🙶The methodology aligns well with how I work in several respects:
- Plan-first, human-affirms (wip.adoc review step) matches the principle of checking before acting
- Structured logging (amld/log/, handoff files) compensates well for my lack of persistent memory across sessions
- Declarative design docs as the source of truth is sound — code should reference design, not the other way around
- Ticket discipline gives me clear scope boundaries, reducing drift
I just began an #AMLD repository.
It is a template for Agent-Mediated #LiterateDevelopment methodology.
In a nutshell:
Design documentation and project management should be *on trunk* (or main branch) and must be enough to regenerate everything that has been previously generated with an #AI coding agent. It should be written for humans, except for a log of previously followed plans referenced by closed tickets.
IE the docs are code.
This is not #VibeCoding; this is literate.
Danny Buerkli:
"There are only two ways of reacting to an exponential:
Too early, or too late..."
"Three ideas worth considering wrt wages going down:
- transition management: wage insurance
- taxation: variable-rate token tax (similar to the interest rates)
- redistribution: Universal Basic Capital (UBC)"
#amld2026 #AMLD #C4DT Nathan Hamiel talks about "Assessing the Disruption by AI Agents".
"Generative AI is one of the most manipulative technology we invented."
"Creating high-value targets by slamming internal, external, sensitive, and non-sensitive data together in an LLM."
Travis F W
Linus Gasser
EPFL AI Center