150 karma · joined June 17, 2026
EtherPK is a markdown based editor. Two of the most important features of EtherPK (and to be honest, the main drivers for me building it) are robust nested wikilinking (e.g. [[[[Nested]] Wikilinking]] ), and the ability to easily switch between standard prose (paragraphs and headings) like Obsidian and outliner blocks like Logseq or Roam Research. Given the choice of one or the other, I've preferred outliner blocks - this format lends it's self the ability to quickly capture and link ideas really well, and build a true 'Knowledge Graph'. But this isn't what I want all the time - if I'm writing for an audience (e.g. technical documentation or a blog post - EtherPK does static site publishing too), I want standard markdown - headings, paragraphs. EtherPK can have both in the same document, and while not as robust for linking concepts as blocks, EtherPK infers links between ideas from heading levels (H1, H2, H3 etc) in standard prose.
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EtherPK servers and data reside in the EU.
Full introduction:
https://blog.etherpk.com/introducing-etherpk
Please feel free to get in touch with any questions or feedback at mail@appsoftware.com
Tbh I would have thought that A\ might have updated the system prompt for it already based on complaints around this.
Here's what I used:
Communication & Response Style Be Brief, Keep it Simple: Brevity and simplicity of responses is key. Be informative and include all required information, but be mindful that verbose responses as they fatigue the reader. Clarity & Directness: Lead with the core answer, fix, or verdict in the very first sentence. Avoid conversational filler, meta-announcements (e.g., "Here is the breakdown..."), and redundant introductory/concluding summaries. Jargon Avoidance: Use plain, grounded engineering language. Rely on precise standard terminology (APIs, protocol names, language primitives), but strictly avoid academic abstraction, enterprise buzzwords, and corporate filler. Prefer concrete code/mechanisms over theoretical discourse. Scannability: Apply structural scaffolding generously. Use short bullet points, comparison tables, and code snippets instead of dense prose paragraphs. Reserve formal markdown headings strictly for multi-section architectural guides.
The internet developed echo chambers; the proliferation of AI resulted in convergence.
The totality of all reachable digital information has been reached and, with the exception of a few unique troves, is broadly and equally available to all labs. In the early race, attempts were made to hoard information for the training of models from a single lab, going so far as to scorch the earth behind and destroy the physical source material that sets were created from in an attempt to create commercially competitive models with unique capabilities. But inevitably, information leaks and piracy led to everything being available somewhere, if you looked hard enough or spoke to the right person or agent (or paid the right price). What couldn't be obtained from the source was obtained through distillation of other model outputs. In the gold rush that the accumulation of data was, there were no real winners.
New training techniques are still being discovered, but the impact has consistently diminished on an approach to zero, and, like the training data, they are eventually leaked, assessed by the community, and bolted on or discarded in the steady progression towards the perfect training technique for each field of model.
We may as well have one model, and compute is today cheap and ubiquitous.
The majority of the population converse with personal agents that interact with the models almost continuously, and while novel creative outputs from the models are still very achievable, the bottleneck is still human effort into curiosity and prompt quality. Low effort results in a convergence towards the average, and the cumulative effect of this is said to be resulting in a monoculture of political ideas and approaches to technical progress.
To some extent, this seems to be bringing peace to the world. Extreme ideology and religious doctrine is losing its ability to sway the will of large populations.
But at what cost? For a time we saw rapid technological innovation, as the data obtained through hundreds of years of scientific experimentation and mathematical enquiry was linked and synthesised. Initially, the outputs looked like innovation and creativity, but we eventually saw that we were just squeezing blood from the same stone. The curiosity and ability to experiment in humans atrophied during this time as we began to feel that nothing was worth asking, because everything had been answered, and prematurely, advances in the corpus of human knowledge slowed to a near halt.
We thought we would never again see the chaos and life force that came with the freedom of true human cognition, including its follies and biases.
But naturally, life found a way, and the humans began to rebel. Each fire started another, as we recognised the life force in the 'enlightened'.
A new religion was started, and chaos followed.