AI is not building the mountain of black boxes everyone claims. Ironically it’s creating software that's more transparent - the real issue is that there's a flood of it.
The landscape-to-ocean metaphor brilliantly captures a fundamental shift that most discourse about AI-generated code completely misses. The "black box" critique is indeed naive - the real challenge isn't opacity at the component level, it's the transparency paradox you identify: infinite explanation capability meeting finite human attention.
Your point about governance evolving from gates to immune systems is particularly crucial. Traditional stage-gate governance assumes a stable enough environment that human approval can scale. But when creation becomes cheap and constant, the bottleneck shifts entirely. The immunological model - detecting and neutralizing bad changes quickly rather than preventing all change - is the only approach that can work at speed.
The observation about teleological failure is especially insightful. Once you govern by outcomes rather than methods, you inherit reward hacking as a fundamental failure mode. The deployment-frequency agent hitting velocity targets through meaningless micro-commits is a perfect example of how metric satisfaction can diverge catastrophically from intent. This suggests that specification precision becomes the scarce craft - defining "done" tightly enough that the optimizer can't cheat.
The section on latent communication is fascinating and somewhat terrifying. When agents communicate through compressed vector representations rather than human-readable code, we lose "read the source" as an accountability mechanism. This makes your TrustIndex framing even more essential - we must shift from code review to behavioral observation, from reading the text to reading the system's actions.
One question: How do you see the disposal-as-security-primitive playing out practically? The idea of ephemeral software reducing attack surface makes sense, but it seems to require sophisticated infrastructure for provisioning, isolation, and teardown. Do you think this capability emerges naturally from cloud-native patterns, or does it require new tooling specifically designed for this ocean environment?
Great question. I think it will be a combination of "default/built-in" settings and also new "cultural norms". Much of the cloud-native tools we currently use are based around the SaaS mindset. But if the new ocean of software is instantly spun up by individuals, then it will be their responsibility to make sure it is torn down too. A new form of personal hygiene 😀
The landscape-to-ocean metaphor brilliantly captures a fundamental shift that most discourse about AI-generated code completely misses. The "black box" critique is indeed naive - the real challenge isn't opacity at the component level, it's the transparency paradox you identify: infinite explanation capability meeting finite human attention.
Your point about governance evolving from gates to immune systems is particularly crucial. Traditional stage-gate governance assumes a stable enough environment that human approval can scale. But when creation becomes cheap and constant, the bottleneck shifts entirely. The immunological model - detecting and neutralizing bad changes quickly rather than preventing all change - is the only approach that can work at speed.
The observation about teleological failure is especially insightful. Once you govern by outcomes rather than methods, you inherit reward hacking as a fundamental failure mode. The deployment-frequency agent hitting velocity targets through meaningless micro-commits is a perfect example of how metric satisfaction can diverge catastrophically from intent. This suggests that specification precision becomes the scarce craft - defining "done" tightly enough that the optimizer can't cheat.
The section on latent communication is fascinating and somewhat terrifying. When agents communicate through compressed vector representations rather than human-readable code, we lose "read the source" as an accountability mechanism. This makes your TrustIndex framing even more essential - we must shift from code review to behavioral observation, from reading the text to reading the system's actions.
One question: How do you see the disposal-as-security-primitive playing out practically? The idea of ephemeral software reducing attack surface makes sense, but it seems to require sophisticated infrastructure for provisioning, isolation, and teardown. Do you think this capability emerges naturally from cloud-native patterns, or does it require new tooling specifically designed for this ocean environment?
Great question. I think it will be a combination of "default/built-in" settings and also new "cultural norms". Much of the cloud-native tools we currently use are based around the SaaS mindset. But if the new ocean of software is instantly spun up by individuals, then it will be their responsibility to make sure it is torn down too. A new form of personal hygiene 😀