Sigil One is live now.
It helps crypto holders estimate likely tax exposure before selling, preserve cleaner records, and export handoff materials for CPA review.
Not tax filing software.
Not official tax advice.
Not a wallet connection.
Just clearer records before the next decision.
https://t.co/EUaLDlCfRp
This started as a small fundraiser for Clyde and somehow turned into a crash course in crypto promotion 😂
I’ve had 100+ promo accounts reach out in the last day, met some genuinely useful people, and learned a lot about how this ecosystem actually moves attention.
Still keeping this one about Clyde. ❤️
I’m coining a new term: full-circle absurdness.
When people, ideas, decisions, or random moments separated by years reconnect so precisely that the pattern starts to feel statistically disrespectful.
I’ve had way too much of that lately.
This got a lot more attention than I expected 😅
Clyde is still raising money for his first school trip to NYC. And yes, for everyone asking, there is actual chocolate too 😂
Pinned post has everything.
Started this as a simple experiment to help get Clyde to NYC.
A few hours later I’ve learned more about crypto promotion, distribution, community funnels, and internet behavior than I expected.
Still the same goal though: help my son get to his first school trip away from home.
$CLYDE
This is Clyde, my son. He has cerebral palsy and is raising money for his first school trip away from home to NYC.
He’s selling chocolate. I decided to try something a little different too.
I just launched $CLYDE on https://t.co/EqA5AMyuvN and I’m putting in the first $100 myself.
Any creator fees or proceeds from tokens I personally sell go toward Clyde’s benefit, starting with his trip.
No promises of profit. No price support. It can go to zero.
Just seeing what the internet can do to help get Clyde to New York.
Strong AI products need more than a good demo. They need evidence that the workflow still holds when requirements change, inputs conflict, or the system reaches the edge of what was tested.
This is exactly the kind of pre-launch pressure testing Sigil Systems is built to provide
Before you hand an AI workflow to a client, what have you tested beyond the demo?
What happens when a requirement changes halfway through the task? When two sources disagree? When the system says “complete,” but the evidence does not support that claim?
Those are the kinds of questions I examine through Sigil Systems.
My Pre-Launch AI Product Risk Review gives founders and AI teams an independent review of one defined product, workflow, claim set, or operating process before a launch or client handoff.
You receive a focused written readout of what the evidence supports, identified failure paths, what remains unresolved, and which tests should happen next.
After my completed review of Fork, Ryan Feller, Founder & Chief Architect at NGAST | Fork, wrote:
“I appreciated the rigor, care, and boundary discipline he brought to the review process.”
The aim is to give you something concrete to act on before a customer, partner, or client starts asking harder questions.
This is an independent review, not certification, legal advice, endorsement, or a full security audit.
Message me REVIEW with your product link and deadline. We’ll confirm fit and agree a fixed fee before work starts.
#AI #AIGovernance
2443 followers today!
I’ve been at this for 13 Months 3 days..
Learned a lot, really just appreciate the people curious enough to follow me & continue to follow the work. 😁
Completed Virginia Tech’s Activator: Technology Based Business Validation for Military-Connected Founders.
Building Sigil Systems means developing the business alongside the technology. This is another milestone in that work.
Thank you to Virginia Tech Continuing and Professional Education and the Boeing Center for Veteran Transition and Military Families for supporting military-connected founders.
#VeteranEntrepreneur #VirginiaTech #SigilSystems
Before you hand an AI workflow to a client, what have you tested beyond the demo?
What happens when a requirement changes halfway through the task? When two sources disagree? When the system says “complete,” but the evidence does not support that claim?
Those are the kinds of questions I examine through Sigil Systems.
My Pre-Launch AI Product Risk Review gives founders and AI teams an independent review of one defined product, workflow, claim set, or operating process before a launch or client handoff.
You receive a focused written readout of what the evidence supports, identified failure paths, what remains unresolved, and which tests should happen next.
After my completed review of Fork, Ryan Feller, Founder & Chief Architect at NGAST | Fork, wrote:
“I appreciated the rigor, care, and boundary discipline he brought to the review process.”
The aim is to give you something concrete to act on before a customer, partner, or client starts asking harder questions.
This is an independent review, not certification, legal advice, endorsement, or a full security audit.
Message me REVIEW with your product link and deadline. We’ll confirm fit and agree a fixed fee before work starts.
#AI #AIGovernance
Planning and rule-execution layers are critical to a successful build.
They remove pauses, ambiguity, false branches, and wasted tokens.
A narrow, specific plan executed directly beats:
idea → loose goal → build → wrong branch → debug → rebuild
Good planning can make the work feel backwards:
90% deciding exactly what should happen.
10% executing it.
Maybe the most useful AI skill isn’t prompting.
It’s knowing when to say:
Nope.
That interpretation is invalid.
Keep everything else.
Try again from there.
That single move has saved me more time than most prompt tricks.
AI drift probably wastes a stupid amount of compute.
One weird assumption gets in.
User fights it for an hour.
More prompts.
More context.
More retries.
Sometimes the right move is just:
“That branch is wrong. Here’s why. Start from there.
Right on cue 😂
Finished the Free Diagnostic result-hierarchy pass, pushed it live, verified the production states, cleaned the repo…
Claude session usage: 93%
There’s probably no better screenshot for what building with AI actually looks like right now.
The leverage is real.
So are the limits.
Ship before the meter hits 100%.
If I had to rebuild an audience from zero, I’d do the boring part first.
Spend 8 months posting consistently about:
who you are
what you’re building
what you’re learning
what you believe
No hard sell.
Just become familiar.
Then release something real.
Now the people who already recognize your name have something tangible to connect you to.
After that, if you actually have useful skills, start applying them to other people’s problems too.
That’s when the compounding starts:
identity → familiarity → product → proof → outside validation → opportunity
Most people try to start at the end.
Build recognition before you need attention.
Then give that attention somewhere useful to go.
This is what I mean by owning the Sandbox.
I don’t just mean servers or software.
I mean owning enough of the product, rules, data, tools, distribution, and economics around your work that someone else changing a policy can’t erase your ability to keep moving.
Not unlimited freedom.
Enough ownership that permission stops being the bottleneck.
Supabase paused Sigil One for inactivity.
Fair signal.
I’ve spent the last stretch building, testing, and tightening the product and the systems around it.
Now the phase changes.
Sigil One is coming back online, and the focus from here is simple:
users, feedback, revenue.
I’ve built enough to stop hiding behind the build.
Time to see what the market says.