Always Push Back. The Habit That Catches AI Before It Embarrasses You.
August 22, 2026 // Episode 157The Machine
This one will not take long, and it should not, because the fix is one sentence. Whenever you are using any artificial intelligence, Claude from Anthropic, Microsoft Copilot, Grok from xAI, Meta, whatever it happens to be, and you are about to publish anything it spit out, especially anything touching numbers, percentages, or a claim you would be embarrassed to have somebody catch as wrong, ask it to run it again. Ask it to double check what it turned out.
Because almost every single time I am running a project, and I mean almost every single time, that second pass catches something.
The Friday Routine, And Where This Actually Lives
Every Friday I go through the same process on a client's site. A crawl. A look at the AEO strategy, meaning how the site is showing up inside AI answer engines, not just search results. A check of what needs updating. A pull from the webmaster tools, figuring out exactly where placement sits, how many visits are landing, what the most popular pages are. And how all of it is interacting with the large language models themselves, and how frequently.
Sometimes that means Cloudflare data. Sometimes Netlify. Sometimes something else entirely, depending on where the site lives and what system is coordinating that traffic. All of it gets pulled together and run through AI to compile into something the client can actually use.
And before that report goes anywhere, I push back on it. At least once.
What Happened This Week
I was looking at exactly this kind of report, one of the Friday deliverables. I told it, essentially, look at this, double check it.
It came back and said there was a corrected version. Two claims fixed, after cross-checking against the reports from the previous few weeks running.
Then it said something worth sitting with. You were right to push. The cross-check found two things that would have failed her AI review.
That line is the whole reason this matters, and it is not the reason it mattered five years ago.
Your Client Is Going To Check Your Work With The Same Tool
Here is what I always come back to. This client, the one this report is headed to, is not just going to glance at it and trust the name at the bottom. She is going to take that report, drop it into her own AI, and ask it directly. Is this right. Is this accurate. Is it true.
That is the actual audit happening now, whether you planned for it or not. The client-facing verification pass used to be a courtesy. It is not a courtesy anymore. It is baked into how people receive anything from anybody claiming expertise. If your work has not survived its own internal cross-check before it leaves your hands, it is not ready to survive hers.
Your name is on it. Always push back, no matter what it takes, every single time you are using AI.
This Is Not Just A Marketing Problem
I see this constantly with real estate agents too. An agent asks AI to pull neighborhood data together for a seller, comps, market trends, whatever helps that seller make a real decision about listing their home. Or a buyer's agent runs a valuation question, trying to land on what a correct offer actually looks like.
Same rule, no exceptions. Push back at least once before that number reaches somebody making a six or seven figure decision partly because of it.
The pattern does not change across categories. Marketing data, real estate valuations, research summaries, whatever you are working in. The tool is exceptionally good at sounding certain. Certainty was never the thing you were actually supposed to be checking for.
Setting up your own AI verification habit starts before this one. If you have not created an AI account yet, start there: How To Set Up Claude AI Safely, Step By Step. Full business version of this episode, built around the actual Friday client-audit workflow: Why I Push Back On My Own AI Before A Client Ever Sees It.
Want help building this into your own process? Text AI to (661) 476-2217.
The Whole Discipline In One Move
You do not need a system for this. You need one sentence, deployed as a reflex, every time.
Ask it to run it again. Ask it to double check what it turned out. That is the entire mechanism. It costs a minute, maybe two, against a client relationship that costs a great deal more to rebuild than to protect on the front end.
Whatever system you are running this through, treat the first answer as a draft, not a delivery. The second pass is where the real work happens.
Common Questions
Why do I need to double check AI output if it already sounds right?
Because sounding right and being right are two different things, and a confident-sounding answer gives you zero signal about which one you got. A large language model predicts the next likely word from patterns, it does not consult a database of verified facts. The fix is not smarter prompting, it is a second pass: ask it to run the numbers again and cross-check them against the source data.
What does pushing back actually look like?
One sentence. Something like, double check that against the actual data, or run that again and show your work. Almost every single time, the tool comes back having caught something, a number that did not match the source, a claim that did not hold up under a second look.
Does this slow the workflow down a lot?
A minute, maybe two. Compare that to what it costs when a client runs your report through their own AI to check it and it comes back wrong. That is not a delay, that is insurance, and it is the cheapest insurance in the whole process.
Why does this matter more for client work than personal use?
Because your name is on it. A private question that comes back slightly off costs you nothing but your own time. A client deliverable with a wrong number in it costs you the relationship, and clients are increasingly running your work through their own AI to check it before they even read it themselves.
Which AI tools does this apply to?
All of them. Claude from Anthropic, Microsoft Copilot, Grok from xAI, Meta's AI, whichever one you are using. The underlying mechanism, predicting the next likely word from patterns, is shared across every general purpose model on the market. None of them are exempt from needing a second pass.
Can Connor with Honor help me build this into my process?
Yes. HonorElevate is the AI consulting practice for small business owners and operators who want working, trustworthy AI systems without figuring out the plumbing themselves. Visit HonorElevate.com or SantaClaritaArtificialIntelligence.com, or text AI to (661) 476-2217.