Replay: Tech Stack Audit With a Little Help From Ai 3.23.26
Stop Collecting Tools. Start Building Systems.
In this session, Rebecca Green debuted the new Technology Audit course — and the core message was simple: most agents don't have a tool problem. They have a systems problem. More apps won't fix it. A clean, honest audit will.
The CEO Shift: A Different Question
There's a pattern Rebecca sees constantly in one-on-one sessions with agents: too many tools, too little structure. The instinct is always to add something new. A better CRM. A slicker email platform. Whatever just got recommended in a Facebook group.
The shift that actually changes things isn't finding the right tool — it's asking a different question. Instead of "What should I try next?" ask "What system do I need to build, and what tool supports that?"
That reframe — from tool collector to CEO — is what the entire tech audit is built around.
And the filter for every tool you evaluate is the same three questions: Does it save me time? Does it make me money? Does it improve the client experience? If the answer is no to all three, the tool isn't neutral. It's actively costing you.
The 3-Step AI-Assisted Audit
The tech audit Rebecca walked through is a three-phase process, and AI does the heavy lifting at every stage.
Step 1: Inventory Everything
Start by listing every single tool, app, and subscription you're currently paying for or actively using. Don't filter — just list. Then drop that list into ChatGPT, Claude, or Gemini with a prompt asking it to identify overcomplication and categorize each tool as:
Essential — core to how your business runs
Underutilized — you're paying for it but not using it well
Unnecessary — redundant with something else you have, or just not doing a job
Unsure — needs more context
This step alone surfaces gaps and redundancies most agents have never noticed. Multiple tools doing the same job. Subscriptions that have been quietly charging for months with nothing to show for it.
Step 2: Evaluate for Profitability
The second phase zooms in on your core infrastructure — starting with your CRM — and asks harder questions:
Is your CRM actually tracking ROI, or are you just storing names?
Are you using at least 80% of the features you're paying for?
Is it actively supporting lead generation and follow-up?
The same lens applies to your operations stack (transaction management, document storage, task management) and your marketing systems (email platform, lead magnets, nurture sequences, open and click rates).
Rebecca is also building a dedicated Tech Stack Audit Bot — a custom GPT that walks agents through these questions systematically, so nothing gets glossed over.
Step 3: Run the Final Prompt
Once you've worked through the profitability and operations questions, feed all of it back into the AI and ask it to identify:
Your biggest deficiencies
Where you're wasting money
What to eliminate immediately
What to optimize
What's genuinely missing
Rebecca noted that after running this process, every single agent has found dead weight to cut. Check your phone apps and your subscription billing — unused services have a way of becoming a quiet accounting nightmare.
The conclusion is almost always the same: you need better systems with the tools you already have.
Automate the Boring Stuff — Or You Become the System
One of the most important outcomes of the audit is identifying manual, repetitive work that should be automated. Lead follow-up. Email sequences. Scheduling. If you're doing these by hand every time, you're not building a business — you're just doing a job.
AI is an output system, meaning you still need to put the right inputs in. But once you do, it can run standard processes for you: lead intake, buyer nurture sequences, follow-up cadences. Rebecca demonstrated how the audit bot can tailor automation recommendations based on your specific tech stack — if it sees you're using Flodesk, it generates Flodesk-specific drip sequences rather than generic advice.
On integrations: Zapier (or built-in app integrations) is the bridge that eliminates manual data entry between systems. If you're copying contacts from one place into another by hand, that's a workflow waiting to be automated. A quick workaround Rebecca shared for systems that don't pass tags during automation: let them drop into a generic bucket, then spend five minutes each week manually sorting. It's not perfect, but it's far better than the alternative.
The Simplicity Principle (and the 24-Hour Rule)
The principle that anchors the whole audit: simplicity scales, complexity stalls.
This applies whether you're a solo agent or running a team. Every tool you add is something to manage, update, learn, and pay for. The more complex your stack, the harder it is to train someone on it, hand off work, or actually use it consistently.
Rebecca's personal rule before adopting anything new: wait 24 hours. Then ask the AI: "Do I actually need this, or am I avoiding using what I already have?" And check whether a tool already in your stack can do the job.
A Few Specific Tool Notes
A handful of concrete recommendations and cautions came out of the discussion:
Google Workspace is Rebecca's recommendation for core infrastructure, specifically because of its integration capabilities across other tools.
Dropbox over Drive for centralized document storage. Drive lacks the sharing and saving flexibility needed for client documents, and storing files in your CRM creates a serious problem if you ever need to switch platforms — you can lose everything. Dropbox keeps your documents portable and independent.
Flodesk caution: It's user-friendly, but it doesn't accept HTML, which limits what you can do with AI-generated content. If content flexibility matters to you, that's worth knowing before you commit.
The long game on email marketing: Rebecca shared a personal example of a Meta ad lead that converted — four years later — through a consistent nurture sequence. That's the compounding value of building the automation once and letting it run.
