A roadmap for accelerators

Mike's Notes

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

Resources

• https://thespinoff.co.nz/business/16-10-2019/the-ministry-of-awesome-reflects-the-exciting-new-era-of-christchurch-startups
• https://creativehq.co.nz/stories/access-activator-successful-applicants/
• https://creativehq.co.nz/stories/wellingtons-creative-tech-scene-has-a-new-starting-point/
• https://www.sproutagritech.com/sprout-accelerator/
• https://ministryofawesome.com/founders/
• https://rowansimpson.com/essays/
• https://steveblank.com/tools-and-blogs-for-entrepreneurs/
• https://www.kiwisaas.com/
• https://my.nzte.govt.nz/essentials/export-essentials-saas

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 https://steveblank.com/tools-and-blogs-for-entrepreneurs/ The Startup Owners Manual
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 https://www.kiwisaas.com/
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 https://startupaotearoa.org/ https://www.blog.ajabbi.com/2025/06/some-initial-notes-on-what-my-first.html
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 https://creativehq.co.nz/adapt-for-the-future/explore-courses/
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 https://my.nzte.govt.nz/essentials/export-essentials-saas
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 https://my.nzte.govt.nz/courses/intro
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 https://cloud.google.com/startup?hl=en https://www.blog.ajabbi.com/2026/02/having-data-centre-changes-roadmap.html
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 https://www.sproutagritech.com/sprout-accelerator/ https://www.blog.ajabbi.com/2025/11/workspaces-for-agriculture.html https://www.blog.ajabbi.com/2026/02/waimumu-field-days-background-to-ajabbi.html
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 https://cloud.google.com/startup?hl=en

The AI advertising wars

Mike's Notes

This is an extract from a recent thoughtful SubStack post by Gennaro Cuofano, in The Business Engineer. The post discusses the AI advertising wars. This extract is about recent changes at the newly formed Agentic AI Foundation, a Linux Foundation initiative.

"What we’re witnessing is the emergence of a complete protocol stack for agentic commerce. Understanding how these pieces fit together reveals both the competitive dynamics and the cascading implications for the digital ecosystem." - Gennaro Cuafano

Note to self

• Create a Pipi MCP Engine.
• Look into the open-source protocols at the Agentic AI Foundation.

The post also discusses the war around payment protocols.

Resources

• https://businessengineer.ai/p/the-ai-advertising-wars
• https://substack.com/@thebusinessengineer
• https://aaif.io/
• https://www.linuxfoundation.org/press/linux-foundation-announces-the-formation-of-the-agentic-ai-foundation
• https://block.xyz/inside/block-anthropic-and-openai-launch-the-agentic-ai-foundation
• https://agentics.org/
• https://en.wikipedia.org/wiki/Linux_Foundation#Agentic_AI_Foundation
• https://en.wikipedia.org/wiki/Model_Context_Protocol

References

• Reference

Repository

• Home > Ajabbi Research > Library > Subscriptions > The Business Engineer
• Home > Handbook > 

Last Updated

28/01/2026

The AI advertising wars

By: Gennaro Cuofano

The Business Engineer: 27/01/2026

Creator of The Business Engineer, the deep-tech research hub, spun off from FourWeekMBA, the leading blog on business model strategy. Gennaro has over 10 years of experience as a deep tech executive.

...

The Protocol Stack: Five Layers of the New Commerce Architecture

What we’re witnessing is the emergence of a complete protocol stack for agentic commerce. Understanding how these pieces fit together reveals both the competitive dynamics and the cascading implications for the digital ecosystem.

Layer 1: Foundation Infrastructure

The foundation layer has effectively been won by the Model Context Protocol. MCP, launched by Anthropic in November 2024, has achieved what few technology standards accomplish in a single year: industry-wide adoption backed by competing giants. The numbers tell the story:

• 97 million monthly SDK downloads
• 10,000+ active servers
• ~2,000 entries in the MCP Registry (407% growth since September)
• First-class client support across ChatGPT, Gemini, Microsoft Copilot, Cursor, and VS Code

In December 2025, Anthropic donated MCP to the newly formed Agentic AI Foundation under the Linux Foundation. This wasn’t an act of charity but strategic positioning—by making MCP vendor-neutral, Anthropic ensured its protocol would become critical infrastructure rather than a competitive weapon that might be forked or abandoned. As Mike Krieger, Anthropic’s Chief Product Officer, put it:

"A year later, it’s become the industry standard for connecting AI systems to data and tools.”

MCP now sits alongside two other founding projects under the AAIF:

• AGENTS.md (OpenAI): Adopted by 60,000+ open-source projects for providing AI coding agents with project-specific instructions
• goose (Block): An open-source, local-first agent framework
• Agent2Agent / A2A (Google): Enables communication between autonomous agents, supported by 150+ organizations

The significance of this consolidation under the Linux Foundation cannot be overstated. These protocols are becoming the TCP/IP of the agentic economy—essential infrastructure that no single company controls but upon which all higher-value services depend.

Layer 2: Payment Infrastructure

The payment layer remains more fragmented. Google’s Agent Payments Protocol (AP2), co-developed with PayPal and backed by over 60 merchants and financial institutions, provides secure payment tokenization for agent-initiated transactions. It’s designed to work seamlessly with Google Pay and the broader Google commerce ecosystem.

The payment processor alignment is telling:

• Stripe → OpenAI’s commerce stack (Shared Payment Token, Agentic Commerce Suite)
• PayPal → Google’s AP2 + Perplexity’s commerce features

This isn’t neutral infrastructure—the payment processors are choosing sides in the protocol wars, betting on which business model will dominate.

Layer 3: Commerce Infrastructure—The Battlefield

This is where the war is actually being fought. Two competing protocols with fundamentally different architectures and business models are vying to become the standard for agentic commerce.

Google’s Universal Commerce Protocol (UCP), announced at the National Retail Federation conference on January 11, 2026, was co-developed with Shopify, Etsy, Wayfair, Target, and Walmart, with endorsement from over 20 partners including Visa, Mastercard, American Express, Stripe, Best Buy, and Zalando.

UCP is a full-journey protocol covering:

• Product discovery
• Cart management
• Checkout
• Post-purchase support
• Loyalty programs and returns (roadmap)

The architectural philosophy is revealing: UCP establishes a common language through which agents can discover merchant capabilities, negotiate supported features, and execute transactions. Merchants publish their capabilities via a .well-known/ucp file, agents discover what’s available, and transactions proceed through standardized primitives.

OpenAI’s Agentic Commerce Protocol (ACP), launched in September 2025 in partnership with Stripe, takes a narrower approach. ACP is checkout-focused—it solves the “last mile” of completing a purchase rather than the entire shopping journey. The protocol is Apache 2.0 licensed and explicitly designed to work across payment processors and AI platforms.

ACP’s architecture reflects OpenAI’s strategic position: they don’t need to own discovery (ChatGPT’s conversational interface handles that) or post-purchase (merchants handle fulfillment). They need to capture value at the moment of conversion. For merchants already on Stripe, enabling agentic payments requires as little as one line of code.

The scope difference is intentional. UCP gives Google a reason to keep merchants within its ecosystem across the entire customer journey. ACP lets OpenAI capture transaction value wherever discovery happens.

...

Unix Mindset: MCP Is Unix Pipes for AI

Mike's Notes

"The Model Context Protocol (MCP) is an open standard, open-source framework introduced by Anthropic to standardise the way artificial intelligence (AI) models like large language models (LLMs) integrate and share data with external tools, systems, and data sources. Technology writers have dubbed MCP “the USB-C of AI apps”, underscoring its goal of serving as a universal connector between language-model agents and external software. Designed to standardise context exchange between AI assistants and software environments, MCP provides a model-agnostic universal interface for reading files, executing functions, and handling contextual prompts. It was officially announced and open-sourced by Anthropic in November 2024, with subsequent adoption by major AI providers including OpenAI and Google DeepMind." - Wikipedia

Resources

• https://www.linkedin.com/pulse/unix-mindset-mcp-pipes-ai-kingsley-uyi-idehen-xwiue/
• https://www.linkedin.com/in/kidehen/
• https://modelcontextprotocol.io/introduction
• https://en.wikipedia.org/wiki/Model_Context_Protocol
• https://gemini.google/overview/canvas/
• https://www.openlinksw.com/data/html/unix-mindset-pipes-mcp.html
• https://virtuoso.openlinksw.com/
• https://opal.openlinksw.com/
• https://blog.modelcontextprotocol.io/posts/2026-07-28-release-candidate/

References

• Reference

Repository

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

Last Updated

28/05/2026

Unix Mindset: MCP Is Unix Pipes for AI

By: Kingsley Uyi Idehen

LinkedIn: 01/06/2025

Founder & CEO at OpenLink Software | Driving GenAI-Based AI Agents | Harmonizing Disparate Data Spaces (Databases, Knowledge Bases/Graphs, and File System Documents).

The “Unix mindset applied to AI” is a compelling paradigm that draws from Unix’s foundational design philosophy and applies it to AI systems architecture. It’s a powerful insight I came across while digesting a recent presentation by Reuven Cohen.

Here’s how Unix pipes and the Model Context Protocol (MCP) embody this approach:

Unix Philosophy Core Tenets

The Unix philosophy revolves around several key principles:

1. Do one thing well – Build small, focused tools instead of monolithic applications
2. Composability – Chain simple tools to create complex workflows
3. Universal interface – Use text streams as a common data format
4. Modularity – Favor loosely coupled components that can be mixed and matched

Unix Pipes as the Model

Unix pipes (|) are the quintessential example of this philosophy. You can write:

cat data.txt | grep "error" | sort | uniq -c | head -10

Each tool (cat, grep, sort, uniq, head) performs one task exceptionally well. Together, they form a powerful, composable data-processing pipeline. The magic lies in composition, not in any single tool.

MCP Protocol: Pipes for AI

The Model Context Protocol extends this Unix mindset into the world of AI:

1. Standardized Interfaces – Like Unix pipes use text, MCP uses standardized JSON-RPC protocols for AI-tool communication—providing a universal interface for AI systems to interact with services and data.
2. Composable AI Workflows – Rather than building monolithic AI systems, you can compose:Data connectors (to databases, APIs, file systems)Processing tools (calculators, web scrapers, code interpreters)Specialized models (e.g., for vision, reasoning, code generation)Output formatters (to generate documents, charts, or dashboards)
3. Tool Interoperability – Vendors can create MCP-compatible tools that work together seamlessly—just like Unix tools from different sources pipe into one another without friction.

Practical Applications

This enables streamlined, reusable AI workflows such as:

Document → Semantic Analysis → Content Transformation → Data Lookup → Formatting → Publication 

Each step is a focused component that adheres to MCP protocols. You’re not locked into a single vendor’s ecosystem—you’re free to mix the best tools for the job.

The Broader Vision

This marks a shift from AI as a black box to AI as composable infrastructure—where intelligence is modular, interoperable, and infinitely reusable, just like the Unix tools that have underpinned computing for decades.

BTW — Google Gemini’s Canvas now includes an HTML-based infographic generator, which I used to create an interactive visual version of this concept. It also includes rich metadata, offering yet another showcase of the powerful symbiosis between recent Large Language Model (LLM) innovations and the long-established (and now increasingly appreciated) power of structured data representation—rooted in the same conceptual tenets that gave rise to the World Wide Web: Linked Data Principles (where entities and entity relationship types a named using hyperlinks).

View of the Infographic version of this article using the OpenLink Data Sniffer Browser extension for discovering and visualizing document metadata

You can view the Infographic by clicking on the link below:

• Unix Mindset, Pipes & MCP for AI: An Infographic

This is the kind of flexibility and power our Virtuoso platform delivers—seamlessly combining Data Spaces with a full-featured Web Application Server.

If you haven’t yet explored Virtuoso—or its new OpenLink AI Layer (OPAL) add-on—you’re missing a direct path to harnessing the transformative potential of AI that’s redefining the future of software.

Why wait? The future is composable, interoperable, and agentic—and Virtuoso gets you there, faster.