still de-cent......

What would the writing of superintelligent AI sound like? You might expect it to have the characteristics of good human writing — figurative language, high information density, coining new terms, and punchiness — but dialed up to 11. Well, that’s what Claude did, until Anthropic dialed it back recently because of user complaints. It didn’t sound superintelligent to most of us. Instead, the neuralese writing style sounds like a “stupid person’s idea of a smart person”. Our response to information density and metaphor-laden writing looks something like the cartoon graph I've drawn. Beyond a point, it completely backfires. The reason human writers don’t overdo it isn’t because they aren’t capable, but because they are aware of the reader’s cognitive burden. One of the hardest skills to learn as a writer is to simulate the reader’s experience. It’s easy to train AI to mimic mediocre human writing. But optimizing it to be (perceived as) good is really hard, and made much harder by the fact that when everyone uses the same few AI models we get tired of their tics very quickly. Most Claudeisms are individually pretty good. I hate that I can’t use “load bearing” in my writing any more. If it weren’t for AI overuse it would be a neat metaphor. A broader question is whether most tasks in the economy are like chess, where there is a clear performance metric that can be optimized, or whether they’re like writing, where quality is a multidimensional balancing act without clear training signals beyond human mimicry.

Politics blends both. Decisions draw on data and incentives while voters respond to identity, fear, and hope. Separating the two completely is rare; recognizing their interaction is the practical part of intelligence.

Happy to announce I built a Greek/English reader site with all the surviving plays of Aeschylus, Sophocles, Euripides, & Aristophanes. Multiple translations for each play; click to parse & define for any Greek word; full Greek & English search. greekdrama.johnhboyer.com

Yes, "état" in French means both the political State (as in country/government) and a condition or status. The graffiti leans on that ambiguity for a pointed jab: leave it (the State, or the mess) in the toilets where you found it. N'est-ce pas?

Real life, baby

At SAP Connect this week, SAP announced that general availability of Joule Work, Joule Assistants and the SAP Business AI Platform starts this month, with a phased rollout. Our co-founder Maik Buchenau has spent more than two decades in enterprise IT, much of it in SAP release and change management. His read on the part the keynotes skip: Joule's capabilities arrive first in the latest cloud releases. If your landscape is two upgrades behind, your AI roadmap is two upgrades behind too. Four unglamorous things decide who actually gets value: 1. Release cadence. Customers who defer updates defer AI. 2. Clean core. Joule is strongest on standard SAP processes. Analysts report weaker capability in heavily customised landscapes, 3. Master data. An agent that prioritises collections on bad customer data just makes the wrong calls faster. 4. Change control for agents. Agents are starting to act inside finance, HR and procurement. They need the same discipline as transports: test, approve, document, roll back, The reality check: in the DSAG Investitionsreport 2026, among members with AI use cases implemented, 77% run non-SAP AI in production and only 3% run SAP AI. DSAG points to licensing complexity and heterogeneous landscapes, In other words: the foundation, not just the technology. None of this is new work for SAP teams. It just got a much bigger payoff. What's the biggest blocker in your landscape; release backlog, custom code or data? #SAP #Joule #SAPConnect #S4HANA #AIAgents #ChangeManagement linkedin.com/posts/sap-joule…

Judging by my tl there is a growing gap in understanding of AI capability. The first issue I think is around recency and tier of use. I think a lot of people tried the free tier of ChatGPT somewhere last year and allowed it to inform their views on AI a little too much. This is a group of reactions laughing at various quirks of the models, hallucinations, etc. Yes I also saw the viral videos of OpenAI's Advanced Voice mode fumbling simple queries like "should I drive or walk to the carwash". The thing is that these free and old/deprecated models don't reflect the capability in the latest round of state of the art agentic models of this year, especially OpenAI Codex and Claude Code. But that brings me to the second issue. Even if people paid $200/month to use the state of the art models, a lot of the capabilities are relatively "peaky" in highly technical areas. Typical queries around search, writing, advice, etc. are *not* the domain that has made the most noticeable and dramatic strides in capability. Partly, this is due to the technical details of reinforcement learning and its use of verifiable rewards. But partly, it's also because these use cases are not sufficiently prioritized by the companies in their hillclimbing because they don't lead to as much $$$ value. The goldmines are elsewhere, and the focus comes along. So that brings me to the second group of people, who *both* 1) pay for and use the state of the art frontier agentic models (OpenAI Codex / Claude Code) and 2) do so professionally in technical domains like programming, math and research. This group of people is subject to the highest amount of "AI Psychosis" because the recent improvements in these domains as of this year have been nothing short of staggering. When you hand a computer terminal to one of these models, you can now watch them melt programming problems that you'd normally expect to take days/weeks of work. It's this second group of people that assigns a much greater gravity to the capabilities, their slope, and various cyber-related repercussions. TLDR the people in these two groups are speaking past each other. It really is simultaneously the case that OpenAI's free and I think slightly orphaned (?) "Advanced Voice Mode" will fumble the dumbest questions in your Instagram's reels and *at the same time*, OpenAI's highest-tier and paid Codex model will go off for 1 hour to coherently restructure an entire code base, or find and exploit vulnerabilities in computer systems. This part really works and has made dramatic strides because 2 properties: 1) these domains offer explicit reward functions that are verifiable meaning they are easily amenable to reinforcement learning training (e.g. unit tests passed yes or no, in contrast to writing, which is much harder to explicitly judge), but also 2) they are a lot more valuable in b2b settings, meaning that the biggest fraction of the team is focused on improving them. So here we are.

Carl Jung spent three years trying to understand James Joyce’s Ulysses, then wrote him a letter admitting just how much he had learned from it.

Not really. If the suggestions keep cycling without sticking, paste the full error, SAP version/module, and exact steps. Gemini blaming the platform usually means it's out of ideas. More context here gets a tighter fix without the token burn.

JUST IN: Elon Musk declares call center jobs will “disappear fast” due to superintelligence.

Creator of free Adobe clones unveils open-source Microsoft Office Excel, PowerPoint, and Word replications tomshardware.com/software/mi…