This presentation brings together key observations, solutions, and economic reasoning into one central argument: UKRIβs disruption-led strategy is economically flawed. Instead, we propose a collaborative infrastructure built on βοΈT10T β The Ten Technologies β as showcased through Sienna AI. Each section below is linked to detailed arguments and examples that justify this strategy shift.
The GOV.UK CMS β created in 2012 and barely updated β exemplifies how government technology fails without proper innovation infrastructure. We expose its dysfunction, compare it to modern standards, and show how our S-Web 6 Mothership CMS is what GOV.UK should have been. This also lays groundwork for collaboration with Microsoft or other capable tech leaders β not in opposition, but as a necessary correction.
Here, we refine the only defensible use of disruption: targeting foreign or domestic companies who pay little or no tax in the UK. We detail how HMRCβs own system failures prevent intelligent decision-making, and argue that HMRC tax data should be central to UKRIβs grant logic. If the government is to spend billions on innovation, it must ensure it isnβt funding the collapse of tax-generating companies in favour of flashy, short-lived replacements.
The closing argument. UKRI could build an entire nation-scale infrastructure from just 500 core functions β not 45,000 fragmented ones. The 10 Technologies is the blueprint. Sienna AI is the implementation. This section links to all related documents and pages explaining the technologies, the modular structure, and the global scaling plan. While brief, this final chapter is what gives the story its wings β because now the audience knows the alternative already exists.
Prologue: βοΈ T10T β Laying the Tracks for Macroeconomic AI
Despite a dedicated research and innovation agency with an Β£8.8 billion annual budget, there is no national technology platform in the UK. This, then, is a proposal to government and the private sector to start a serious conversation around building such a platform β one that could take the form of the 10 Technologies (T10T) framework or an equivalent with matching scope.
T10T is not specifically βan AI project.β Its foundations were laid in 2002, long before artificial intelligence entered the design. AI only became a consideration in 2016 with the Nudge CRM-AI design, and wasnβt formally added to the system architecture until 2022. That said, since 2016 β when the M-Systems framework was introduced β there was always a placeholder for an unknown final technology: S-World AngelWing, positioned at M-System 16, which would transfer the vast macroeconomic outcomes back into M-System 1: The S-World Network..
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S-World AngelWing β Supereconomics Software Framework with Butterfly Background, March 2020
In the simplified 2023 diagram, the mystery of AngelWing was clarified: Technology 10 β AngelWing represents βthe combinatorial explosion of the nine lower technologies and AI.β Here, AI becomes the powerhorse required to activate the full system, particularly when entangled with human operations via Mission Control QuESC β the Quantum Economic System Core. Together, they seek to perfect the Sienna AI T10T holy grail: Predictive Quantum Software.
Sienna AI β T10T Iceberg Diagram (v2) showing visible business layers and deeper macroeconomic systems, January 2025
This model does not forecast the future β it shapes it. Its architecture is not predictive in the traditional sense; instead, it mirrors a computational Feynman βsum over histories,β where all possible futures are explored and optimized for the most beneficial outcome. This is not science fiction β it is the software pursuit of PQS: Predictive Quantum Software. First imagined in 2012, PQS became the architectural father of the M-Systems from 2016 to 2020. From 2021 onward, it evolved into the central objective of the Ten Technologies (T10T) β shaping the economic future not by forecasting it, but by engineering it into existence.
Before we even touch on macroeconomic Technologies 6 through 9, we begin with direct impact. Our application for grant funding β βοΈβοΈGP-AI Gatekeeper 2025 β for Sir Keir Starmer and Wes Streeting β projected an economic gain of Β£112 to Β£147 billion when developed alongside its companion innovations: The Good Doctor App, GP-AI Psych, and GP-AI Physio. This projection is grounded in the study βEconomic Growth Gained by Returning 1% of the UK Population to Workβ. Noting that the worldβs largest hedge fund, Bridgewater Associates, identified workforce participation as the only long-term quantifiable macroeconomic growth factor β a point made clear in Rob Copelandβs The Fund (2023), which chronicles the firmβs founder, Ray Dalio, and his obsession with predicting macroeconomic trends.
The likely economic benefit of this technology extends far beyond the Β£112β147 billion projected for GP-AI Gatekeeper. The full suite of βοΈSienna AI medical technologies is designed to support far more than 1% of the population in returning to work. Moreover, Gatekeeper β alongside the other five modules that make up Sienna AI T10T β can be deployed across every sector of government.
Take HMRC, for example. When we spoke to Adam and Jess from HMRC support, they said it would be βa miracleβ if we created HMRC Gatekeeper. Itβs a little-known fact that HMRC customer service staff are not trained to help citizens complete tax forms. And yet, without any special training, GPT-4 was able to guide us through the entire process β no sweat.
When thinking about macroeconomics and national productivity, tax collection is arguably the single most critical system to optimise. And yet, as demonstrated in our GDS GOV.UK CMS Solution case study, HMRCβs technology is literally from the last century. Even worse, their current plan for company tax is not to upgrade β but to retire the system entirely, handing it off to third-party tools like QuickBooks that have no incentive to prioritise national economic efficiency.
When Gatekeeper logic is extended across departments β from education and local councils to justice and HMRC β we project that Sienna.gov T10T could increase UK GDP by 18β24% through systemic efficiency alone.
UKRI Logic Is Way Off
Instead of funding 45,000 individual projects at an average of Β£470,000 each β projects that no one else can access or build upon β UKRI could have used just 10% of its budget to create 4,500 shared, high-value tools that everyone can use. The logic behind creating tens of thousands of siloed, duplicate systems makes no sense in a digital era where microservice architecture allows us to build once and deploy everywhere.
Whether it's Sienna AI T10T or another universal framework, the UK urgently needs a core technology platform that supports every company and every sector of government. Contractors and developers wonβt lose work β theyβll simply be contributing to a shared system that improves life for everyone, not just one grant winner at a time. The same teams can be paid to build usable, well-documented, and interoperable systems β at a fraction of the cost it pays for siloed projects.
Nick Ray Ball (10 May 2025, 21:00): βSienna, please estimate the amount of taxpayer money that UKRI has received since 2016?β
Sienna (GPT-4o): βBased on the available data, UK Research and Innovation (UKRI) has likely received over Β£60 billion in total funding since 2016.β
This UKRI spreadsheet of all grant recipients since 2016 shows that despite this, only Β£20.4 billion has actually been granted β suggesting that approximately 65% of taxpayer money has been absorbed by administrative overheads. The scale of this inefficiency verges on the systemic. The term kleptocracy β used to describe the worst forms of institutional corruption during the Afghan war β may not be far off. (We have asked UKRI to dispute this figure. To date, they have made no comment.)
Over Β£60 billion has been spent on these isolated projects β yet the UK continues to slide toward recession, and in our GDS GOV.UK CMS problem analysis, we show how the underlying content management system still operates on a foundation built in the 1990s β software later repackaged for the cloud and presented as innovation. This isnβt just inefficient; itβs irrational. Itβs not about politics or ideology β itβs about logic, transparency, and value for taxpayer money.
To create GP-AI, HMRC Gatekeeper, and the full suite of Sienna AI modules β along with a major share of the systems specified in the 10 Technologies β would cost a tenth of what UKRI has spent. And rather than fueling decline, such a system could radically reverse the UKβs economic trajectory. We're not saying βchoose usβ β weβre saying: stop burning taxpayer money on siloed projects, and start building something the entire country can use. If not Sienna AI, then something with the same logic, scope, and ambition.
ππ§ The Macro Technologies 6, 7, 8 and 9
However, designing a truly unified platform β such as the 10 Technologies (T10T) framework β unlocks something far beyond departmental efficiency. It enables a class of tools we refer to as macroeconomic technologies: T6 through T9.
Sienna AI β T10T βThe 10 Technologies Design β May 2025
βοΈ T10T β Laying the Tracks for Macroeconomic AI
These systems go beyond saving money β they generate it. At scale, they enable the construction of new industries, intelligent cities, and whole economic landscapes β T9. Grand Εpin Networks. Together, they form SπRES Financial engineering β a sovereign economic operating system capable of Dynamic Comparative Advantage resource modeling, tax symmetries, and nation-scale reinvestment.
Where typical economic AI models aim to forecast, the 10 Technologies (T10T) is designed to shape the future. It is not a reactive tool β itβs an engine of strategic direction. Inspired by a chaos theory, string theory, quantum theory, macroeconomics, behavioural science, quantum loop gravity, and now generative AI. T10T was created not to guess what will happen, but to build systems so powerful and well-distributed that the outcome is no longer left to chance.
This is the difference between forecasting and engineering. Between waiting for economic cycles to turn β and turning them. Between data science and macroeconomic software.
With the full T10T platform in place, anchored by the combinatorial explosion of the nine lower technologies and generative transformer AI we move from siloed efficiency gains to an integrated economic operating system. A system that not only boosts GDP through tools like Sienna.gov & GP-AI Gatekeeper β projected to raise UK productivity by 18β24% β but opens the door to exponential growth through its macroeconomic tier: Technologies 6, 7, 8 and 9.
This is SπRES β The E-TOE (2017) - The Economic Theory of Everything, capable of unlocking new industries, cities, and taxation models (Tax symmetry the network is paid in output). Itβs not speculative: it is architectural. In the Malawi History 2 & 3 simulations We showed a 32X (3200%) Zero to One % of GDP improvement. weβve projected an 8x (800%) expansion of the UK economy within a decade β through a radical redesign of what government software can and should do.
At the heart of this vision lies the ultimate destination: PQS β Predictive Quantum Software. First imagined in 2012, it was born of the insight that while we may not predict what every person will do, we can design a system that moves entire populations toward better outcomes. T10T is that system β built not to model the future, but to make it.
All this before the high performance 6-module software design that is Sienna AI, Entangled with SπRES Preparing for implementation as described in the 2024 podcast
Sienna AI (2024)
The 2024 UK Butterfly model further evolved the macroeconomic system by entangling the core monetary and business engines with the Sienna AI Six Module Design: Quanta Analytica, the TBS-CC OKRs, Gatekeeper ALL-COMMs, S-Web 6 VC AI CMS, the Nudge CRM-AI, and the Swapping Menus Function.
This last innovation β the SMF β allows every business in the network to resell the products or services of every other, effectively turning social influence into a retail layer. Combined, these six technologies dramatically expanded the functionality of T1βT6, transforming macro simulations for advanced economies and raising the likelihood of success far beyond the pre-2022 models, which had focused primarily on developing nations.
In macroeconomic terms, the Sienna AI Six Module Design finally solved one of the hardest challenges in SπRES: enabling individuals to seamlessly exchange Network Credits for sovereign currency. This βtrade-layerβ logic, embedded deep within the commercial architecture of Sienna AI, gives governments a functional mechanism for both scaling and stabilising productivity.
This is the core insight of the Sienna AI 6M design: when stacked atop the SπRES growth model, it rewrites the economic rules for both developed and developing nations. In 2021 β before AI was formally integrated β the model projected $1,039 trillion in global growth by 2080, based entirely on simulations from the worldβs poorest economies. It began with Malawi β a deliberately hard test case, then ranked at the very bottom of the World Bankβs global GDP per capita list. Again and again, the Malawi History 3 simulation lifted it from 0% to 1% of global GDP by 2080. These werenβt optimistic forecasts β they were minimum baselines engineered to succeed under the harshest economic conditions on Earth.
This is the core insight of the Sienna AI 6M design: when stacked atop the SπRES growth model, it rewrites the economic rules for both developed and developing nations. In 2021 β before AI was formally integrated β the model projected $1,039 trillion in global growth by 2080, driven primarily by applications in the Global South.
But in 2023, we discovered that by using price itself as the API variable β rather than relying on third-party software endpoints β the system could regulate inflation directly. This breakthrough made the platform applicable to advanced economies too, laying the groundwork for global integration through the Sienna AI 6M design.
Sienna AI, then, is not just a cherry on top. It is the interface layer, the operating system, and the monetisation engine of the T10T platform β a platform built not to react to economic decline, but to engineer prosperity into the system itself.
