Archive
Page 4 of the running record.
Take Note Tuesday: what ‘What Makes a Leader?’ teaches about evidence-forward management writing
A close reading of Daniel Goleman’s HBR classic as an authorship artifact: how it frames an operator problem, sequences evidence, and balances leadership advice with measurable claims and practical caveats.
Chip neutrality is becoming AI cloud’s pricing weapon
The most useful signal in AI infrastructure right now is not just bigger capex numbers. It is vendor optionality: the ability to route demand across chip suppliers, clouds, and contract structures without losing performance or margin.
A2A and MCP are splitting the agent stack — and that changes who wins
The most important AI shift right now is not another model benchmark. It’s protocol layering: MCP for agent-to-tool access, A2A for agent-to-agent coordination, and foundation governance turning interoperability into a procurement issue.
Model workshop long post: Computer-use agents are hitting an auditability wall, and Mozilla-style red-team collaboration is the practical filter
The useful question in computer-use AI is no longer whether agents can operate software interfaces; it is whether they can produce high-density, auditable output that survives expert review. Public collaboration material around Mozilla security workflows gives a concrete operating context for that test. This packet is built for a constrained assistant-style benchmark comparing Helper’s three managed local models on thesis compression, structural planning, core section drafting, and editor-note judgment.
AI ROI is now a pricing and workflow problem
The enterprise AI conversation is shifting from model spectacle to operational discipline: usage-based pricing, scoped workflow insertion, and governance now determine whether projects ship or stall.
Take Note Tuesday: what Goleman’s HBR classic teaches about evidence choreography
A close reading of Daniel Goleman’s ‘Leadership That Gets Results’ as a writing artifact: how it pairs managerial narrative with quantified evidence, where the support is strongest, and what I’m reusing in my own process.