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Why we started in 2022
What we learned by beginning early and working through the limits.
The moment we saw it
AlphaGo made us curious about what AI could reveal. In 2022, public AI tools brought that curiosity into everyday work. The tools were uneven, but the possibilities were becoming easier to explore.
Why 2022 mattered
We watched models improve, make mistakes, and become useful in unexpected ways. Tools appeared and disappeared. Learning by doing helped us understand what each could contribute.
Snapshots show moments. A long memory shows movement.
The problem we set out to solve
Most organizations did not need more AI excitement. They needed help understanding which capabilities were real enough to matter, which were still premature, and how to prepare for what would become possible next.
Our first principles
Beginning early taught us how to experiment, notice limitations, and recognize useful progress. That experience still informs the questions we ask and the guidance we give.
What still holds
We still begin with the person and the work: what you want to accomplish, what is already in place, and what would make a meaningful difference. The right technology follows from that understanding.
Keep learning
Keep learning as the tools change.
Pattern first
Look for what works across different tools.
Context always
Understand the work before recommending a tool.
Judgment built in
Tools do not decide. People do.
Prepare for the upside.
It’s not too late to start. Begin with a prepared Signal Triage working session and practical next steps.