Increasingly, there is a disconnect between established operational/corporate systems and the new AI-enhanced powers of individual workers.
The over-production of documents is just one symptom. It's clear that organizations are struggling to successfully evolve in the era of worker 'superpowers'. Probably because change is hard!
Perhaps this is indicative of a failure of imagination as much as anything? The AI era is not living up to its potential if workers are given superpowers, but they are not empowered to use them effectively.
Empowered teams and individuals have more accountability and ownership of business outcomes - this points to a need for flatter hierarchies and enlightened governance, supported by appropriate models of collaboration and reporting (AI helps here too!).
In the OP article the writer IMHO reached the wrong conclusion about their colleague who built a system that didn't work - this sounds like the sort of initiative that should be encouraged, and perhaps the failure here points to a lack of technical support and oversight of the colleague's project.
Now more than ever organizations need enlightened leadership who have flexible mindsets and who are capable to envisioning and executing radicle organizational strategies.
You can get a new panoramic film camera for $69 - the Sprocket Rocket [1]. It makes images with grungy lomography charm - edges are soft but center is surprisingly sharp for a plastic lens. I really like the look of the images it produces. It has a hot shoe and a bulb setting.
While cool, there is quite a bit of difference between this and what the widelux is. The widelux rotates the lens as the front cover moves, which creates a drastically different look.
I asked an LLM to create a plan for a 'digital rebirth' in order to minimize privacy harms. It's a lot of work, but increasingly: a worthwhile endeavor.
I assume that a significant proportion of writers have worked this out via trial and error: AI can be highly useful, but you still have to work very hard on the text, maybe even harder.
Thanks! This took a while (approximately 30 days) to get to this point.
The market basically relies on two main alternative approaches right now, both of which have their merits:
1. File-based Memory (Markdown/Artifacts):
Instead of just relying on the context window, you prompt the agent to maintain its state in local files (e.g., a PLANNING.md or a TASKS.md artifact). It’s a step up, but text files lack relational integrity. You are still trusting the LLM to format the file correctly and not arbitrarily overwrite critical constraints.
2. The Orchestrator Agent (Dynamic Routing):
Using a frontier model as a master router. It holds a list of sub-agents (routes) and is trusted to dynamically evaluate the context, route to the correct agent, and govern their behavior on the fly. The merit here is massive flexibility and emergent problem-solving.
I went in the opposite direction.
The trade-off with Castra is that it trades all that dynamic flexibility for a deterministic SQLite state machine. The demerit (though I consider it a feature) is that it is incredibly rigid and, honestly, boring. There is no 'on-the-fly' routing. It’s an unyielding assembly line. But for enterprise SDLC, I don't want emergent behavior; I want predictability.
The alternatives optimize for agent autonomy. Castra optimizes for agent constraint.
To counter the unnatural look of noise reduction I often add a film grain effect.
reply