Luigi, Mike, and Andrew unpack Autodesk University — keynote demos, AI assistants as tool-pickers inside systems of record, token pricing, and whether agents-on-workflows beat agent-first products. They debate fee compression in PM software, the $1 vs $99 contractor spend split, and whether you’d buy Autodesk stock after AU (or just buy Google).

Hammad Chaudhry (Pomerleau) joins Luigi, Mike, and Andrew on running innovation and digital construction at a multi-billion-dollar GC — when to slow down before you speed up, security vs adoption, BIM/VDC as table stakes, and how to justify tech spend to the C-suite.

Francesco Iorio (Augmenta) joins Luigi, Mike, and Andrew on LLMs vs spatial AI, why building-scale design breaks token-context workflows, BIM metadata and prefabrication, and what it takes to automate the guts of buildings — not just the aesthetics.

Spencer Thompson of Cardinal Civil Contracting joins Luigi, Mike, and Andrew. They dig into what makes site-development precon different from vertical work — dirt as the windshield of a job, geotech unknowns, and pricing risk as levers for owners rather than a blanket premium. Spencer also talks takeoffs, true production vs dirt counting, and why Cardinal is cautious about unleashing AI company-wide until security guardrails are real.

What if completing a construction takeoff became as simple as uploading a drawing and asking for what you need?

In this episode, we speak with Elan, CEO and co-founder of Kamai, about using AI to make takeoffs faster and easier for contractors. Elon shares how his cybersecurity background in the Israeli military led him and his co-founder, Ben, into construction technology.

We discuss why construction software must be almost effortless to adopt, how Kamai turns drawings into precise measurements, and why customers care more about cost and results than whether the underlying AI models are open or closed.

Elan also explains Kamai’s approach to distribution, including bringing its takeoff capabilities into tools contractors already use, and why conversational interfaces could fundamentally change how people interact with construction drawings.

Kyle Bonde, Senior Estimator at Hensel Phelps, joins the Construction Technology Podcast to discuss what it takes for new technology to succeed inside a major general contractor.

Kyle explains why adoption beats automation, how Hensel Phelps evaluates and implements new tools, and why software must fit an estimator’s existing workflow before it can create value at scale. The conversation covers AI takeoffs, scope generation, conceptual estimating, Copilot, custom software built with tools like Lovable, and the growing tension between established platforms and fast-moving startups.

The group also explores where preconstruction technology is heading, including more specialized takeoff tools, AI-generated interfaces, automated scope analysis, better use of historical project data, and systems that help estimators find scope gaps before they become costly problems.

A practical look at how one of the industry’s most technology-focused estimators separates useful innovation from software that is not ready for the field.

What happens when AI stops assisting the estimator and starts doing the estimate?

In this episode, we speak with Dmitry from Handoff about H1, an AI system that autonomously turns construction drawings into complete estimates. Users upload their plans and receive takeoffs, markups, scope reports, pricing, assumptions, and potential conflicts.

Dmitry explains why Handoff is focused on smaller and growing contractors, how H1 connects estimates to supplier pricing, and what it takes to build enough trust for a contractor to bid from an AI-generated estimate.

We also discuss Handoff’s broader ambition: automating the back office of a construction company, from the first estimate through project management and invoicing.

Construction still runs on phone calls, jobsite conversations, and quick decisions that rarely make it into the official project record.

Karly Heffernan, co-founder of Hardline, joins Luigi La Corte, Mike Powers, and Andrew Zukoski to discuss how contractors can turn those conversations into structured project memory without changing how field teams work.

They explore why field software often fails, how phone-call data could automate RFIs and follow-ups, the “Big Brother” concern, legal discoverability, whether construction will remain human-first, and what happens to traditional software as AI agents become more capable.

Is the most valuable data in construction hiding in phone calls?

Can AI tools like Claude actually perform construction takeoffs?

In this episode, Luigi, Andrew, and Mike test Fable/Claude against real construction projects with known ground truth. The results are mixed: AI is getting very strong at scope identification, especially across drawings and specs, but quantity takeoff is still harder to trust.

The conversation gets into where AI is already useful, where it breaks down, and why auditability matters. Can a model count doors, fans, and equipment? Yes. Can it reliably calculate concrete, drywall, paint, or labor-driven quantities without a human checking the work? That is where the debate starts.

The group also talks about whether subcontractors should use Claude today, why estimators still need to verify the outputs, and what this means for takeoff software, preconstruction workflows, and the future of AI in construction.

In this episode, Luigi, Mike and Andrew are joined by Elliot Christensen, Senior Vice President of Operations at Cleveland Construction.

The conversation starts with Cleveland’s approach to technology adoption and why labor shortages are pushing contractors to think differently about efficiency, self-perform work, and repeatable scopes. Elliot shares how Cleveland is evaluating vertical integration, where CM fees are headed, and why design-build may create better alignment between owners, architects, engineers, and GCs.

The group then gets into Cleveland’s move from Procore to Autodesk. Elliot explains why the decision was driven less by product issues and more by cost, pricing structure, platform breadth, and Autodesk’s connection to the design ecosystem. The conversation also covers what Procore could do differently, why bundled platforms are attractive to contractors, and how Autodesk’s design-build-operate strategy may play out.

The second half focuses on Cleveland’s technology stack and startup adoption. Elliot explains why Cleveland is all in on Trunk Tools, where OpenSpace, Box AI, Breadcrumb, and Autodesk fit, and how AI agents could change the way project managers work. The episode closes with a rapid-fire round on overhyped categories, software buying advice, and why construction software fails when the field does not buy in.

Takeaways

• Cleveland moved from Procore to Autodesk primarily because of cost structure and platform economics
• Autodesk’s advantage is its connection to design, build, and operate workflows
• Contractors are under pressure to do more with lower CM fees
• Point solutions are harder to justify unless they solve several problems well
• Cleveland is betting heavily on Trunk Tools for drawings, RFIs, submittals, and construction-specific AI
• Box AI is useful for internal experimentation because the data is already there and the cost is capped
• AI agents may eventually shift project managers from managing paperwork to managing workflows and exceptions
• Field adoption is still the hardest part of construction software

Chapters

00:00 Introduction and Cleveland Construction’s approach to tech
01:17 Labor shortages and the need for efficiency
02:37 Self-perform work and repeatable scopes
04:41 Declining CM fees and vertical integration
05:08 Why design-build may win
08:10 Takeoffs, BIM, and risk transfer
15:38 Cleveland’s move from Procore to Autodesk
18:37 The cost savings behind the switch
19:11 Autodesk vs. Procore functionality
20:36 What keeps Cleveland on Autodesk long term
23:42 Autodesk’s design-build-operate advantage
27:57 What Procore should change
34:13 Why contractors cannot afford too many point solutions
36:51 Cleveland’s Trunk Tools bet
38:25 OpenSpace, Breadcrumb, Box AI, and Cleveland’s core stack
41:03 Token spend and capped AI costs
43:51 Why Trunk Tools is different from horizontal AI tools
47:53 Could Autodesk catch up on AI?
50:24 Project managers managing agents
52:33 Startup opportunities in quality control
55:22 Rapid fire: overhyped categories, pilots, and software buying advice