Mon · 13 Jul 2026·Issue 032
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Back to this week
Week ofApril 13 / 202605 stories / 3 bonus / ~24 min total

The Reading List.

Contents01States are struggling to meet...02Want to use AI to...03Project Glasswing: Securing critical software...04Concept Note: AI RMF Profile...05Inside the AI Index: 12...
01
/ LEADRead Sunday
Bucketbusiness
LevelAccessible
SourceAP News
Read6 min

States are struggling to meet their clean energy goals. Data centers are to blame

As AI-driven data centers multiply, utilities are warning they may not be able to meet surging electricity demand without adding fossil generation, putting state clean-energy targets at risk. This is a useful “AI is infrastructure” reality check: the bottleneck isn’t just chips and models—it’s power, permitting, and who pays for grid upgrades.

Read on AP News ->
# datacenters# energy# infrastructure
02
Read Wednesday
Bucketbusiness
LevelAccessible
SourceMIT Sloan
Read4 min

Want to use AI to plan your retirement? Here’s how to proceed

A practical guide to using AI for retirement planning without outsourcing judgment: how to ask better questions, sanity-check outputs, and avoid “confidently wrong” assumptions about taxes, fees, and risk. Good for non-technical readers because it treats AI as a planning copilot—useful for scenarios and checklists—rather than a decision maker.

Read on MIT Sloan ->
# finance# decision-making# risk
03
Read Friday
Buckettools
LevelIntermediate
SourceAnthropic
Read5 min

Project Glasswing: Securing critical software for the AI era

Anthropic is convening a cross-industry initiative aimed at finding and fixing high-severity vulnerabilities faster than traditional processes can. The key takeaway is defensive scaling: as AI makes vulnerability discovery cheaper for attackers, defenders need automated vulnerability hunting and faster patch pipelines to keep the “time-to-exploit” from collapsing.

Read on Anthropic ->
# cybersecurity# software# defense
04
Read Friday
Bucketregulation
LevelAccessible
SourceNIST
Read3 min

Concept Note: AI RMF Profile on Trustworthy AI in Critical Infrastructure

NIST is developing a “profile” that translates the AI Risk Management Framework into concrete guidance for critical-infrastructure operators (energy, water, transportation, etc.). For non-technical leaders, this is useful because it turns abstract “trustworthy AI” talk into requirements you can hand to vendors and internal teams.

Read on NIST ->
# standards# risk# infrastructure
05
Read Sunday
Bucketmodels
LevelAccessible
SourceStanford HAI
Read6 min

Inside the AI Index: 12 Takeaways from the 2026 Report

Stanford HAI distills the AI Index into 12 plain-English takeaways: faster capability gains, a widening gap in measurement and transparency, rising environmental costs, and early signs of workforce disruption. The value is that it’s data-backed and broad—useful for non-technical readers who want to understand “what changed this year” without drowning in benchmarks.

Read on Stanford HAI ->
# ai-index# trends# measurement

Bonus material

For the curious.

Optional / 03 reads
arXiv

AI Disclosure with DAISY

A timely HCI study showing structured disclosure can improve transparency around AI use in writing/research without making authors less comfortable.

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