Mon · 13 Jul 2026·Issue 032
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Week ofMarch 23 / 202605 stories / 3 bonus / ~39 min total

The Reading List.

Contents01What 81,000 people want from...02Reimagine learning and development for...03Geopolitics and the geometry of...04Measuring progress toward AGI: A...05Analyzing the passage of state-level...
01
/ LEADRead Sunday
Bucketbusiness
LevelAccessible
SourceAnthropic
Read8 min

What 81,000 people want from AI

Anthropic used an “AI interviewer” to collect open-ended interviews at massive scale from 80,508 Claude users across 159 countries and 70 languages. The value here isn’t just the headline count—it’s a grounded map of what people actually want (time savings, better work, life management) alongside what they fear (jobs, reliability, loss of control), which is more actionable than generic “AI optimism vs doom” debates.

Read on Anthropic ->
# adoption# work# society
02
Read Wednesday
Bucketbusiness
LevelIntermediate
SourceMcKinsey
Read6 min

Reimagine learning and development for the AI age

McKinsey argues the biggest scaling constraint isn’t model access—it’s workforce capability and operating-model design. The practical guidance is to move learning into the flow of work, make managers the multiplier (not the bottleneck), and tie skilling to measurable business outcomes instead of generic “AI literacy.”

Read on McKinsey ->
# skills# workforce# change
03
Read Sunday
Bucketbusiness
LevelIntermediate
SourceMcKinsey Global Institute
Read12 min

Geopolitics and the geometry of global trade: 2026 update

MGI’s update frames global trade around three forces: geopolitical “tariff splashes,” AI-driven demand shifts, and the ripple effects across supply chains. The AI-adjacent value is concrete: semiconductors and data-center equipment show up as strategic trade flows, which turns compute capacity into a budgeting + procurement + geopolitics problem—not just a technical one.

Read on McKinsey Global Institute ->
# geopolitics# datacenters# semiconductors
04
Read Friday
Bucketmodels
LevelIntermediate
SourceGoogle DeepMind (Google Blog)
Read6 min

Measuring progress toward AGI: A cognitive framework

DeepMind proposes a cognitive-science-inspired taxonomy (abilities like memory, reasoning, executive function, social cognition) and a protocol for benchmarking models against human performance distributions. The important stance is measurement: before arguing “how close to AGI,” we need shared evaluation language and better tests for missing abilities.

Read on Google DeepMind (Google Blog) ->
# evaluation# benchmarks# agi
05
Read Friday
Bucketregulation
LevelIntermediate
SourceBrookings Institution
Read7 min

Analyzing the passage of state-level AI bills

Brookings analyzes what predicts whether state AI bills get introduced and whether they actually pass, highlighting that outcomes depend heavily on political and coalition dynamics—not just policy text quality. Useful if you’re trying to forecast where compliance requirements will show up first in the U.S. and how fragmented the near-term landscape may get.

Read on Brookings Institution ->
# policy# states# governance

Bonus material

For the curious.

Optional / 03 reads

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