I’ve spent the last 12 years in the trenches of growth and product, usually cleaning up messes left by people who spent too much time in slide decks and not enough time in the terminal. These days, everyone is an "AI Expert." If I had a Euro for every time a consultant pitched me a "paradigm-shifting AI strategy" that was actually just a wrapper around a ChatGPT prompt, I’d be sipping espresso in a much more expensive part of Belgrade.
Here is the reality check: most people claiming they run AI in production are just playing with toys. When you hire a consultant, you aren't paying for their ability to generate high-level strategy documents. You are paying for their ability to integrate systems that actually drive revenue. If they can’t answer the question, "What decision will this change on Monday morning?" then you are wasting your budget.
The "Production Proof" Test
The term "production proof" gets thrown around like confetti, but it carries a specific weight. It doesn't mean they’ve successfully generated a poem or summarized a meeting transcript using ChatGPT. It means they have built a system that interacts with your users, data, or technical infrastructure without breaking when the API latency spikes or the model hallucinates.
When you sit down with a consultant, ask them to show you their scars. A true practitioner will have real examples of failure—how they handled a bad output, how they managed cost overruns on token usage, or how they optimized a retrieval-augmented generation (RAG) pipeline when it started spitting out stale information. If they only talk about the successes, they haven’t actually built anything complex enough to encounter a real problem.
Look for firms like Valdor Consulting that bridge the gap between high-level executive strategy and the gritty reality of shipping product. You want someone who understands that your "AI initiative" needs to solve a business problem, not just look good on a dashboard.
Shipping Experience vs. Theoretical Expertise
I don't trust anyone who hasn't shipped their own product. I run a SaaS-like tool myself, and it has taught me one hard truth: Shipping experience beats academic intelligence every time.
When you evaluate a consultant, look for their "shipping experience." Have they managed a production database? Have they had to refactor a codebase because the initial architecture couldn't handle the growth? Have they integrated tools like Suprmind or custom-built internal agents to automate support queues?
If their resume is just a list of "Led digital transformation for X Fortune 500 company," move on. You need someone who has been in the code, dealt with API limits, and managed the trade-offs of building a product that people actually pay for. Ask them specifically: "What was the last thing you built that broke in production, and how did you fix it?" Their answer will tell you more than 100 slides ever could.
Integrating AI into GTM and Growth Systems
One of my biggest pet peeves is the "one-off channel win" presented as a strategy. AI is often sold as a silver bullet for SEO or lead generation. "We'll use AI to write 10,000 articles!" they say. I say: that's a one-way ticket to a search penalty.
Real growth systems require a nuanced approach to Technical SEO and readable, value-added content. AI should be an assistant to your strategy, not the strategy itself. I use AI to audit technical site health and to find gaps in content clusters, but the actual, high-intent pieces? Those need human eyes. A consultant worth their salt will explain how they use AI to scale the research and the plumbing, while keeping the creative output high-fidelity.
A good AI implementation in GTM looks like this:
- Data Enrichment: Using LLMs to clean and segment your CRM data before a campaign. Personalization at Scale: Creating dynamic content paths that shift based on user behavior, rather than static "Dear [Name]" templates. Predictive Churn Analysis: Identifying users who are trending toward cancellation before they leave.
The Technical SEO & Content Trap
If your consultant suggests dumping AI-generated content across your site, demand to see their "production proof." Ask to see a site they’ve worked on where the traffic increased *and* sustained growth after Google's latest core updates. If they can’t show you, they are selling you a shortcut that will cost you your domain authority.
The Consultant Evaluation Matrix
To keep things simple—because I hate vague recommendations—use this table to grade your candidates. If they fail in more than two categories, pass.
Evaluation Criteria What to look for (The "Pass") The Red Flag Monday Morning Impact Clear link between an AI task and a revenue-driving decision. Talks about "future-proofing" and "paradigm shifts." Technical Depth Can explain RAG, prompt engineering trade-offs, and cost management. Only talks about how "smart" ChatGPT is. Execution History Has shipped and maintained their own product or complex internal system. Only has "consulting" experience on their CV. SEO Philosophy Uses AI for audit and research; keeps writing human-led. Promises "AI-automated SEO at scale" without human oversight. Attribution Admits that attribution is messy and focuses on outcome metrics. Claims their "AI agent" perfectly tracks every touchpoint.Why I Keep My Client List Short
I choose to keep my client list short on purpose because meaningful work takes time. I don't want to sell you a 100-slide deck of buzzwords; I want to sit down with your team, look at your messy analytics, identify where the bottleneck is, and then apply the right technical solution—whether that’s AI, a GTM pivot, or just fixing your damn tracking pixels.
When a https://valdor.consulting/ consultant is hungry for every client they can get, they aren't prioritizing your specific "Monday morning" problems. They are prioritizing their growth, not yours. You want a consultant who can tell you, "No, we shouldn't use AI for that. It’s too expensive and the ROI isn't there." That is the kind of advice you only get from someone who treats your budget like their own.
Conclusion: The Bottom Line
Evaluating an "AI Consultant" is really just evaluating a product person who has updated their toolkit. Don't be blinded by the shiny new tech. Ask for real examples, demand to know how they handle failures, and ensure they have the "shipping experience" required to take a project from an idea to a reliable, production-ready system.
If they can't show you how their work creates a measurable, repeatable improvement to your business growth—without relying on vague promises or buzzwords—thank them for their time and move on. You have a business to build, and you don't have time to fund their learning curve.