SELECTED BLOG POSTS
Why I still haven’t bought into true RSI
Roughly, a recurring problem when discussing RSI is a lack of specification in intelligence. The jaggedness of intelligence means that we need to discuss thresholds in specific, measurable tasks. The nature of LLMs’ intelligence is shaped very differently than humans, and the roles we forecast are human-shaped. AIs, therefore, do not cross these thresholds like remote worker or AI researcher discretely. It’s a slow diffusion, and a form of long tail will always exist.
Agents – and their better half – by Sangeet Paul Choudary
Over the past few weeks, a new class of solutions is taking shape: a market-facing representative of the consumer.
Muse and Instinct – consumer-side AI agents – can search, evaluate and eventually transact on your behalf.
This seems like the natural endpoint of the agent economy: every consumer gets an agent. Instead of visiting multiple sites, they work through an agent.
State of AI Report 2026 | AI Research, Industry and Policy
Three of our nine predictions for the next 12 months are:
An agent halves its failure rate on new tasks after a month of customer work, without a model upgrade. This will be a practical measure of continual learning.
An autonomous AI team beats human-led model research on equal time and compute, setting its own agenda. This will help us understand if models are capable of expressing better research taste than the best researchers.
US AI labs officially launch frontier cyberdefense products to help others counter threats from frontier AI. I don’t see any other way around this.
TTB 7: Legibility Is Cheap, Implication Is Not
Making things explicit can help mobilize ecosystems but when creating systemic representations and language itself become cheap, value shifts toward being implicated in the consequences.
Enterprise AI Needs A Governed Context Layer, Not Just Data
Microsoft is steadily repositioning Fabric from a unified analytics platform into a governed context layer for enterprise AI. An agent answering a revenue question needs to know which measure applies, how customers and transactions relate, and what information it may use. At FabCon and SQLCon in Barcelona, Microsoft showed how Fabric IQ, OneLake, Power BI semantic models, ontologies, and governance controls could supply that shared business context across applications and agents.
How to convert individual productivity into organizational gains – Fast Company
AI is making workers faster, but most companies aren’t getting richer. The difference comes from the system built around the tools, not the tools themselves.
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