After 27+ Years in Tech, This Morning Changed How I Think About Work
I have been in technology long enough to see several “this changes everything” moments.
Client-server. Virtualization. Cloud. Mobility. Security consolidation. Managed services.
Most waves changed infrastructure first and workflow second. You had to redesign systems, retrain teams, rewrite process, then maybe see the benefits six to eighteen months later.
This morning felt different.
On Friday, March 6, 2026, between 6:37 AM and 9:00 AM, I sat in a restaurant with a pot of tea, sent instructions from my phone, and watched a full block of real business work get completed through my AI assistant running on OpenClaw in a Linux VM at my house.
Not theory. Not a keynote concept. Not a proof-of-concept deck.
Work.
What happened in 143 minutes
Between 6:37 and 9:00 AM, this is what got done:
- Researched and benchmarked GPT-5.4, released the previous day
- Sent a networking email related to AI consulting
- Rewrote consulting Facebook bio with specialties and credentials
- Audited Google Search Console across three websites
- Fixed a favicon rendering issue in Google search results
- Built and deployed five SEO-focused pages for chuckpoole.com
- Added IAMCP Carolinas speaking engagement information to calendar and websites
- Diagnosed and repaired a silent OneDrive backup failure
- Synced all website changes back to cloud storage
- Updated White Rabbit Advisory Group site with a Speaking section
- Fixed a calendar display bug
- Drafted a post on managing AI costs
- Shifted workload between AI models to optimize operating cost
If you had shown me that list a few years ago and asked how it gets done, I would have described role coordination: developer, SEO specialist, admin support, maybe a systems person.
Today, the pattern is different.
The shift from doing to directing
For most of my career, value came from direct execution. You solved the ticket, wrote the config, fixed the workflow, installed the system, cleaned up the mess.
Those skills still matter. In fact, they matter more now because good direction depends on real technical judgment.
But the center of gravity is moving.
The high-leverage role is increasingly this: define objectives clearly, sequence work intelligently, validate outcomes quickly.
In other words, less manual clicking, more operational direction.
That is not “doing less.” It is doing a different category of work.
Why experience matters more, not less
There is a common fear that AI flattens expertise.
I do not see that.
What I see is that AI amplifies the person who can:
- Frame the right objective
- Spot weak assumptions
- Catch subtle errors
- Decide what matters now versus later
Those are judgment skills built over years of messy real-world projects.
In my own path, running PalmTech Computer Solutions for over 20 years taught me that operations fail at the seams: handoffs, unclear ownership, missing verification. After selling that business and moving into AI consulting through White Rabbit Advisory Group, I have found the same truth still holds.
AI helps with execution speed. Experience determines whether that speed goes in the right direction.
Security and control still matter
I am CISSP certified, so my default posture has always been to ask, “Where is this running, who controls it, and what are the failure modes?”
That is one reason my assistant runs on a Linux VM at my house rather than being treated as a black-box SaaS dependency.
For me, that local control is not nostalgia. It is operational discipline.
If a workflow is core to business continuity, you should know how it is wired and where your data paths actually go.
Today’s OneDrive backup issue was a good reminder. Silent failures are dangerous because they feel like success. AI helped surface and fix it quickly, but the bigger lesson is governance: verify, do not assume.
This is different from previous waves
Cloud transformed infrastructure economics.
Mobile transformed user access.
AI, in this form, transforms managerial bandwidth.
That is the difference I felt this morning.
The limiting factor was no longer “Can I personally execute each task?”
The limiting factor became “Can I direct work clearly enough to keep throughput high and quality intact?”
That is a new operating model for knowledge work.
What this means for consultants and IT professionals
If you are in consulting, managed services, or technical leadership, the practical implication is straightforward:
Your edge will come from orchestration quality.
That includes:
- Task decomposition
- Prompt and instruction precision
- Verification discipline
- Cross-domain context management
- Cost-aware model selection
The consultant who can combine those skills will deliver better outcomes faster than teams still structured around serial handoffs.
This does not eliminate specialists. It changes when and how you need them.
A personal note on reinvention
Reinvention in tech is rarely comfortable. You carry habits from the last successful era, and many of those habits are still useful.
But every so often, you hit a morning that makes the direction undeniable.
Today was one of those mornings for me.
I was not trying to prove a point. I was trying to clear a workload before the day got noisy. By 9:00 AM, I realized I had moved through research, content, SEO, systems reliability, and planning from one seat at breakfast.
That does not happen by accident. It happens when experience and new tooling align.
Looking ahead
I will be sharing more of these practical operating patterns in upcoming talks, including the IAMCP Carolinas Chapter meeting on April 21, where I am speaking on generative AI and the future of the IT consultant.
Additional speaking updates are posted here: speaking.html
If this morning taught me anything, it is this: after 27+ years in tech, the most valuable skill now is not just solving the work yourself. It is building a system where the right work gets done quickly, correctly, and with intent.