I've been working on an AI-assisted subcontractor management system. It starts with the signed subcontract and agreed scope, budget and programme. Basically after procurement is done and you have locked in the sub-contractor. From there, we have each step in the process and some small, discrete Claude skills that you run to support each process. We also have a library of business templates and project information that sits behind them. Setup and mobilisation: summarise obligations, build a checklist for documents and site readiness, and agree how progress will be reported. Delivery: check performance against the plan, review payment claims against verified progress, assess variations and draft notices. For variations, check entitlement first, then price and time. This Close-out: check the final account and handover requirements, then record lessons learned and subcontractor performance for future projects. The system combines organised project records, shared business information and reusable AI workflows that you customise to your processes. Check out the walk-through: https://youtu.be/04Vw2WqI2dE

How to Use AI in Construction Estimating Without Losing Control of the Bid A construction estimate is a commitment: we can build this scope for this price, in this time, from documents we’ve often only had for a couple of weeks. That’s why handing the whole bid to AI and hoping for the best is a terrible idea. I think there are three sensible levels: - Start with risk reduction. Use AI to check your estimate for missed requirements, gaps, double-counting and formula errors. - Use it to structure information. Build requirements and clarifications registers, then review them before they feed into the next step. - Once your data is organised, use it for more of the heavy lifting like assemblies, line-item pricing, subcontractor quote comparisons and submission documents. The important part is keeping human review between each workflow so errors don’t compound. Where are you currently using AI in your estimating process?

Something I’ve noticed after working with business owners across different industries is that the ones who eventually build something sustainable usually have one thing in common: They genuinely care about what they’re building. They care about their customers. They care about their reputation. They care about their team. And they care about getting the business right. But caring about the business doesn’t mean you should be the person handling every follow-up, admin task, customer message, or operational detail. That’s where a lot of good businesses get stuck. The owner becomes the person everyone depends on, even when systems and automation are already in place. I’ve always believed the right support isn’t about finding someone to simply “do tasks.” It’s about finding someone who can take ownership of the work and treat the business with the same level of care. Whether you’re building an eCom brand, growing a service business, or using AI to scale your operations, that human execution layer still matters. Systems create leverage. The right people make that leverage actually work. 💯

I hear a lot of confusion about the term “AI agent” in construction. To me, an agent pulls together a few different concepts: - Workflows that explain how to complete repeatable tasks - Context from your project documents, registers and correspondence - Memory about the project, your business and how you prefer to work - Tools and permissions that control what it can access and what actions it can take We then package this into an interface that we or our team can call when we need work done. The main difference between a workflow and an agent is responsibility. A workflow completes a defined task. An agent owns a narrow area of responsibility, chooses which workflows to run, checks the result and keeps a record of what it has done. Would I let an AI agent autonomously build a programme or send contractual notices? No. But I would let it monitor correspondence, identify a potential variation, update the register and draft a notice for review. That is where agents are useful today: bounded responsibilities, clear permissions and human approval. I explain the full model here: https://youtu.be/hnGixjVMD2g

Registers are often the first thing to slip when things get busy. That was my experience as a PM, and an out of date register is essentially useless. Scheduled tasks are great for making sure they're kept current. I don't schedule a prompt, I schedule a skill. The instruction in the task is one line, run the document controller, and the skill carries all the detail. Three things to work out before you build one: - Where the information comes from. Project inbox, registers, daily site reports, meeting minutes. - Where it ends up, and whether you review it first or it writes straight to the register. - How often it runs, because when you open the register you need to know what window it covers. Then run it manually for a few days. Once you stop tweaking it, that is when it goes on a schedule. You still want to check in on the outputs though. I went into more detail in this video.