Trillion Dollar Hashtag - Logo SVG
Subscribe Now
Trillion Dollar Hashtag - Logo SVG
Issue #
26

The Great Acceleration

AI is unlocking 10x speed and game-changing power—transforming how we work, innovate, and outsmart the competition.

The Great Acceleration
‘Even for me, despite spending most of every day using Generative AI, there are still moments when one’s jaw drops’

Executive Summary

Generative AI is evolving rapidly, providing businesses with unprecedented tools to innovate and outperform competitors. This newsletter shares concrete examples of AI delivering remarkable results at 10x speed, highlighting both jaw-dropping potential and critical strategic considerations.

Superpowers Unleashed

ChatGPT was launched on November 30th, 2022, as a ‘research project’ by OpenAI. Supposedly there was no fanfare, indeed many in the office didn’t even know it had happened. They were expecting maybe a few thousand hardcore AI researchers and enthusiasts to look at it over the weekend. Instead, within five days it had seen one million users. And their woefully underpowered hardware infrastructure was struggling to stay up. In fact it kept falling over. ‘The GPUs are melting!’ one engineer exclaimed.

Within two months they’d reached 100 million users, and now, two and a half years later, they are receiving 800 million unique users a week. And they are still ‘constrained’ by a shortage of GPUs.

As a user, what has been most striking is the rise in capabilities of the frontier models, and the introduction of so-called ‘reasoning models’ which instead of rapidly spitting out a response based on the statistical model embedded in their training data, precede every answer by following a ‘chain of thought’ process that enables them to build a more robust and fleshed out response. And then, in the last few months, we’ve seen new models released that have ‘agentic’ capabilities, meaning that they are not constrained by language alone, but can call on a range of other tools to assist in answering a question.

Put these together and you get both ‘jaw dropping moments’ and access to ‘superpowers’. And that means all of us, not just an elite few.

I’ve long encouraged participants in my #GenerativeAIforRealEstatePeople course to push models hard, and be unreasonable in what you ask for. As they often surprise you as to what they are capable of. As every month passes I shout this message louder.

In my last cohort, during a session when we work through a ‘Prompt Library’ we have on the course, I asked this of ChatGPT’s ‘reasoning’ model o3:

“Identify three European secondary cities that are likely to see above-average growth in life-science real-estate demand over the next five years. Weight your scoring model 40 % macro-economic indicators, 30 % venture-capital inflows, and 30 % university R&D intensity. Show your working in a Python table, cite external data sources, and finish with an executive-summary paragraph.”

Having not tested this out I was amazed as the model thought and thought and thought (for several minutes) and then proceeded to output, stage by stage, a rather extraordinary answer. In the process, it performed various web searches, ran Python code to perform calculations, and worked back and forth over the question until producing a neatly formatted table comparing several cities across multiple criteria, and an exceptional conclusion.

It was the first time I had seen evidence of these new ‘agentic’ capabilities, and I have to say I started laughing, because the results were so extraordinary.

Simultaneously I had a feeling of doom - ‘we are toast’ - because this was so good a response that one wondered what on earth us humans are going to do in the future, and a feeling of elation because, if you look at the glass half full, you think ‘wow, what amazing things are ‘we’ going to be able to do soon’.

Either way, you can try this out yourself. Let me know what you think.

(Interested in sponsoring this section? Let’s connect.)

Case Study: Using AI to Solve the Geovation Challenge

Similarly, over the weekend I was reading about the UK Government’s Geovation arm and their ‘PropTech Innovation Challenge’, and wondered if AI could help with this. So I took one of their ‘Challenges’ -

‘‘How might we transform currently siloed and proprietary land ownership data into an open and interoperable resource that accelerates the conversion of potential development sites into tangible housing projects?’

And thought about how I could answer this with the help of my ‘AI Friends’.

Iterating with AI

So I did this: Wrote a prompt incorporating all the details about the ‘Challenge’ and ran it through:

  • Gemini Deep Research
  • Google’s AI Studio (aistudio.google.com) - Gemini 2.5 Pro
  • Perplexity
  • Claude, with ‘Extended Thinking’ enabled
  • ChatGPT Deep Research using o3

Then I took all the responses, converted them into pdfs and uploaded them to Google’s NotebookLM. This allows you to interrogate multiple ‘sources’ (which can be text, audio or video) at once, in a way that focuses exclusively on those sources. Which means answers are very constrained and largely free of ‘hallucinations’.

I then spent some time pulling out the main themes from the responses, and asking for orthogonal ideas. This ended up with a synthesis of all the responses and a breakdown of the best ideas and concepts from each.

Having established that the best overall response was from ChatGPT’s o3 model, I then went back to it to ask it to incorporate the best ideas that emanated from the other models. Checking to see that they worked together, and did not contradict each other.

Rather remarkably it then went through a lengthy process where it found the appropriate places to insert the other’s ideas, before coming back and asking ‘would you like a newly created response’?

And then gave me a little over 16,000 words of detailed, comprehensive, remarkably coherent response.

I then uploaded this new version (including the updates) and the original version back into Gemini 2.5 Pro in Google’s AI Studio and asked it to critique the two versions and tell me which was best. Pleasingly it said the updated version was the winner.

Then I uploaded this final version, together with the original Geovation ‘Challenge’, plus their scoring metrics, and asked Gemini to critique the work as if they were a judge..

And received back a very high rating and positive judgement.

Had it not been so good I would have then dug into weaknesses, and iterated the report.

Finally I listened to the whole report - using the Eleven Labs Reader App - checking for content and citations.

All excellent.

If I was doing this for real I’d have done it with a Planning domain specialist, to further steer the process and tweak the output. If I had, I'm pretty certain our submission to Geovation would be as good as anyone else’s. Maybe even win the prize. (Curious to see the full 16,000-word AI-generated report? You can ​view it here​).

Lessons for the Future of Work

So this on its own was a remarkably good result. But the killer aspect to it all was that it was done in a matter of hours. As opposed to the weeks or even months it would take without AI assistance.

Which makes you think about the nature of ‘work’ going forward. Put simply, AI is going to enable us all to do a lot more. When a project takes days you can do a lot. Most notably you can also do things in depth in areas you never could before because you could not justify, financially, the cost of doing so.

These tools will enable us to apply more innovation, to more areas, at 10X the cadence we’ve been used to.

And that is where I think, with the right mindset, we’ll really benefit from AI. It is very easy, and understandable, to be concerned about ‘the machines’ taking over and wiping out jobs. But if you zoom out a bit, and think of all the things we either do not currently do, or do not do very well, and then consider how AI could enable us to do them all, and do them to a very high standard, you start to see where ‘the bigger pie’ is that we can build.

We definitely do need a ‘bigger pie’ or the work available will not keep ‘idle hands busy’ but truth be told, across all businesses, we probably only do a fraction of things really really well. And so much does not get done. But with AI, we could feasibly tackle it all, and with far greater finesse.

Let’s put these superpowers to good use.

Over to you

Within your business, being honest, what don’t you do all that well? And what would you like to do if it cost you a tenth the time and money? How much better could your company, or work, be?