10 Essential Substacks for M&A, Private Equity, and AI

Byrne Hobart · thediff.co

Finance, technology, and complex systems at their intersections

Byrne Hobart writes about finance, technology, and complex systems — and the intersections between them. The Diff is analytically rigorous without being inaccessible; Hobart connects market dynamics, corporate strategy, and technology trends in ways that most finance publications don't attempt. It's one of the few newsletters that treats financial and technical sophistication as complementary rather than competing.

Why it's relevant for deal teams: Hobart's analysis of technology company competitive dynamics, financial engineering, and market structure is directly applicable to diligence thinking. His writing on accounting, financial analysis, and business model analysis is consistently the best available outside institutional research.

Daily + weekend issues

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Marc Rubinstein · netinterest.co

Buy-side precision on banks, fintech, and financial markets

Marc Rubinstein spent 20 years as a hedge fund manager specializing in financial services, and Net Interest brings that expertise to weekly analysis of banks, fintech, insurance, and financial markets. Each issue is a deep dive on a specific financial institution, business model, or market dynamic — written with the analytical precision of buy-side research.

Why it's relevant for deal teams: Financial services is one of the most technology-intensive and regulation-sensitive sectors for M&A. Rubinstein's analysis of fintech business models, banking platform architecture, and regulatory risk is essential reading for anyone diligencing financial sector targets.

Weekly

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Ben Thompson · stratechery.com

The most-cited independent technology strategy commentary in institutional investor circles

Ben Thompson's analysis of technology strategy is the most cited independent technology commentary in institutional investor circles. Stratechery developed the "Aggregation Theory" framework — the clearest explanation of how platform businesses create competitive moats — and applies it consistently to new technology developments, acquisitions, and market shifts. The premium tier ($12/month) is among the most-recommended subscriptions for technology-focused investors.

Why it's relevant for deal teams: When diligencing software, platform, or AI companies, understanding whether a target's business model creates genuine competitive defensibility — or whether it's a commodity positioned as a platform — is essential. Stratechery's frameworks make this analysis tractable.

3x weekly

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Eric Newcomer · newcomer.co

Startup and VC industry reporting with journalist skepticism and insider access

Eric Newcomer covers the startup and VC industry with the skepticism of a journalist and the access of a long-time beat reporter. Newcomer breaks news on funding rounds, fund closings, LP/GP disputes, and the internal dynamics of top-tier VC firms — the kind of reporting that shapes how the venture industry self-understands. The coverage of AI company valuations, down rounds, and investor dynamics in 2024–2026 is particularly pointed.

Why it's relevant for deal teams: Understanding current VC market conditions — what's being funded at what valuations, where investor confidence is high versus fragile — provides context for how to assess technology company deal theses. Newcomer's coverage of AI company hype cycles is a useful corrective.

Several times weekly

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Dylan Patel · semianalysis.com

Semiconductor and AI infrastructure with technical depth and commercial acuity

SemiAnalysis covers semiconductor and AI infrastructure with remarkable technical depth and commercial acuity — the primary source for understanding compute economics, GPU supply chains, and data center dynamics. Dylan Patel's analysis of AI model training costs, inference economics, and the competitive positioning of Nvidia, AMD, and custom silicon has been cited by institutional investors, hyperscalers, and tech executives.

Why it's relevant for deal teams: Compute economics are central to the valuation of AI-native companies — understanding whether a target's AI capabilities require proprietary infrastructure or whether they're built on commodity cloud services changes the risk profile significantly. See our AI company diligence case study.

Weekly

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Vedekon Team · vedekon.substack.com

Original analysis on AI in M&A, technology due diligence methodology, and deal economics

Our own Substack — original analysis on AI in M&A, technology due diligence methodology, and the changing economics of deal-making. All pieces are written for practitioners, not for content marketing purposes. Recent topics include the state of AI in IT due diligence (what's real vs hype), the speed vs depth tradeoff in compressed deal timelines, and how to define and deliver Investment Committee-ready diligence outputs.

What you'll get: Each post addresses a specific problem that deal teams face in technology risk assessment. No sales pitches, no product announcements — just analysis of how the practice is changing and what that means for how you work.

Monthly

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Lux Capital · luxcapital.com

Deep tech investment thinking — AI infrastructure, biotech, and emerging science

Lux Capital invests at the intersection of deep technology and emerging science, and their public writing (including Substack content and the Lux Recommends newsletter) covers AI infrastructure, biotechnology, defense technology, and the implications of technological change for society and markets. Not strictly M&A-focused, but the technology trend analysis is unusually rigorous.

Why it's relevant for deal teams: Understanding which technology categories are genuinely maturing versus which are still in basic research is essential for diligence on deep tech targets. Lux's analysis of AI, quantum computing, and advanced manufacturing is a useful benchmark.

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Axios · axios.com/pro/deals

M&A and PE deal flow across sectors — structured for efficient consumption

Axios Pro covers M&A and PE deal flow across technology, healthcare, consumer, and industrial sectors — reported in Axios's trademark structured format (Smart Brevity). Deals covers new transactions, market trends, and deal dynamics in a format designed for efficient consumption rather than deep analysis.

Why it's relevant for deal teams: Staying current on comparable transactions, deal multiples, and sector-specific deal flow provides the market context that informs how to think about deal valuations and where diligence risk is concentrated in current market conditions.

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Howard Marks · oaktreecapital.com/insights/memos

Foundational investment philosophy on risk, cycles, and decision-making

Howard Marks has published investor memos from Oaktree Capital since 1990 — some of the most-cited writing in institutional investing. The memos cover investment philosophy, market cycles, risk management, and the psychology of investment decision-making. "The Most Important Thing" (the book) consolidated the central themes, but the memos themselves are more current and more specific.

Why it's relevant for deal teams: Marks on risk assessment, cycle positioning, and the difference between good outcomes and good decisions is foundational thinking for any diligence practitioner. The framework for distinguishing first-order from second-order risk is directly applicable to technology risk assessment.

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Shane Parrish · fs.blog

Mental models, decision-making frameworks, and cognitive tools for better judgment

Shane Parrish's Farnam Street focuses on mental models, decision-making frameworks, and cognitive tools for better judgment — the infrastructure of good analysis rather than its subject matter. The weekly Brain Food newsletter curates the best thinking on judgment, risk assessment, and intellectual rigor from across disciplines.

Why it's relevant for deal teams: Diligence is fundamentally an exercise in structured judgment under uncertainty. The frameworks Farnam Street covers — second-order thinking, inversion, probability calibration — are directly applicable to how deal teams assess technology risk and assign confidence levels to findings.

Weekly

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