Data + AI Reading Dashboard
Curated signal for strategy, enterprise adoption, data foundations, governance, and technical fluency.
43 curated reads13 standing sourcesCurated 2026-09-24
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Highest-value reads now
Ranked by your filters, editorial priority, and what you have in progress. Deep reads are left out unless you pick “Deep read”.
5 picks · ~102 min total
ArticleHarvard Business Review12 min2026-03
To Scale AI Agents Successfully, Think of Them Like Team Members
Rahul Telang, Muhammad Zia Hydari & Raja Iqbal
Why it matters
Frames agents in the language of roles, boundaries, and accountability, which is how non-technical executives will want agent governance explained.
BlogAnalytics815 min2026-07
High priorityGetting the Semantic Model & Layer Right in the Age of AI
Analytics8 (with Christina Salmi)
Why it matters
Treats context, the semantic model, and the semantic layer as three steps in order. Clear language for explaining why agents fail on ungoverned data.
BlogAnthropic Engineering20 min2024-12
High priorityBuilding Effective AI Agents
Erik Schluntz & Barry Zhang
Why it matters
The clearest distinction between workflows and agents, and the case for starting simple. Gives you a vocabulary to push back on over-engineered agent proposals.
ReportMcKinsey & Company / QuantumBlack40 min2026-08
High priorityThe State of AI: Global Survey 2026
McKinsey QuantumBlack
Why it matters
The benchmark executives quote on AI adoption versus EBIT impact. Know its headline numbers on scaling and agents before your CFO or board brings them up.
NewsletterDeepLearning.AI15 min
High priorityThe Batch: this week's issue
Andrew Ng & DeepLearning.AI editors
Why it matters
One well-edited pass over the week's AI news. Ng's opening letter is a useful test of your own point of view before leadership conversations.
Curated library
The filters above apply here too. Status choices are saved on this device only.
ReportMcKinsey & Company / QuantumBlack40 min2026-08
The State of AI: Global Survey 2026
McKinsey QuantumBlack
The benchmark executives quote on AI adoption versus EBIT impact. Know its headline numbers on scaling and agents before your CFO or board brings them up.
Enterprise adoption / ROI / Executive strategy
SurveyROIAgentsScalingHigh priorityReadArticleHarvard Business Review12 min2026-03
To Scale AI Agents Successfully, Think of Them Like Team Members
Rahul Telang, Muhammad Zia Hydari & Raja Iqbal
Frames agents in the language of roles, boundaries, and accountability, which is how non-technical executives will want agent governance explained.
Agents / Technical / Enterprise adoption / ROI
AgentsOperating modelAccountabilityMetered paywallHigh priorityReadBlogAnalytics815 min2026-07
Getting the Semantic Model & Layer Right in the Age of AI
Analytics8 (with Christina Salmi)
Treats context, the semantic model, and the semantic layer as three steps in order. Clear language for explaining why agents fail on ungoverned data.
Data foundations / Agents / Technical
Semantic layerContextAI readinessHigh priorityReadBlogAnthropic Engineering20 min2024-12
Building Effective AI Agents
Erik Schluntz & Barry Zhang
The clearest distinction between workflows and agents, and the case for starting simple. Gives you a vocabulary to push back on over-engineered agent proposals.
Agents / Technical
AgentsWorkflowsDesign patternsHigh priorityReadNewsletterAINews / Latent Space10 min
AINews: today's issue
swyx & the smol.ai team
The earliest signal on model and tooling shifts, usually weeks before they show up in vendor pitches. Skim the headlines and move on.
AI news / Agents / Technical
DailyModelsToolingMedium priorityReadBlogAnalytics810 min2026-09
What Databricks' AI Spend Can Teach the Rest of Us
Analytics8
AI cost control is becoming a CFO conversation. Offers practical guardrails you can adapt no matter which platform you run.
Enterprise adoption / ROI / Data foundations
FinOpsAI spendDatabricksMedium priorityRead
Books & long-form
Books, substantial reports, and long papers, each with approximate time and the payoff that justifies it.
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Est. hours complete
ReportStanford HAI
~4 hrThe 2026 AI Index Report
Stanford Institute for Human-Centered AI
Intended payoff
Five or six defensible, sourced data points on cost, capability, and adoption trends for your own strategy materials. Start with the top takeaways and the economy chapter.
BookHarvard Business Review Press
~7 hrPower and Prediction: The Disruptive Economics of Artificial Intelligence
Ajay Agrawal, Joshua Gans & Avi Goldfarb
Intended payoff
A defensible framing for why your roadmap needs system redesign, not only point use cases, for board and executive discussions.
ReportNIST
~2 hrGenerative AI Profile (NIST AI 600-1)
National Institute of Standards and Technology
Intended payoff
A short list of the risks and suggested actions to adopt as controls in your AI policy and intake review.
Researchapplied-llms.org
~2 hrWhat We've Learned From a Year of Building with LLMs
Eugene Yan, Bryan Bischof, Charles Frye, Hamel Husain, Jason Liu & Shreya Shankar
Intended payoff
A build-versus-buy and team-staffing checklist for LLM products, plus the right questions for AI delivery reviews.
BookPortfolio / Penguin Random House
~6 hrCo-Intelligence: Living and Working with AI
Ethan Mollick
Intended payoff
A shared vocabulary and set of principles for workforce AI enablement and change management.
BookO'Reilly Media
~15 hrIntended payoff
Working fluency in evals, RAG, agents, and fine-tuning trade-offs, enough to lead technical design reviews with credibility.
BookO'Reilly Media
~20 hrDesigning Data-Intensive Applications
Martin Kleppmann
Intended payoff
A first-principles grasp of storage, replication, and streaming trade-offs to anchor data platform architecture decisions.
Standing sources
The newsletters, blogs, and research sites worth checking regularly. Links go to each public home page.
smol.ai / Latent Space
Daily recap of what AI builders are discussing across X, Discord and Reddit.
NewsletterDailyFree
swyx & Alessio Fanelli
The AI engineer's view of models, agents, and tooling, with essays alongside the podcast.
NewsletterWeekly+Free
DeepLearning.AI (Andrew Ng)
A calm, well-edited weekly digest with Andrew Ng's framing letter up top.
NewsletterWeeklyFree
Jack Clark
Research papers read through a policy and safety lens.
NewsletterWeeklyFree
Emerj Artificial Intelligence Research
Use-case briefs by industry, including manufacturing, written for enterprise buyers.
ArticleWeeklyFree
Olga Berezovsky
Practitioner analytics: metrics, retention, experimentation, and analyst craft.
NewsletterWeeklyMetered paywall
TDWI (Transforming Data with Intelligence)
Vendor-neutral research on data management, governance maturity, and AI readiness.
ResearchOngoingFree w/ registration
Harvard Business Review
How boards and CEOs frame AI, which is useful for aligning your language with theirs.
ArticleSeveral per weekMetered paywall
Harvard Business Review
Data strategy, data products, and operating-model pieces written for executives.
ArticleWeeklyMetered paywall
Analytics8
Consultancy perspective on data strategy, semantic layers, and platform ROI.
BlogFew per monthFree
Ethan Mollick
Evidence-grounded takes on how AI changes work and organizations.
BlogWeeklyFree
Simon Willison
Hands-on, skeptical notes on LLM tools, agents, and prompt-injection risk.
BlogDailyFree
World Economic Forum
Benchmarks for AI and digital use cases at award-winning factories and value chains.
ReportTwice yearly cohortsFree