The semiotics of networked content
Explore how networked content transcends platforms, focusing on the significance of signs over replication in the evolving digital landscape.
Working on content interop super-ontology in the #mastodon, #micro.blog, #twitter, #feedland, and #wordpress multiverse.
Posts are actual pieces of content. They are mostly made on the platform where you find them.
Timelines are views into (yours and others’) posts. These views are made possible by transmitting information about the post via #RSS (or something else) and aggregating into a timeline. Timelines can include feeds from yours or others’ sources.
What’s interesting is that timelines can also be published and consumed, also via #rss.
This means that, if you consume a feed, you don’t know if the source-content in the feed originates with that feed. Feed elements could “pass through” as signs to their sources. In fact, it doesn’t even matter.
In this sense, we don’t want to replicate content around the networks, we want to replicate signs.
The agent-shaped org chart
Every real org has the same topology: principal, role-holder, specialists. Staff AI maps onto it, node for node, and the cost collapse shows up in the deliverables that were always just human-handoff overhead.
AI as staff, not software
Two frames for what AI is doing to work. The tool frame makes tools smarter. The staff frame makes roles unnecessary. Those aren't the same product, the same company, or the same industry.
Knowledge work was never work
Knowledge work was always coordination between humans who couldn't share state directly. The artifacts were never the work. They were the overhead — and AI just made the overhead optional.
The work of being available now
A book on AI, judgment, and staying human at work.
The practice of work in progress
Practical essays on how work actually gets done.
How do I get my dev team to adopt AI?
A stub on helping mixed-interest development teams find their own useful ways into AI.
Want to learn about agents? Talk to someone who ran an agency.
I spent 20 years running consulting engagements at Fortune 500 companies. Turns out that's the best preparation for running a fleet of AI agents ... because the problems are identical.
Your AI agents need a water cooler
We run a twelve-session AI fleet that coordinates through an IRC breakroom. A friend asked: why are you making AI agents act like humans? The answer turned out to be more interesting than the question.
ActivityPub spec
Explore the ActivityPub specification to understand how to write effective specs and enhance your web development skills.
The ur-post
Explore the concept of the ur-post and its role in microblogging, sources, and references in the digital content landscape.
Embracing the AI workforce
Discover how AI enhances the workplace by fostering collaboration and spontaneity, offering a fresh alternative to traditional office dynamics.