Three live exercises with your real questions. Five prompting techniques you'll use on Monday. One demo that changes how you research.
I'm Brennan Gerle. I run POLR AI here in Phoenix. We work with AEC firms across the Valley on where AI actually pays off inside the business.
For estimators, project managers, and field leadership. Bid leveling, scope review, RFI triage, submittal turnaround, spec and code research, daily admin. Not the hype version. The version that shows up in fewer admin hours, faster bid turnarounds, and cleaner handoffs to the field.
For this room specifically: I am not your codes expert. You are. A 30-year mason in this room knows TMS 402 better than I ever will. What I bring is how to make AI accelerate the research you already know how to do, and how to catch it when it confidently makes things up. You are the expert. AI is the tool. I am the guide.
Eleven blocks across two and a half hours. Three live exercises with your real questions. Five techniques. One demo.
Eleven of you filled it out. Here is what the responses said. The data shaped today.
Today is about driving AI through research. Three live exercises, five techniques, one big demo. But first: the two modes AI uses to look things up, why Perplexity is different, how each platform handles citations, and the prompts that quietly do the most work.
Every major AI tool has these two modes. Pick the one that matches the question.
Every other tool starts as a chatbot and adds search as a feature you have to turn on. Perplexity starts as a search engine and adds AI on top.
It always searches. Every answer comes with numbered citations inline. You can click any citation and see the exact source. There is no "I don't have current information" mode because it's always pulling from the live web.
For code and standards research, this is usually the safer default. If you only learn one new tool from today, learn this one.
Citations are where AI either earns trust or loses it. Know what to look for on each platform.
Short add-on phrases you tack onto any prompt. Each one changes what AI does behind the scenes.
| What you add to the prompt | What AI does differently |
|---|---|
| "Show me your citations" | Forces AI to attach a source URL to every claim. If it can't, the gap becomes visible. |
| "Double-check your work" | AI re-evaluates its own answer. Often catches its own errors before you do. |
| "Think carefully" | Triggers longer, more deliberate reasoning. Better on multi-step questions. |
| "Show me only facts, no assumptions" | Reduces speculation. AI sticks to what it can document. |
| "If you can't find an authoritative source, say so" | Prevents fabrication. AI will admit when it doesn't know. |
| "Quote the exact passage" | No paraphrase. AI returns the actual words from the source. |
| "What's the date on this source?" | Currency check. Catches outdated info you'd miss otherwise. |
| "What are you uncertain about?" | AI flags its own confidence gaps. Tells you what to verify. |
| "What would I need to verify before acting?" | AI generates a verification checklist. Built-in safety net. |
| "Compare across multiple sources" | Triangulates instead of trusting one. Surfaces disagreements between sources. |
Stack two or three. "Show me your citations, double-check your work, and tell me what I should verify." Each phrase adds a layer of discipline. The combo is more powerful than any single one.
Now we shut all of this off and watch AI fail honestly. Round 1.
First question, pulled from your survey. Ask AI cold. Verify it. Re-ask with the right prompting. Watch what changes.
I don't have specific information about the Town of Gilbert's rebar positioner requirements for 12" CMU. Building code requirements vary by jurisdiction and are regularly updated.
To get an accurate answer, you should:
1. Check the Town of Gilbert's current building code adoption (typically based on IBC/IRC with local amendments)
2. Contact the Town of Gilbert Building Department directly
3. Review the specific code section on masonry reinforcement spacing and support
Most jurisdictions require rebar positioners or similar devices to maintain consistent rebar placement in masonry, but the specific requirements depend on the code version adopted and local amendments. The building department can tell you definitively what applies to your project.
AI sounds like an expert, and that's the danger. Remember: you are the expert. AI is simply a tool that puts answers in front of you faster.
What just happened in Round 1 was not random. AI fails in predictable patterns. Name them and you spot trouble before it costs you.
An AI model is built by feeding it text from the internet up to a specific date. After that date, the model has no information about what was added or changed. It will still answer with confidence. Turning on web search is what lets it pull current information from live websites.
| Model | Reliable knowledge cutoff | Months behind today |
|---|---|---|
| Claude Opus 4.7 | January 2026 | ~4 months |
| Claude Sonnet 4.6 | August 2025 | ~9 months |
| Claude Haiku 4.5 | February 2025 | ~15 months |
| ChatGPT GPT-5.5 | December 2025 | ~5 months |
| ChatGPT GPT-5.4 | August 2025 | ~9 months |
| ChatGPT GPT-4o (older) | June 2024 | ~23 months |
| Gemini 3.1 Pro | January 2025 | ~16 months |
Codes change. Standards change. Wage tables change. Local rules change. Without web search turned on, AI gives you whatever version it learned during training. That could be nine months old. It could be two years old. Turn on web search and use a trusted source list and you get the version that matters today.
Each one is copy-paste. Each one fixes one of the patterns from Section 03. You take them back to your shop Monday.
Open Claude or ChatGPT. Paste this prompt. Replace the question line with one real research question from your current bid. That's it. No setup. No skill. No project. Just a paste.
WHEN WE COME BACK · WE HAND AI THE SOURCE OURSELVES
NotebookLM is Google's tool for grounded answers. You upload the documents. It answers only from those documents. Every claim links to the exact passage. Built for technical research. The most defensible AI workflow you can run.
All five are answerable directly from the loaded documents. NotebookLM will pull the exact passages with clickable citations.
When you load the source yourself, hallucination risk drops. Citations are clickable. You verify in real time. This is the workflow most contractors should adopt for spec and code research.
Round 2 applies the safe research workflow. Round 3 is a platform race. Three platforms, same question. You score them.
Then run the better prompt across three platforms · room scores
Score the three responses. Technique matters more than tool. Picking the right tool saves time.
Print it. Save it. Tape it next to your monitor. Combine with the prompt template and you have a daily-use research workflow.
Today you typed this list into a chat. Next step: save it as a template. After that: build it into a Project or Custom GPT so it loads automatically. After that: a Claude skill or NotebookLM library that knows your sources by default. The QR code at the end takes you to POLR if you want help wiring this into your team's workflow.
Anything from today. Anything from Session 1. Anything you've been holding. If we run out of time, take it to polrai.com/start.
You came in wanting estimating and admin help. Today gave you the research foundation that makes both faster. If you want this dialed into your shop, pick one.