Comprehension debt is real even as a solo founder.
I use AI heavily for implementation but the
architectural decisions still have to live in my
head. An AI agent can write the handler in minutes.
Understanding why the codec layout is structured
that way, why this fee constant exists, why this
capability gate was added takes much longer.
The pattern I found: if the decision is not
documented at the layer where it is enforced, it
gets lost. A later AI session will change it
because it only sees the local context, not the
reason behind the structure.
The fix that worked for me: every protocol decision
is recorded where it is enforced, not in a
separate doc. Golden-vector tests lock byte
layouts. Constants are named for their purpose.
Validation hooks carry comments about why they
reject, not just what they reject. The codebase
becomes its own knowledge base.
AI is the best tool I have ever used. But it is a
tool. The understanding still has to come from the
person building the system.
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Comprehension debt is real even as a solo founder.
I use AI heavily for implementation but the
architectural decisions still have to live in my
head. An AI agent can write the handler in minutes.
Understanding why the codec layout is structured
that way, why this fee constant exists, why this
capability gate was added takes much longer.
The pattern I found: if the decision is not
documented at the layer where it is enforced, it
gets lost. A later AI session will change it
because it only sees the local context, not the
reason behind the structure.
The fix that worked for me: every protocol decision
is recorded where it is enforced, not in a
separate doc. Golden-vector tests lock byte
layouts. Constants are named for their purpose.
Validation hooks carry comments about why they
reject, not just what they reject. The codebase
becomes its own knowledge base.
AI is the best tool I have ever used. But it is a
tool. The understanding still has to come from the
person building the system.