and refine the foundations to grow global startups."

                What

                Test farm management workspace using HTML Mockups on

                • Dairy farmer-led catchment group
                • Agritech wait list from Waimumu

                Learned

                • To come

                To do

                • To come

                Resources

                June 2026

                July 2026 - June 2028

                To apply

                Google AI Accelerator

                "With this program, you can get access to startup experts, your Google Cloud and Firebase costs covered up to $200,000 USD (up to $350,000 USD for AI startups) over 2 years, technical training, business support, and Google-wide offers."

                What

                Collaborate with DeepMind to run wild ML integration experiments to go where no developer has gone before.

                • Pipi > IaC > GCP
                • Pipi > VM > BoxLang > Workspaces
                • Pipi > MCP > DeepMind Gemini
                • Pipi > Scientific Workflows > TPU

                Learned

                • To come

                To do

                • To come

                Resources


                 


                 

                Having a Data Centre changes the roadmap

                Mike's Notes

                This is the revised Pipi roadmap now that the data centre is running. The recent Ajabbi Research report, "The Workspace Issue," has also been revised to reflect these changes.

                Update 25/03/2026

                A very nice chap from Google contacted me to assist with applying to join one of the Google AI Accelerators. I started the application, then stopped when I realised that the 2 years of support and generous free credits started as soon as it was approved. I need to complete all Stage 1 steps in the roadmap below, and the Stage 2 IaC connection to the GCP free tier to deploy Pipi open-source before applying, to make the best use of the opportunity.

                I'm requesting support from Google DeepMind to experiment with connecting Pipi via MCP to DeepMind Gemini and to find a way for Pipi closed-core to use Google TPU. Stage 3 will be highly experimental with unexpected results.

                Pipi is a non-generative multi-agent system with no tokens. It doesn't need tokens to work and its 27 layers deep so far and counting. I expect it to get very barnacled and crusty over time.

                Update 31/03/2026

                Setting up data centre automation has revealed that workspace deployments need to be performed in this order of account types due to the permissions cascade.

                • Agent Accounts (to admin Pipi)
                • Researcher Accounts (to edit UoM, ontologies and physical laws)
                • Developer Accounts (to create enterprise workspaces)
                • Personal Accounts (to sort out personal profiles - UI fonts, etc)
                • Enterprise Accounts (to test and use the system for work)
                • etc

                Update 17/04/2026

                Containers, named Pipi Nest, were created to deploy Pipi.

                Resources

                References

                • Reference

                Repository

                • Home > Ajabbi Research > Library >
                • Home > Handbook > 

                Last Updated

                17/04/2026

                Having a Data Centre changes the roadmap

                By: Mike Peters
                On a Sandy Beach: 27/02/2026

                Mike is the inventor and architect of Pipi and the founder of Ajabbi.

                Having a separate Pipi Core Data Centre changes everything. This has a direct impact on what is possible and on the best path forward. 

                This is the revised working Deployment Roadmap for Pipi. The sequence is roughly correct; the timing is just a guess.

                Stage 1

                Production foundations to enable automation and rapid use.

                When Task Detail
                February 2026 Migration ✔ Separate networks for the isolated Pipi Core Data Centre and the Ajabbi Office.
                March - April 2026 Pipi Nest ✔ Pipi deployment container
                April 2026 Mission Control ✔ Telemetry on the Data Centre.
                April 2026 AutomationPipi Core running autonomously in a Pipi Nest 24x7x365, with a x10 increase in productivity.
                May 2026 Data Centre Admin Agent Workspace rendered by the CMS Engine with no errors.
                May 2026 Workspace Workspaces containing 15,000 web pages are rendered by the CMS Engine with no errors.
                2026 Workspace Workspace UI Menu rendered without errors.
                2026 Workspace Draft in-context help & learning material generated for each workspace without errors.
                2026 Workspace Module-based UI forms and data grids rendered with sample data without errors.
                2026 Workspace Complete HTML workspace demo with connected initial developer documentation rendered without error
                2026 Workspaces for Agents & Developers Workspaces are deployed in the Data Centre for production use by System Admin and DevOps, with a x10 increase in productivity.
                2026

                2026

                2026
                2026
                2026

                Stage 2

                Automate Pipi deployment across every available cloud platform, with a free tier.

                When Task Detail
                2026 IaC Deploy infrastructure on the AWS Free Tier.
                2026 IaC Deploy infrastructure on the Azure Free Tier.
                2026 IaC Deploy infrastructure on the Digital Ocean Free Tier.
                2026 IaC Deploy infrastructure on the GCP Free Tier.
                2026 IaC Deploy infrastructure on the IBM Free Tier.
                2026 IaC Deploy infrastructure on the Oracle Free Tier.
                2026 IaC Deploy infrastructure on the Wasabi Free Tier.
                2026
                ...

                Stage 3

                Deploy to any platform when admitted to its startup program that offers lots of credits to enable experimentation and scaling with early customers.

                When Task Detail

                IaC Deploy infrastructure on every non-free part of the platform.

                IaC BoxLang VM containing Pipi Open-Source, deployed via IaC.
                  MCP, A2A, Skills Pipi > LLM > Pipi
                  Working Demo Fully working demo workspaces available for customers and developers to try out.
                  Customer Deployments Ajabbi Personal, Developer, and Enterprise account Workspaces are available.
                  Customer Deployments Ajabbi Researcher and SME account Workspaces are available.
                  Scientific Workflows TPU
                 
                 

                Stage 4

                At a certain threshold, Pipi 10 will come into being, creating many more possibilities.

                The Workspace Issue

                Mike's Notes

                This is a copy of the January issue of Ajabbi Research.

                It is a historical overview of the effort to create a workspace-based UI for Pipi.

                Ajabbi Research is published on SubStack on the first Friday of each month, and subscriptions are free.

                Each issue is a broad historical overview of a research topic, serving as an index to dozens of previously posted related articles. There are now over 600 articles/posts.

                This copy of the issue will be updated with additional information as it becomes available. Check the Last Updated date given below.

                Eventually, each issue will be reused on the separate Ajabbi Research website as an introduction to a research area comprising multiple research projects.

                Resources

                References

                • Reference

                Repository

                • Home > Ajabbi Research > Library >
                • Home > Handbook > 

                Last Updated

                31/03/2026

                The Workspace Issue

                By: Mike Peters
                Ajabbi Research: 02/01/2026

                Mike is the inventor and architect of Pipi and the founder of Ajabbi.

                This is the story of how Pipi got a workspace-based User Interface (UI). The steps taken have been part of Pipi's development since 2007, spanning 5 versions.

                The NZERN Pipi 2003-2005 Development Plan started it all.

                Pipi 4 (2005-2008)

                The story starts with Pipi 4. It was a big, successful system that supported community-driven Ecological Restoration in NZ. Here is a history of that Pipi version.

                Due to very rapid scaling, a no-code approach was required to build the UI.

                NetSuite was the original inspiration. A database-based framework was constructed to store user interface components, and another database to store the information being displayed and edited.

                Recently, an archive of Pipi 4 help documentation was discovered and is now available for viewing. It is incomplete, but it gives an idea of how it worked.

                Pipi 6 (2017-2019)

                When Pipi was rebuilt from memory, the monolithic architecture was refactored into loosely coupled modules. Many new modules were created to support a rich UI. Each module had its own database.

                Pipi 7 (2020)

                Pipi was converted to microservices. Pipi could self-document. Static HTML mockups of workspaces were created as experiments. They were generic and could be applied to any subject domain, e.g., space, health, film, or experiments.

                Pipi 8 (2021-2022)

                System-wide namespaces were introduced, making Pipi headless, and the microservices were converted into autonomous agents (Engines). Self-documentation broke as a result.

                More agents were created to manage each other. Some were merged, and others split. These agents are large, with 10,000 lines of code common, and they maintain internal, complex databases, messaging, and workflows, all of which maintain state. None of them is stateless.

                Pipi 9 (2023-2026)

                Many of the internal engines were aggregated into complex systems. Some contained up to 20 different engines, all operating independently and interacting. These systems were then combined into more extensive systems, etc. So far, there are 300+ different engines (with multiple copies), and Pipi 9 has emerged.

                Key problems needed to be solved to enable a workspace-based UI to emerge from Pipi. These included;

                • Ontology-driven constraints
                • Domain modelling
                • Model-driven UI to provide automatic accessibility
                • Self-documenting
                • Structured learning
                • i18n for every human language and writing system.
                • Design system
                • Security and permissions
                • Useful URL patterns
                • Naming conventions
                • Ribbon menu

                Ontology-driven constraints

                The Ontolog Forum was a great help. BORO was hacked to run in reverse. This drives the system-wide constraints. The BORO Engine (bor) can also autonomously run forward if needed, similar to the KREB's cycle. This means ontologies can be imported into Pipi by the Ontology Engine (ont) to help provide world models based on primitives supplied by the Physical Law Engine (plw).

                In the Reductionist System (red), the Domain Engine (dmn) and Module Engine (mod) create data models using Domain-Driven Design (DDD) from ontologies.

                Model-driven UI

                The User Interface Description Language (UIDL) was an EU-funded project that was abandoned in 2010 after 10 years of excellent work. It was to enable accessibility on different screens and devices. The research results were reverse-engineered to build a User Interface Engine (usi) that would run in reverse to generate accessibility solutions for Pipi. The CSS Engine (css) replaced some redundant components of the UIDL project. Additional engines for localisation and personalisation were created.

                Self-documenting

                With the help of Alex Shkotin from the Ontolog Forum, templates were designed for the Wiki Engine (wik) and Docs Engine (doc) to automatically populate and generate system documentation from hundreds of agents and thousands of processes. There are some test examples to look at.

                Structured learning

                IEEE Learning Objects were an inspiration for the Learning Object Engine (lob). This engine was used to structure learning materials using Diataxis to address users' diverse learning needs. The Help Engine (hlp) takes the same material to provide in-context help in the UI.

                i18n for every human language and writing system

                Using SIL and Unicode naming conventions, the Language Engine (lng) stores UI translations in multiple languages and writing systems, enabling Pipi capable of supporting all 7,000 known languages. Then the Locale User Interface Engine (lui) creates localised UI.

                Design System

                A Design System Engine (dsg) was built to handle multiple design systems, including a default one for the initial workspace UI. The design system includes UI components and design tokens.

                Security and permissions

                Role-based Access Control (RBAC) was implemented to manage security and user permissions. This applies to different types of user accounts and to finer-grained access.

                Useful URL patterns

                Clear URL patterns were established.

                Naming conventions

                A naming convention was adopted for output directories and filenames based on simple predictive rules.

                Ribbon menu

                A ribbon navigation menu (Tab Group) outline was created that could also be a non-ribbon navigation. One source, many formats.

                Workspace Version 1 (October - November 2025)

                A roadmap was first created to provide focus and clarity.

                Batch processes created 15,000 files and directories to form workspaces containing static HTML web pages for testing. Each workspace had a ribbon menu and used iframes to organise navigation and content. Testing is successful.

                The  industry-based enterprise workspaces created for testing were:

                The Workspace Version 1 trial revealed that the UI is a thin wrapper around Pipi.

                Workspace Version 2 (April 2026)

                Changes to Workspace Version 2 include;

                Additional role-based user account types were added.

                Changes to the workspace engine model.

                Changes to deployment naming convention.

                Documentation for standard Enterprise workspaces.

                Documentation for customer support.

                Documentation for account settings.

                Documentation for Developer Account.

                Documentation for Agent Account.

                The Render Engine (rnd) then uses a database to create workspaces made of static HTML web pages.

                • Test
                • Feedback
                Setting up data centre automation has revealed that workspace deployments need to be performed in this order of account types due to the permissions cascade.
                • Agent Accounts (to admin Pipi)
                • Researcher Accounts (to edit UoM, ontologies and physical laws)
                • Developer Accounts (to create enterprise workspaces)
                • Personal Accounts (to sort out personal profiles - UI fonts, etc)
                • Enterprise Accounts (to test and use the system for work)
                • etc

                Workspace Version 3 (May 2026)

                The Render Engine (rnd) uses a database to generate workspace ribbon menus as static HTML web pages.

                • Test
                • Feedback

                Workspace Version 4 (June 2026)

                The Render Engine (rnd), Learning Object Engine (lob) and Help Engine (hlp) use databases to generate workspace user in-context documentation as static HTML web pages.

                • Test
                • Feedback

                Workspace Version 5 (July 2026)

                The Render Engine (rnd) and Form Engine (frm) use databases to generate workspace forms as static HTML web pages. See the Pipi 4 example, which will also be used here.

                Workspace Version 6

                The Render Engine (rnd), Form Engine (frm) and Docs Engine (doc) use databases to generate a complete HTML workspace demo with connected initial developer documentation rendered without errors.

                • Test
                • Feedback

                Workspaces for Pipi & Developers

                Working Workspaces for System Admin and DevOps use are deployed in the Pipi Core Data Centre. This will speed up development and production x10.

                Then

                The process of providing cloud workspaces for customers will begin.

                Whaikaha Access Activator

                An application to attend the 8-week Whaikaha Access Activator 2026 May intake is being submitted to kick this off. Using the Govt.UK Design System as an example, a simple paper-based process to design and test workable UI templates for;

                • Autism
                • Colour-blind
                • Irlen
                • Dyslexia
                • Physical or Motor Disability
                • Epilepsy
                Blind and deaf folks will be catered for with later separate projects.