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What I’ve Learned About Trust from 30 Years of Consulting

In consulting, trust isn’t a buzzword—it’s the whole game.
You can have the best tech stack, the sharpest team, and the flashiest slide deck in the room… but if the client doesn’t trust you, none of it matters.

After over 30 years in the business, here’s what I’ve learned about how trust is built (and lost).

1. Trust is consistency over time
It’s not about one impressive meeting or a great kickoff call. It’s about showing up, following through, and doing what you said you’d do—over and over again.
Trust builds slowly and silently. Then, one broken promise can blow it up.

2. You earn it faster by telling the truth sooner
Bad news doesn’t get better with time. When something goes sideways—and it will—clients want honesty, not spin.
I’ve found that the faster we admit a misstep and share how we’re fixing it, the more credibility we build. It’s counterintuitive but true.

3. Being technically right isn’t always enough
You can win the argument and still lose the room.
Trust isn’t just intellectual—it’s emotional. Clients trust people who listen, who meet them where they are, and who understand their pressure (not just their project scope).

4. Trust is built between meetings, not just in them
It’s the quick update when nothing’s changed. The extra question that shows you’re thinking ahead. The quiet follow-up that signals, “We’ve got you.”
These moments don’t get logged in JIRA or tracked in a spreadsheet—but they’re noticed.

5. Trust is fragile—and portable
People remember how you made them feel. If you’ve built trust with a client, they’ll take you with them when they move companies. If you’ve burned it, same deal.
In this business, your reputation travels faster than you do.

The longer I’ve led teams and worked with clients, the more I’ve realized: we’re not just in the software business. We’re in the trust business.

And like anything worth building, it takes time, intention, and care.

If AI Is So Smart, Why Can’t It Run a Project?

AI can draft an email, summarize a meeting, write code, and even crank out a blog post like this one (with help). But there’s one thing it still can’t do:

Run a real project.

We’ve tried. We’ve experimented with AI for status reports, timelines, risk assessments, and backlog grooming. It’s impressive—fast, helpful, and often accurate. But project management? That’s still human territory.

Here’s why:

1. AI can’t read the room.
Deadlines shift. Priorities change. A stakeholder’s “no big deal” tone in an email actually means “I’m about to escalate this.”
AI doesn’t catch nuance. It doesn’t read body language, office politics, or tension over Teams calls. Project leaders do.

2. Projects don’t follow scripts.
Even the best Gantt chart goes sideways by week two. People get sick. Budgets get cut. A client pivots.
AI is great at pattern recognition—but projects are often the opposite: messy, emotional, and unpredictable. Leading through ambiguity takes real-time judgment, not pre-trained algorithms.

3. Relationships still matter. A lot.
When things go south (and they will), people want to talk to someone they trust—not a chatbot.
A seasoned project lead knows how to listen, adjust, empathize, and reset expectations without blowing up the timeline—or the relationship.

4. AI doesn’t know your business.
It knows businesses in general. It doesn’t know your unique challenges, team dynamics, or what happened last quarter that’s still lingering in the background.
Good project leadership isn’t just about tasks. It’s about context—and context still requires a human brain.

That said—AI is an amazing co-pilot.
It can flag risks faster. Draft communication. Generate insights from sprint notes.
But it’s not leading the call, navigating egos, or rescuing a deliverable gone off the rails. That’s you.

So no, AI can’t run a project.

But it can help you run one better.

Your Best Consultant Might Be the One Who’s Not Billing (Yet)

In consulting, there’s a saying:
“If they’re not billing, they’re costing.”

That’s technically true. But it misses something bigger.

At Intertech, we’ve come to realize that our most valuable consultants aren’t always the ones billing every hour. Sometimes, the people on the bench are driving the most important transformation in our business.

Right now, that transformation is AI.

Here’s how we’re using bench time strategically:

1. Training on AI tools and frameworks
Rather than rushing consultants into the next project, we give them structured time to learn tools like GitHub Copilot, ChatGPT, and AI-assisted test generation platforms. The result? They re-enter projects faster, more capable, and AI-enabled.

2. Standardizing AI in our dev process
We’re using bench cycles to build internal playbooks for applying AI—from proposal writing to automated documentation to code review. These aren’t “nice to haves.” They’re practical assets that increase velocity and quality across the board.

3. Prototyping with purpose
Benched consultants are experimenting with real-world use cases: generating scaffolding code, refactoring legacy modules, streamlining unit test creation, and integrating AI-driven analytics into apps. It’s hands-on R&D—without the overhead of a live project.

4. Supporting AI adoption across teams
Having AI-fluent consultants available helps us accelerate adoption across project teams. They’re building demos, advising PMs, and helping clients understand what’s possible. They’re our internal accelerators.

5. Staying ahead of client expectations
Clients are asking: “What’s your AI strategy?”
Our bench consultants are a big part of the answer. They’re not just staying billable—they’re making sure we stay relevant.

Bottom line?
A smart bench strategy isn’t just about cost control. It’s about innovation.
Done right, your non-billing consultants might be your most valuable team members—because they’re building the future you’ll soon be charging for.

The 3 Kinds of Clients We Say No To—And Why

When you’re starting a business, you say yes to everything. Every prospect, every project, every “maybe” that could lead to a win. I’ve done it. Most founders have.

But after years of consulting work, here’s the truth:
Some clients just aren’t a good fit—and saying “yes” to the wrong ones costs more than you think.

Today, we’re more intentional. Not because we’re arrogant. Because we’re focused.
Here are three types of clients we politely decline—and why it’s better for everyone when we do.

1. The “We Just Need Bodies” Client
What they say: “We just need a few developers to crank out code.”
Why we say no: We’re not a temp agency. If a client only wants hands on a keyboard with no strategy, collaboration, or architecture involved, we’re not adding the value we’re built for. We help solve problems, not just fill seats.

2. The “Everything’s on Fire” Client
What they say: “Can you take over this broken project… yesterday?”
Why we say no: Sometimes urgency is real. But other times, it’s the result of poor planning, shifting priorities, or internal dysfunction. If we’re stepping into chaos without clear leadership or direction, success becomes a moving target—and both sides lose.

3. The “Budget Mystery” Client
What they say: “We don’t really have a set budget. Just give us a ballpark.”
Why we say no: No budget = no clarity. Good partnerships require transparency from both sides. If we’re forced to guess what they can spend, we’re already misaligned. We value trust and candor, and that starts on day one.

Here’s what we do look for:

Clients who want true collaboration
A clear business challenge with measurable impact
Openness to our process—not just our people

Saying no isn’t easy. But saying yes for the wrong reasons? That’s how you drain your team, dilute your value, and damage your reputation.

We’ve learned it’s better to walk away early than to regret staying too long.

Afraid of AI? Here’s What to Do Instead

Take a walk through any office, wait online for others to join a Teams or Zoom call, or bump into an old co-worker at Starbucks——you’ll hear the same concern:

“Is AI going to take my job?”

It’s a fair question. Unless you’re in a profession that involves fixing plumbing, laying concrete, or replacing brake pads, it’s hard not to feel like the digital tidal wave of AI might wash you out of relevance.

But here’s the thing: AI isn’t just a threat. It’s a tool. One that’s already helping most of us—whether we realize it or not.

Like right now. You’re reading something that was written by a human (me) and shaped by an AI assistant. I still had to think, edit, and guide it. But it helped me get here faster—and better. It’s not a replacement. It’s a force multiplier.

Fear is normal. Staying afraid is optional.
The worst thing to do with AI is nothing. To bury your head and hope this all blows over. Spoiler: it won’t.

The second worst thing? To become a doomsday narrator in your own story.

The better option is this: get curious. Learn how to use it. Let it help you. Because once you stop seeing AI as a rival and start using it like an ally, everything changes. Along with helping you, look how it can help those who work with or for you. At Intertech, everyone, including the admin is reading a book or attending a course on AI for their job.

Here’s how to stay relevant—and even thrive—with AI:

1. Become a “human-AI hybrid.”
The people who succeed in the next decade won’t be the ones who avoid AI. They’ll be the ones who use it daily—and pair it with judgment, emotional intelligence, and common sense. Think you + AI = amplified value. For my software application development firm, like mine, AI represents the challenge that AI will reduce our billable hours. This is the reality of the future. Either we embrace it, or others will surpass what we can deliver.

2. Use it to eliminate the junk work.
AI is great at first drafts, summaries, idea generation, and repetitive tasks. Let it take care of the shallow work so you can focus on the deep stuff—strategy, creativity, relationships, leadership.

3. Focus on what AI can’t do (yet).
Things like building trust, mentoring a junior colleague, closing a deal with nuance, or navigating politics inside a client’s organization. That’s still very much human territory. Strengthen your relationships with clients, employees, partners, or others.

4. Stop waiting for perfect. Start experimenting.
Use ChatGPT, CoPilot, or others. Not sure where to start? Tell AI about your job and ask for feedback. Try an AI meeting note taker. Let AI generate a first pass on a report. You don’t have to be an expert. You just have to start. Every new skill starts with awkwardness.

5. Ask AI to help you with AI.
Open up to AI and share what you’re about, what you do, your goals, and where you have questions and want answers. Have it be a dialogue not a one-and-done question. Guide the AI on the journey not vice versa. Expect to be surprised. The more you interact with your AI, the more it learns about you and will guess what you want next. And, finally, a good thing about AI is to think how often it calls in sick, gets tired of you asking it to answer the same question, or doubts what it’s saying… zero.

Bottom line? Yes, I will change work. It already is. But it’s not coming to replace the people who adapt—it’s coming to help them outperform everyone else.

So the question isn’t “Will AI take my job?”

It’s “Am I willing to evolve with it?”

And if you’re already using AI to draft blogs, answer emails, and prep for meetings… congratulations. You’re not behind. You’re ahead.