The hottest Strategy Substack posts right now

And their main takeaways
Category
Top Business Topics
Stealing Signals • 259 implied HN points • 01 Nov 24
  1. NFL games are improving in quality this season, with fewer boring games, which is great for viewers.
  2. Athletes often make unexpected mistakes in the heat of the moment, like dropping the ball before scoring, which can be hard to understand.
  3. There are uncertain player performances and roles in upcoming games, making it tough to predict how they'll do, especially in teams with injuries.
Faster, Please! • 1188 implied HN points • 19 Mar 26
  1. A single energy chokepoint like the Strait of Hormuz can quickly shock the global economy, driving up fuel, food, and industrial costs.
  2. The damage from such shocks depends on how much the world still relies on that chokepoint, and that reliance can be reduced over time by changing energy systems.
  3. Democracies should treat energy policy as a core strategic priority, accelerating electrification and domestic clean energy to boost resilience and reduce vulnerability.
Big Technology • 8131 implied HN points • 20 Feb 26
  1. AI is being pushed to replace the old practice of writing to think, which risks making decisions shallower and eroding the discipline of clear, precise narratives.
  2. Internal generative tools are often unreliable and hallucinate, yet employees face heavy pressure to use them without adequate training, guidance, or measures of impact.
  3. The workforce is split between veterans who resist and newer employees who comply out of fear, producing higher volume expectations, lower-quality work, and a shift in company culture.
Marcus on AI • 11777 implied HN points • 13 Feb 26
  1. OpenAI's technical lead is slipping as Google, Anthropic, and several Chinese firms largely catch up, eroding its competitive edge.
  2. Major backers are pulling back or signaling uncertainty — Nvidia scaled back a big pledge and SoftBank's top investor is wavering — which raises serious questions about future funding.
  3. OpenAI is burning cash and may have limited runway, so if venture funding dries up it could need a bailout and would likely lose talent to competitors.
OSS.fund Newsletter • 56 implied HN points • 26 Mar 26
  1. Buyers have shifted — they are more informed, hypothesis-driven, and expect fast, measurable results instead of broad discovery or generic workshops.
  2. AI-native competitors win by showing up narrow and pragmatic, offering tight scopes, quick proofs, and practical data-governance that remove friction.
  3. Traditional IT services can stay relevant by upgrading commercial skills with hands-on drills that turn messy account context into next steps, tighten proposals, handle governance, and prove value quickly.
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The Chip Letter • 5023 implied HN points • 12 Feb 26
  1. In the 2000s AMD reshaped itself by selling its flash-memory unit, buying ATI for graphics, and spinning off its chip factories, which changed the company’s business model.
  2. The company mounted a major legal and strategic challenge to Intel that was a high-risk move, producing intense conflict and short-term financial pain that led to leadership change.
  3. AMD’s fortunes later recovered under new leadership, so today’s success is the result of both those risky early moves and subsequent execution rather than any single decision.
Investing 101 • 55 implied HN points • 11 Mar 26
  1. Multidisciplinary skunkworks like Imagineering bring artists, engineers, storytellers, and others together to turn creative uncertainty into tangible products. They act as permanent studios that translate ideas into real experiences.
  2. Flagship Pioneering is a repeatable biotech incubator model that has spawned huge winners like Moderna and demonstrates how a discovery mechanism can generate major portfolio value. It shows the power of intentionally building companies from uncertainty.
  3. With AI creating exponentially more uncertainty, there’s a clear opportunity to adapt the Flagship model to systematically find and build AI deployment businesses. Replicating that incubator approach could turn AI-driven uncertainty into productive, investable companies.
The Algorithmic Bridge • 658 implied HN points • 12 Mar 26
  1. Automating tasks inside an existing system usually doesn’t kill jobs; whole roles disappear when a new paradigm makes those tasks pointless.
  2. Treating AI like a drop‑in replacement (ATM thinking) overestimates its short‑term impact because AI is unreliable, struggles with edge cases, and institutions resist replacing humans.
  3. The real disruptive path is designing new businesses and systems around AI from scratch, creating ā€˜zero‑man’ models that make entire jobs or industries irrelevant.
High ROI Data Science • 119 implied HN points • 29 Oct 24
  1. Information asymmetry is when one group knows more than another. This can create unfair advantages in social systems and businesses.
  2. The Werewolf Game illustrates how a small, informed group can control the majority. This game teaches us about strategy and deception in group dynamics.
  3. To protect ourselves from manipulation, we need to build mental firewalls. Knowing about information asymmetry helps us fight back against unfair advantages.
The Beautiful Mess • 912 implied HN points • 11 Mar 26
  1. Vague problem statements like ā€œmake the app easierā€ don’t help — be specific about what’s broken, why it matters, and what outcomes you want so you can diagnose and measure impact.
  2. Look at problems from multiple levels — user behavior, surrounding context, incentives, and long‑term strategy — and move between those views to test assumptions and find the real crux.
  3. Don’t jump to simple fixes; investigate trade‑offs, who relies on the data, and how changes shift work downstream, and create shared understanding so the team can navigate complexity together.
Software Design: Tidy First? • 1369 implied HN points • 23 Feb 26
  1. Work runs in three modes — Explore, Expand, and Extract — and each mode has different goals and tradeoffs, so manage projects differently as they move between them.
  2. In Explore mode, set bold, learning-focused goals and expect to hit roughly half of them (P50); finding surprising value is more important than finishing every planned task.
  3. Keep explorations as independent as possible because they’re fragile and delay-sensitive, while extraction accepts dependencies and demands reliability, so structure teams and processes to match the phase.
Gad’s Newsletter • 26 implied HN points • 23 Mar 26
  1. UPS deliberately shrank its post‑pandemic network and cut low‑margin Amazon volume because the expanded capacity no longer matched demand and was destroying profits. The company is trading top‑line volume for a leaner operation to restore margins by closing buildings and cutting roles.
  2. Contraction is being paired with a big automation and technology bet — about $9 billion in robotics, RFID, and facility upgrades — to replace manual labor and rebuild a smaller, denser network around higher‑margin healthcare, SMB, and premium shipments. The goal is to raise revenue per piece and reduce labor intensity.
  3. Execution and timing are the key risks: union pushback, automation delays, and a leaner FedEx competing on price could undermine savings or leave the network underutilized. Getting closures, route consolidation, and automation sequenced correctly is essential to avoid degraded service or margin pressure.
Why is this interesting? • 1085 implied HN points • 19 Feb 26
  1. Nostalgia gives revived local brands a built-in advantage because consumers already understand and trust them. That makes it much easier to win buyers than starting a new brand from scratch.
  2. When a local brand is backed by a powerful retailer, it can use low prices, preferential shelf space, and deep distribution to dominate daily purchase channels. That systems-level muscle multiplies the effect of nostalgia in ways global firms struggle to match.
  3. As geopolitical fragmentation and rising local confidence reshape markets, belonging and local identity can trump global scale. This doesn't doom giants like Coca-Cola, but it ends the automatic assumption that the biggest players will always win.
Doomberg • 7496 implied HN points • 27 Dec 25
  1. The merger pairs a loss-making Trump Media shell with an early-stage fusion company, which makes little strategic sense and looks driven more by market access and publicity than sound business logic.
  2. TAE’s work so far is limited to lab demonstration reactors that haven’t achieved net energy gain, so promises to begin building a utility-scale fusion plant next year are premature and mostly amount to buying land and permits.
  3. Hype about near-term fusion distracts from proven civilian nuclear options and risks misallocating capital and undermining the existing nuclear industry for little practical return.
Marcus on AI • 12726 implied HN points • 03 Dec 25
  1. OpenAI is under urgent competitive pressure as rival models have closed the gap, prompting emergency efforts and noticeable user departures.
  2. The company has overextended financially, burning huge sums with modest revenue and likely only a limited runway, which makes future fundraising riskier.
  3. If OpenAI stumbles, the fallout could ripple through investors, chip suppliers, partners, and pension funds, and could even prompt talk of government intervention.
Fish Food for Thought • 57 implied HN points • 18 Mar 26
  1. Keep exploration ongoing and protected alongside exploitation; a persistent minority of work should always sample the unknown as insurance against change.
  2. Design teams and incentives for different modes: optimize exploit teams for stability and throughput, and set up explorer teams for fast learning with permission to fail and a clear path to scale winning bets.
  3. Treat your roadmap as a diversified portfolio, not a fixed plan—accept short-term inefficiency and noisy metrics because exploration buys future resilience, and continuously rebalance resources rather than pretending the tension is solved.
The Future Does Not Fit In The Containers Of The Past • 97 implied HN points • 08 Mar 26
  1. AI is not just a tool but a new kind of "brain" that works much faster than humans and will change how knowledge is created, shared, and valued.
  2. People win by leaning into what machines can't do — intuition, imagination, insight, and human interaction — and by learning to embrace, adapt to, and complement AI.
  3. A big portion of current tasks will disappear quickly, so firms must stop chasing only efficiency and instead redesign business models and roles, using AI as infrastructure to build new value.
Glenn’s Substack • 1378 implied HN points • 04 Sep 24
  1. Ukrainian military losses are rising, which is common as wars reach their final stages. When a side is losing, they often struggle with resources, morale, and communication.
  2. The situation in Ukraine is worsening with fewer troops and equipment. As their frontlines weaken, many soldiers are defecting or surrendering, leading to a chaotic military environment.
  3. NATO faces difficult choices in response to the war. There's growing pressure to either negotiate peace or increase involvement, while the risk of a direct conflict with Russia looms large.
Software Design: Tidy First? • 1811 implied HN points • 04 Feb 26
  1. Seeing AI’s value only as labor replacement is too narrow; AI also raises company value by increasing revenue, shifting timing of cash flows, and creating optional future paths.
  2. AI can boost revenue and growth by scaling human work, enabling personalization at scale, and adding new features customers will pay for, not just by cutting headcount.
  3. AI creates optionality and timing benefits—like deferred hiring or infrastructure, access to new markets and business models, and faster experimentation—that increase value beyond immediate cost savings.
Superfluid • 79 implied HN points • 08 Mar 26
  1. AI is removing the need to navigate complex interfaces. Jobs built on knowing which buttons to push are disappearing, while roles requiring deep expertise, judgment, and taste stay valuable.
  2. Most people and companies use AI only superficially, so there’s a big gap between casual experiments and truly optimizing work with AI. Deep, compounding AI use is rare and is where the real productivity gains and advantages lie.
  3. White-collar work is splitting into elite tastemakers and standard role players as teams shrink and AI takes over execution. To remain valuable, become scarce by developing exceptional skill, influence, or trusted relationships.
The Beautiful Mess • 555 implied HN points • 04 Mar 26
  1. Keep consistency minimal and practical. Choose a few shared concepts, rituals, or templates that actually help people do their work, not broad vague pillars.
  2. Expect variation and avoid dogma. Ideas spread unpredictably, so let teams adapt frameworks to their context instead of forcing uniform implementations.
  3. Use consistency as a scaffold with an expiration. Introduce temporary rules to stabilize change but set a reassessment date, and prefer nudges like defaults, templates, and visibility over heavy mandates.
The Algorithmic Bridge • 498 implied HN points • 03 Mar 26
  1. A tiny minority of users capture most of AI's real productivity gains while almost everyone else uses it superficially. Power users use the platform's high-value "thinking" features roughly seven times more than the median paid user.
  2. AI's benefits are unevenly distributed across people, companies, and regions, creating concentrated pockets of supercharged productivity. Many large organizations and most users still haven't plugged AI into everyday workflows, so the gains remain localized.
  3. The standard adoption playbook fails because people don't know how to integrate AI into their existing work; hype and basic rollout aren't enough. Closing the gap requires teaching practical skills, encouraging practice, and embedding AI into real workflows.
One Useful Thing • 2598 implied HN points • 27 Jan 26
  1. Agentic AI lets people build working prototypes and explore multiple startup ideas far faster and much cheaper than before, cutting months and big costs out of early-stage work.
  2. Decide when to delegate by weighing how long the task would take you, how likely the AI is to succeed, and how much time it takes to prompt and review outputs. Improving the AI's success probability or lowering review overhead makes delegation more worthwhile.
  3. Traditional management skills—clear goals, specific deliverables, limits of authority, and good feedback—are now the key to getting useful work from AI agents, and common documents like PRDs or orders make excellent prompts.
The Beautiful Mess • 714 implied HN points • 25 Feb 26
  1. Shipping creates the potential for outcomes rather than delivering final results, and each change starts a chain of hypotheses and assumptions you must test. Uncertainty in those links is normal and points to where you need to learn or take a leap.
  2. Changes usually set off multiple impact paths that affect different users, metrics, and timeframes. Start with clear, actionable inputs, name the immediate effects you expect, and connect those to longer-term outcomes.
  3. Strategy and research help you choose where to act, form causal hypotheses, and decide what signals to measure instead of only chasing lagging metrics. Build a roadmap of researched options, set goals for actions or early signals as well as long-term results, and iterate.
The Beautiful Mess • 1163 implied HN points • 13 Feb 26
  1. Understanding is produced through interactions, not by assembling static background information. Context emerges as people engage with each other, their bodies, tools, and environment.
  2. AI and context engineering often treat context as a package you can merge, which pushes work toward solitary recombination of information. That model mistakes more data for understanding and ignores how interaction shapes meaning.
  3. Leaders should act as interaction designers, shaping dialogue, scenarios, and feedback loops so intent becomes the context for action. They must also recognize some decisions can use documented context while others require real-time coordination and emergent sensemaking.
What's Important? • 42 implied HN points • 21 Mar 26
  1. A growing Network of Networks connects aligned communities. It lets people plug into cooperative, positive-sum groups that help them find purpose, integrate experiences, and share resources.
  2. A Leading Edge network is about 150 high-agency members who balance tensions like individual vs collective, material vs spiritual, intellectual vs experiential, ordered vs chaotic, and digital vs physical. That mix of structure, practices, and peer support helps members deepen their work and lives.
  3. Training and funding steward schools to teach network leaders is a high-leverage way to scale this movement. A few trained stewards can quickly create many connected 150-person communities and generate large systemic change.
A Bit Gamey • 13 implied HN points • 22 Mar 26
  1. Treat every project as a hypothesis by writing down the bet — who the customer is, what problem you solve, your approach, and how you’re different. Making the claim explicit lets you test it instead of polishing forever.
  2. Start with a precisely named customer and the single problem that matters to them, not vague broad audiences. If you can be your own customer, it makes clarity and testing much easier.
  3. Run small, fast experiments (landing pages, free offers, communities) to get early signals like clicks and sign‑ups instead of building long before you know it works. Build meaningful product differentiation from the start, not just marketing around a generic offering.
SeattleDataGuy’s Newsletter • 1165 implied HN points • 23 Jan 26
  1. Practice analytical intuition by doing rough estimates, breaking problems into proxy values, understanding baselines and natural variance, and always running manual spot checks instead of blindly trusting tooling.
  2. When a metric moves unexpectedly, first confirm the data with multiple sources, then generate and test product, market, user, and external hypotheses to pinpoint the root cause and escalate with concrete analysis.
  3. Choose KPIs that are relevant, measurable, specific, prioritized, and balanced — pick the right type (North Star, top-level, secondary, or OMTM), avoid vanity metrics, and use simple, trusted proxy metrics tailored to your product.
Erik Explores • 614 implied HN points • 10 Feb 26
  1. Gripen is built for coordinated, squad-level fighting—its peer-to-peer data sharing and electronic warfare let multiple jets act as a single, flexible unit, while the F-35 focuses on individual stealth and sensor fusion.
  2. Because it’s simpler and cheaper to maintain and produce, Gripen can fly more often, train pilots faster, and stay operational when logistics or supply chains are strained.
  3. Its open, modular electronics, AI-friendly design, and support from long-range sensors like GlobalEye make Gripen easier to upgrade and better suited to adaptive, resource-constrained wars where resilience matters.
Not Boring by Packy McCormick • 297 implied HN points • 18 Feb 26
  1. New technologies make key inputs abundant, which magnifies the value of scarce, industry-specific assets so a few winners capture a growing share of economic value.
  2. To win you must identify the industry’s bottleneck (the Schwerpunkt), break it, seize the High Ground by owning the scarce defensible asset, and then integrate outward to lock in those gains.
  3. That often means building full‑stack businesses or using hardware and services instead of defaulting to SaaS, and investors must judge bespoke strategy and execution rather than rely on standard SaaS metrics.
Tanay’s Newsletter • 113 implied HN points • 03 Mar 26
  1. AI erodes labor-based moats like switching costs, application-layer scale, and generic process advantages, making it cheaper and faster to build features, migrate systems, and iterate.
  2. Defensibility shifts to hard-to-reproduce assets: proprietary first-party data, real marketplace liquidity and reputation, regulatory or physical rails, and unique processes that rely on exclusive signals.
  3. Some powers strengthen or split — model and infrastructure scale plus institutional trust grow in importance, while marketing-driven consumer brand shortcuts weaken as agents can deeply evaluate options.
Freddie deBoer • 3186 implied HN points • 08 Dec 25
  1. Voters of color are not a monolith and should be treated as diverse individuals who make independent choices.
  2. Trump’s 2024 gains with parts of the nonwhite electorate — and the rapid erosion of that support afterward — show these voters can shift based on persuasive appeals and concrete policies.
  3. Democrats risk dangerous complacency and condescension if they assume an ā€œenduring Democratic majorityā€ and treat voters of color as guaranteed supporters.
Gad’s Newsletter • 41 implied HN points • 16 Mar 26
  1. Inflation alone doesn’t explain Dollar Tree’s gains — the $1.00→$1.25 price bump and COVID-driven demand were the real revenue engines, while a shift toward low-margin consumables has quietly eaten into gross margins.
  2. Scale helped procurement but hurt profits: SG&A rose with store count as revenue per store fell, and the $1.25 price point forces roughly 80 transactions per $100, creating a labor-heavy cost structure that undermines operating leverage.
  3. The company’s escape hatch is DT Plus! — higher price tiers can cut transaction intensity and improve margins, but the outcome depends on accelerating Plus! penetration, bending the SG&A ratio, and stabilizing revenue per store.
The Beautiful Mess • 476 implied HN points • 16 Feb 26
  1. Teams juggle work in three modes: strategic (intentionally keeping and pruning options), lazy (scattered, novelty-driven work without discipline), and survival (forced triage where dropping anything has immediate costs).
  2. Without clear pruning, learning, and prioritization, strategic juggling can drift into lazy juggling, and accumulated drift can suddenly collapse into hard-to-escape survival mode.
  3. Regularly diagnose where you are, choose constraints on purpose, create breathing room, and set clear criteria for focus so you can move back toward strategic, compounding work.
The Future Does Not Fit In The Containers Of The Past • 72 implied HN points • 01 Mar 26
  1. Break down silos and work as teams across functions; collaborate, orchestrate efforts, and hold everyone accountable so no one acts above the group.
  2. Keep a start-up mindset and stay forever young by continually reinventing, launching new ideas, and treating failure as a learning step.
  3. Trust quickly and be optimistic; trust is binary and enables speed and high performance, and bold optimism pushes you to aim high rather than settle for small dreams.
Huddle Up • 166 implied HN points • 25 Feb 26
  1. The New York Times built a bundle of products — like games, cooking, and Wirecutter — that now drive most user engagement and make news one piece of a larger offering.
  2. Moving readers onto bundled subscriptions instead of news-only plans dramatically improved economics, producing far more subscribers, revenue, free cash flow, and a higher market valuation.
  3. That bundling playbook is being copied across media because diversifying subscription products gives publishers a clearer path to sustainable growth and survival.
Entry Level Investing • 117 implied HN points • 04 Mar 26
  1. Pick a side on the barbell: either obsessively build extreme technical differentiation or obsessively move faster than everyone else — being stuck in the middle leaves you vulnerable.
  2. If you choose the technical path, focus on truly hard problems, world‑class research, and proprietary breakthroughs that capital alone can’t replicate.
  3. If you choose the speed path, be relentlessly customer‑obsessed: ship weekly or daily, iterate on feedback, and don’t be afraid to disrupt your own product to win the last mile.
The Beautiful Mess • 621 implied HN points • 03 Feb 26
  1. Leaders should know each team’s purpose, who they serve, recent releases, key metrics, and rough priorities, but you don’t need ledger‑level detail — broad estimates are enough.
  2. Standardize cross‑organizational communication like release calendars, deployment records, and analytics so partners can see what actually shipped, but teams don’t all have to use the same tracking tool unless a lot of work spans groups.
  3. Low trust drives micromanagement and rigid tracking that kills productivity, so let teams pick their tools and surface context with goals, value models, charters, and problem‑based roadmaps, using temporary common systems only while untangling heavy cross‑team work.
The Breaking Point • 159 implied HN points • 08 Oct 24
  1. When making decisions, it's important to separate methods from outcomes. If you mix them up, it can lead to confusion and endless debates.
  2. You can plan in two ways: starting with methods to estimate outcomes or starting with outcomes to figure out the methods needed. Both ways can work depending on the situation.
  3. To empower your team, give them clear outcomes and let them choose their own methods. This way, they feel involved and motivated to succeed.
High Growth Engineer • 1164 implied HN points • 04 Jan 26
  1. Executives promote engineers who deliver clear business impact, not just technically elegant code.
  2. Finish work end-to-end: ship customer-ready products, build tools that speed the team, take on the operational "dirty work," and anticipate problems before they happen.
  3. Grow and lead others by mentoring, setting standards, and training teams — that influence gets noticed and accelerates promotion.