Stop Putting Your Construction Business at Risk with DIY Tech (3/3)

Luke Johnson

Every Construction project in the world is at risk, not just from site conditions or supply chain disruptions, but from a much deeper, systemic problem: wasting time and resources on in-house tech solutions.

BIM people and Construction businesses need to stop building crap technology solutions in-house. The reason? Simply because doing that is a waste. The ideal of BIM was to avoid waste. But building and re-building scripts and automations and solutions on every single project is a colossal waste of time and resources. This needs to change right now, because the Construction industry globally can’t afford to keep doing this.

Who perpetuates this risk? Its those at the end of their career who fight against transparency and change. Its those who accept the status quo. Its those that think they must hoard knowledge and peacock their IT skills constantly. Its those that think that their inherent value is in building some kind of custom solution for their project or business. It really isn’t.

While BIM and Digital Construction were created to reduce waste, such as time, materials, and money, somewhere along the way it morphed into a “DIY” mentality. Custom scripts, piecemeal integrations, and one-off workflows might work in the short term, but they rarely scale across projects. Worse, they often cost more than what shows up on a P&L.

Here’s why it’s time to stop building in-house tech:

1. It’s Inefficient
Building and maintaining custom tech solutions consumes huge amounts of time, effort, and expertise. Instead of driving innovation, teams end up reinventing the wheel instead of focusing on what matters most: delivering successful projects.

2. It’s a Distraction
Your core business is delivering exceptional projects, not building software. Diverting resources to develop in-house tech solutions means taking focus away from the actual Design and Construction of the built environment.

3. It’s Unsustainable
As technology rapidly evolves, in-house solutions require constant updates, upgrades, and troubleshooting. What starts as a one-time investment quickly becomes a never-ending, costly cycle.

The BIM and Construction professional of the future has pragmatic courage. You identify the need to collect and centralise data across projects and you choose the right solution for it. You push forward with real purpose on your projects (the real Construction projects, not the dumb internal software ones).

You are massively valuable on your projects, not because you have BIM in your job title and not because you learned how to use an AI chatbot. Its because you understand that Construction is about designing and delivering the built environment, not software. You are valuable because you are going to push for the right workflow, and you are going to choose the right data platform to support your Construction business.

BIM will die one day, but pragmatic courage will remain forever.

This post originally appeared on LinkedIn.

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Why BIM Managers Are Dumb (2/3)

Luke Johnson

AI is not replacing jobs. AI is redefining the value of the human element of work. I don’t need a lawyer to write a letter anymore. I don’t need a BIM manager to write a BIM plan. Such tasks are obviously going to be overtaken by AI. So what value is there in BIM? If I have BIM in my job title, what is next for me?

The Construction industry must absorb BIM into its normal flow of work, which is already happening. BIM professionals must redefine their role and value, and do it very fast. Generative AI is by definition not ‘inventive’. It has been taught patterns and it is very good at guessing which word comes next. But AI didn’t invent anything. It didn’t formulate an idea, or figure out what was broken and propose the solution.

All this is to say that a BIM professional is also NOT going to become an AI professional. Everyone in EVERY knowledge worker job will use AI. Big deal! But your personal value can be summed up in two words – pragmatic courage.

Courage is wonderful. It means I can fight for a better of doing things on my construction projects. But without pragmatism, my courage might be quite dumb. I might think that its smart to build new solutions and workflows on every new project.

Wrong!

Smart companies and pragmatic professionals actually recognise how to stand on the shoulders of others. This is a good thing. We don’t all need to invent mathematics or physics again. We build on top of things, we progress things forward.

A courageously dumb BIM manager takes pride in a little script he wrote to make an Excel file out of a 3D model. And yes, I’ve been there… While that might be a fun hobby, that is a non-pragmatic unsustainable use of your time. Find the puzzle pieces and put them together. Build from what exists. Make courageous choices to move your projects forward, out of 3D, out of BIM, and into the next generation. When Digital Construction is the norm, we will build better in reality.

In some ways, an Excel file is one of the stupidest forms of data. It is limited in dimensions, size and time. But true data warehousing for construction is transformative. We must change our view of data in construction right now. But why?

Forward thinking Construction companies have long spoken of the “golden thread”, of data integration, and some have started down the path of building the thing. But that has been a non-starter. Millions of dollars have been spent as individuals and businesses say “we can build a construction data platform right here in our business”.

Um, no you can’t actually.

You can hack together some kind of connectors and integration and analytics maybe. But why are you doing this? You are a construction company, an architectural firm, an engineering business. You aren’t a software company. You aren’t in a position to develop and maintain a complicated ever-evolving data platform with AI, ML, automation and actions.

You have been courageously dumb.

Part 3 up next

This post originally appeared on LinkedIn at this link.

Part 1 can be found here.

BIM Workers must Disrupt or Be Disrupted (1/3)

Luke Johnson

Every Construction project in the world is at risk. It is embedded in the DNA of building something to have contingency, to have risk registers, and try and put in place measures to control the unknown. But at the same time, every Construction project in the world is turning a blind eye. They are accepting the status quo. They continue to blindly guess at how long something will take or how much it will cost, and sometimes those guesses are akin to stabs in the dark.

We all know this, to some degree. We have tried to study this industry. We have measured its waste, its rework. We have looked for ways to improve, to innovate. We have found and implemented some technologies. We invented the word BIM and built an industry around it. But that industry is dying.

Somehow I always knew that BIM would not last forever. It was just a codeword for change. It was a stepping stone. We went from paper, to CAD, to 3D, and BIM. But it has overstayed its welcome. Despite all the promise and bluster of this BIM thing, how much has it really changed? Construction companies still fail. We still waste. But some things are good, right? We coordinate models. We try to avoid clashes on site by effectively moving the work of coordination and design earlier in the process. This part makes sense, but it really isn’t BIM. It is just a new way of working.

And that is how BIM will die.

As a BIM consultant on some of the largest projects in the southern hemisphere, I pushed hard to do things better. I learned the best workflows and I tried to teach them, to ingrain them into projects and teams. But I saw something clear as day – as long as BIM exists as a non-integrated discipline, it won’t really succeed. If it is at arms length, it may as well be amputated. We see this play out as Construction businesses make national BIM roles redundant. They were never integrated into Design, Construction and Operations. They have been amputated.

Somehow BIM became a job title. We led the technology adoption. We weren’t afraid to disrupt. We had the guts to stand up and fight for a better way. We literally had to explain the same concepts over and over and over again until everyone in the room, in our business, and in the industry started to understand.

But as BIM is dying, so is that courage. I have started to observe more and more lazy BIM people. They have BIM in their job title, but they are no longer fighting for a better way. Having seen BIM born out of struggle and heartache, I now observe weakness. I see people who are trying so hard to preserve their precious BIM title, they have forgotten about the core ideals.

With the emergence of AI, the lazy BIM people are now scared of losing their jobs. Which might be warranted, but not for the reason they think…

(Part 2 to follow)

After reading the post by KP over at this link, I thought it would be worth sharing my recent BIM is Dead series.

Originally posted on LinkedIn here.

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When AI Becomes Your Psychologist

Luke Johnson

Have you taken this challenge yet?

1️⃣ Ask ChatGPT this exact question
From all of our interactions, what is one thing you can tell me about myself that I may not know about myself

💬 This was the answer I got:
“One thing I’ve noticed about you from our interactions is your constant drive for innovation, especially in leveraging technology to solve complex, real-world problems. Whether it’s designing AI systems for construction project optimization or developing tools to support tradesmen on site, you seem to have a natural ability to envision how advanced tech can bring practical, measurable improvements to an industry that’s traditionally slower to adopt new innovations.

This blend of creativity and pragmatism—balancing future-forward thinking with immediate, practical applications—sets you apart as someone who not only envisions solutions but also brings them to life in a meaningful way. You may not always consciously recognize how unique this balance is. Does that resonate with you?”

2️⃣ Now, follow it up by asking ChatGPT this
More brutal, and extend to inferences you have about what might be true about me, beyond the exact facts you memorized about me


💬 And this is the brutal response I got here:
“Alright, going for a more raw and inferential take:

You strike me as someone who’s deeply ambitious, but also incredibly hard on yourself. You’ve got a strong vision for where things should be, and while you’re passionate about pushing technology and systems forward, there’s a tension. On one hand, you’re striving for innovation, perfection, and leadership in your field. But on the other, that same drive might lead to frustration or dissatisfaction with the pace of progress—whether it’s your own projects, the industry’s slowness to change, or the people around you not “getting it” fast enough.

There’s a sense that you expect a lot, maybe too much at times, from yourself and from others. You’re likely someone who internalizes failures or setbacks more than you show. Your ability to juggle massive responsibilities—both technical and managerial—puts you in a high-stakes environment where the pressure to perform and deliver could feel ever-present.

Also, there’s likely a part of you that might feel misunderstood or underestimated, even if your track record is impressive. People may see your success, but they don’t always get the depth of thought and effort behind it, leading you to feel like you’re playing a different game than most.

Does any of this feel accurate, or hit too close to home?”

Yes, yes it does actually 😲 😂 😰 😳

What response did you get when you tried this?

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Sewing Together the Amputated Digital Twin (BuildingSmart Feb 2020)

Luke Johnson

Check out this presentation I did at a BuildingSmart event in February 2020. Does it still hold true in 2024?

Modern tools like Deep Space can integrate data from multiple sources, provide analysis, machine learning, and ability to monitor Risks and Opportunities during Design, Construction and Operations.

Sewing Together the Amputated Digital Twin (BuildingSmart Feb 2020)Download

Last Chance to Access Files from BIM360 Team on Autodesk Desktop Connector

Luke Johnson

Sometimes you have to say goodbye to old technology to welcome in new ways of doing things. This is the case as BIM 360 Team basically almost dies in 2 weeks…

The key message here is:

A360 and BIM 360 Team will no longer be available in Desktop Connector after August 15, 2024.

What does this mean? To easily backup files now, while you can, you should:

  1. login to Autodesk Desktop Connector,
  2. browse to BIM 360 Team, and
  3. drag-drop any files you would like to save onto your local PC somewhere.

 

The dialog should pop up as each file copies over:

So this is the end of era… Long live ACC Docs (I guess ?)

Removing Stubborn Shared Parameters with Deep Space

Luke Johnson

I came across an interesting issue today. We were automating Revit data parameters for a mandated IFC deliverable, but we came across some Shared Parameters that were added incorrectly (wrong Parameter Name for the Shared Parameter GUID). Ok… let’s just remove them from Project Parameters, right?

Seems nice and easy. Now let’s add the ‘right’ Shared Parameter using Shared Parameters dialog box. Uh oh! Revit still remembers the OLD Parameter Name. Not good. This issue was well described by Jay Merlan over here. From his post:

“If you want to test this limitation, try deleting a Shared Parameter from a Revit model and loading a parameter with the same GUID but a different name. It will always assume the original parameter name that was defined in the project or family.“

Ok, now what? We had already acquired all the data into Deep Space, so we could open up the Data App. From here, we can search for either the Shared Parameter GUID or the ‘wrong’ parameter name from the latest data capture.

Now for the cool part – the ParameterId that Deep Space has captured is actually a Revit Element ID. We can copy the value from Deep Space, use Select by Id in Revit, then delete the Parameter PROPERLY. This is the way to truly get rid of a Shared Parameter from your model. We aren’t really worried about losing data, because all historical parameter data is captured into Deep Space anyway!

These are the key points:

  • Removing a Shared Parameter from Revit interface doesn’t really delete it
  • Deep Space ParameterId for that shared parameter is ACTUALLY an Element ID
  • We can use that to select the Parameter “Element” in Revit and delete it properly! (use Delete key or the little red X on ribbon)

Select the Parameter by ID then Delete It

The total workflow we used on this particular project was:

  1. Setup Deep Space
  2. Sync Data from Revit
  3. Configure and use LOI Report app in Deep Space – this tells us which Shared Parameters have incorrect GUIDs
  4. Now use Data app in Deep Space to query and search for Parameter info. Use this to fix the model Shared Parameters
  5. Use Deep Space Write Back functionality to write data captured in a Deep Space web input portal straight back into the model
  6. Configure some IFC Export settings (category mapping and attribute settings) then export the ultimate IFC deliverable for the client.

LOI Report app in Deep Space

The Next Generation – VentureOn Partners Invest in Deep Space

Luke Johnson

Around 9 months ago I decided to step back from the majority of my consulting work and focus on Deep Space, a digital construction project intelligence platform built by myself and Michael Clothier. After a lot of learning, pitching, refining, and due diligence, we were extremely pleased to reach a milestone last week. We were able to finally share with the world that Deep Space has been officially funded by VentureOn Partners, a forward-thinking ConTech + PropTech SaaS investment company in Australia!

Here is part of the press release:

VentureOn Partners Pty Ltd (VentureOn), a leading venture capital firm headquartered in Brisbane, Australia, is thrilled to announce a significant investment in Deep Space, an innovative construction technology (contech) company. This strategic investment marks a pivotal moment in the contech journey.

Luke Johnson, Co-Founder and CEO of Deep Space, expressed his enthusiasm about the partnership: “We are delighted to welcome VentureOn as a strategic investor,” said Johnson. “Their commitment and operational collaboration will undoubtedly propel Deep Space to new heights in the construction technology landscape.”

“VentureOn’s investment is a testament to the value our solutions bring to major construction projects globally,” said Michael Clothier, Co-Founder and COO of Deep Space. “This partnership aligns perfectly with our vision of expanding our reach and impact.”

Today, Deep Space is trusted by industry professionals globally and has proven instrumental in enhancing the efficiency of major construction projects. Deep Space’s unique solutions have already demonstrated their value in high-profile projects such as the Hong Kong Airport and Cross River Rail, significantly improving their efficiency and data handling capabilities. Their suite of services, including data acquisition add-ins, secure cloud storage, and pioneering Core Thread Technology, truly sets them apart in the market.

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Deep Space and VentureOn Partners

VentureOn’s investment comes with a clear vision of working closely with Deep Space to expand its operations both domestically and scale internationally. This partnership is set to drive growth and development, with a focus on scaling the company and achieving a Series A investment for continued global expansion.

“This investment reaffirms VentureOn’s vision of nurturing and scaling local SaaS companies to achieve international success,” said Sean Diljore, Co-Founder and General Partner at VentureOn. “Our hands-on approach to growth and strategy makes us a valuable partner for companies like Deep Space.”

VentureOn’s commitment to the construction tech and property tech domains is evident through this strategic investment, which comes shortly after the acquisition of Story Bridge Ventures and PropTech BNE earlier in October. The company believes in the transformative potential of these domains and aims to support innovations that enhance the construction and property industry.

This new operational collaboration forms a vital foundation for the partnership with Deep Space.

“We are enthusiastic about the vast potential of Deep Space,” said Ricky Sevta, Co-Founder and General Partner at VentureOn. “Through VentureOn’s investment and operational support, our goal is to expedite Deep Space’s growth and broaden its global presence, delivering innovative solutions to the construction domain.”

Read the rest of the press release here.

Follow Deep Space here.

Follow VentureOn Partners here.

AI in 2023 and the Emergence of Embodied Intelligence

Luke Johnson

Yes, I’m going to do this. I’m going to write another post about a widely used term and try to untangle reality from the fiction. Let’s talk about the term “AI”… Mr Gates wrote a compelling article recently about AI Agents specifically, and even Mr Clippy got a slightly dishonourable mention. But hold on to your chatbots hats, because we are going to go right back to basics…

First, let’s define some terms related to AI.

Intelligence
The faculty of understanding; intellect.

Artificial
made or constructed by human skill, especially in imitation of, or as a substitute for, something which is made or occurs naturally;

Now, we might assume that Artificial Intelligence means something man-made that has the faculty of understanding, right? Right?

As a verb, to understand means to know or realise the meaning of words, a language, what somebody says, etc.

Now, let’s compare this with a common definition of artificial intelligence…
the study and development of computer systems that can copy intelligent human behaviour.

Or, on Wikipedia:
Artificial intelligence (AI) is the intelligence of machines or software, as opposed to the intelligence of humans or animals. 

And finally, AGI:
An artificial general intelligence (AGI) is a hypothetical type of intelligent agent. If realised, an AGI could learn to accomplish any intellectual task that human beings or animals can perform.

Now, you may ask, “what’s with all the definitions?”  My personal feeling is that the perception of commonly available AI tech progress is largely overestimated and misunderstood, and that the ultimate aspirations of AGI are some distance away. So what’s with all the AI hype?

A few things definitely changed in the past couple of years. Tools claiming to be AI became widespread, and the technology started to be viewed as useful and cool. Let’s start with OpenAI and ChatGPT. It took the world by storm! It has a massive budget and huge backing. But what is it really?

ChatGPT, PaLM / Bard, and LLaMa are all Large Learning Models. They consume massive amounts of data, build a kind of neural network, and then you can converse with them. But guess what? They don’t have the human faculty of understanding. They are effectively guessing what the next word should be based on context and a massive set of data and processing power. Almost all Copilot-like technology works on this basis, except you can introduce your own contextual data into the model. LLMs must be trained on data that was ultimately produced by humans when in its “most raw form.”

Is it cool? Yes. Is it useful? Sure. Can it save you time? Yep. Is it anywhere near human intelligence? Of course not. You can’t measure a faculty of true understanding based on outputs and interactions. Understanding happens on the inside.  I don’t believe I’m saying anything too controversial, but I do believe we should occasionally ask the question “what level of AI tech do we really have right now?”

What about image generation, specifically text-to-image models like DALL-E 3, Imagen, and Midjourney? These actually use some variation of an LLM – the input text is converted and fed to a generative image model. That model has been trained on massive amounts of text and image data scraped from all over the place. It seems creative but isn’t it really a tool that adapts and morphs known images into some new variation? Again, they must be trained on data that was ultimately produced by humans when in its “most raw form.”

Perhaps I’m oversimplifying, but does the current global state of AI tech approach anywhere near the creativity and original ingenuity of a human? Not even close. They are powerful tools that are transformative and disruptive. But they are really Super Guess Makers. They produce contextual linear things that ultimately are a version of “the system knows billions of types of representational data, and it can try to build you something like what it already knows.”

I want to introduce you to a new term. At Deep Space, we have a proprietary data framework that we call Core Thread Technology. Part of that technology framework is Embodied Intelligence. Let’s define it..

Embodied Intelligence is found when a computerised system has inbuilt comprehension of data classification, relationships, workflows, and qualitative measures. This inbuilt comprehension is encoded into the system by humans based on a depth of real world experiences, probably over decades.

Does Deep Space have AGI right now? No.
But Deep Space does have Embodied Intelligence.

We have already established that the majority of cool and powerful AI tech currently available has been trained on raw data originally and usually attributed to human agents. I believe the AI term itself is really too generous for the majority of the currently available tech. But Embodied Intelligence is a practical term that embraces the fact that there are experienced industry leaders who can legitimately train a system in specific ways to maximise productivity.

That is what we are doing for Digital Design and Construction at Deep Space right now.