Two Breakthroughs This Year

This still holds true from when we devised this at the beginning of the year, but since then, two breakthroughs have emerged to push the whole idea forward.

Automation of automation (Master Prompts)

First, it may be possible to ‘automate the automation’. Since GPT-5 came out in early August we’ve seen how much better it is at multi-step problem solving, instruction-following for complex and evolving tasks, and invoking additional ‘tools’ as and when required. And with these new capabilities we’ve found it is possible to develop ‘Master Prompts’ that allow you to enter a workflow and the models work out the entire input/process/output/example framework and build the series of prompts required.

In effect a prompt can create ‘Prompt Packs’.

Now this is at an early stage but the technology has developed to such an extent that a lot of shortcuts to the future are now available.

Practical Agents (Agentic AI)

The second breakthrough to emerge is that the long-forecasted world of ‘Agentic AI’ is arriving fast. Whilst still somewhat brittle, the idea of creating discrete software services that can be given instructions and that can then be left to autonomously work out how to complete them, is coming to pass. Anyone who has used ChatGPT Agent will have experienced the rather odd sensation of watching a virtual entity thinking and acting its way through a problem whilst boxed in a computer within a computer.

This is opening up a whole new world of opportunity and whether more robust forms of Agents take 3, 6, 9 or 18 months to arrive, they will definitely be arriving. And so one can plan for them.

From Prompt Packs to Agents

Which means that in the near future we are very likely to see large swathes of the real estate industry become industrialised. Prompt Packs will naturally morph into collections of Agents.

Just as lean manufacturing, via ‘The Toyota Production System’, codified shop-floor know-how into standard work instructions, Agentic AI will be doing the same for CRE.

Now, ’The Toyota Production System’ is one of the most consequential management innovations of the 20th century — arguably as influential to industrial organisation as double-entry bookkeeping was to finance.

The fundamental point is that the concept of codifying tacit knowledge is hardly new in management thinking. So real estate should not be surprised that it appears to be finally reaching our industry.

There are already domain specific AI companies offering a range of services dealing with high value, document heavy and repeatable real estate workflows. Where this ‘Prompt Pack/Agentic’ framework differs is that it applies to all the other workflows one has to deal with day-to-day that do not merit VC backed startups addressing. The implementation of ‘Prompt Packs/Agents’ will be led by all of us. Each creating our own swarm of virtual helpers to suit our particular needs.

As we’ve​ discussed before​ , the days of us being ‘Agent Bosses’ are near. We’ll create, monitor and curate these tools. We’ll industrialise ourselves!

So, between the high-end outsourced agent creators and our ‘build your own’ efforts, a huge amount of what we’ve been paid for as an industry in the past is about to be automated.

Critical Questions

Which leads to some critical questions:

1. Do we buy or build?

It has long been unfashionable within real estate to entertain industry players building their own technology. Always better to buy in technology from specialists has been the mantra. On the basis that ‘you don’t know what you’re doing, don’t have the talent, and can’t afford to do it properly’.

Today the tables are turned. Given the ease with which a lot of new tools can be developed, or utilised, every real estate company needs to build a level of technical competency, or at least literacy, in-house. You need to know what you’re doing, you need technical talent, and now YOU CAN afford it.

2. If we buy, what does that mean?

‍As we’ve seen, ‘Prompt Packs’ and Agents are going to become easy enough to create and curate in-house, but for the heavy lifts you are going to need help from the AI services companies working on things such as Lease Extraction, Asset Performance Reporting and ESG Analysis.

These are high value, repeatable tasks that are complicated and nuanced - but they can be largely automated. Just not, most likely, by you.

Which means that, unless you are a large player who SHOULD be building this capability in-house, over time the value in this work will accrue to the AI service providers. If you are using someone else’s tools you are vulnerable to being commoditised. And most likely will be.

AI unbundles knowledge from jobs, and reduces the cost of intelligence. Value will move to those that enable this.

The strategic trade-off is clear:
Build = defensibility, talent, control point.
Buy = speed, commoditisation risk, margin erosion.

3. If the ‘machines’ are doing all this work, what are we humans supposed to do?

‍This is not nearly as hard, or as worrying, as often stated. You just have to be clear about relative competencies. Think of it like this:

AI provides:

• Rapid processing of complex, multi-dimensional datasets
• Identification of patterns humans might miss
• Consistent analytical frameworks across large portfolios
• Probabilistic insights to inform human decision-making

Humans provide:

• Market context and nuanced interpretation e.g Local knowledge, regulatory nuance
• Strategic judgment and risk assessmente.g Portfolio capital allocation, risk appetite.
• Stakeholder relationship managemente.g Tenant trust, investor alignment.
• Creative problem-solving for novel situationse.g Complex mixed-use repositioning, adaptive reuse.

Changing Assumptions

So you need to be paying huge attention to what we discussed in ‘​AI Fluency is Not Enough​’ - as AI removes existing constraints (eg intelligence) it creates others (eg data, coordination and trust). You need to be over-indexing on how the above will reshape the industry.

• Where can we add value?
• Where can we act as a ‘control point’?
• How can we absorb customer risk and guarantee an outcome?
• How can we change the story - what was expensive is now cheap, but you now need XY or Z.

And above all else, changing your assumptions about the future:

• What constraints within our industry will go away, but what will endure?
• What do we need to know that we did not know before, and how long will it take for us to acquire this new knowledge?
• What coordination problems will be commoditised (for example which reports)?
• What will be defensible - of those four ‘Human’ skills listed above which ones am I/We strongest at?
• Should I be updating my five-year plans to two. Or one?

OVER TO YOU

Ask yourself:

• Which of my workflows are most at risk of commoditisation?
• Where can I act as a control point?
• Which human skill is my differentiator?
• What’s my planning horizon — five years, or one?

** Obstacles remain, of course, such as fragmented data, tacit knowledge, and organisational inertia. But the trajectory is clear: agents will chip away at each, and this rebundling will force CRE leaders to redefine where they add value.