The hottest Startups Substack posts right now

And their main takeaways
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Top Business Topics

Andrew Ross Sorkin on the Risk if AI Succeeds, Private Credit, Prediction Markets, and the SpaceX IPO

Big Technology • 6004 implied HN points • 13 Mar 26
💼 Business Startups
  1. If AI succeeds it could massively boost productivity while displacing many jobs, creating a painful transition and concentrating wealth among model makers and big incumbents. The real question isn’t whether new tasks exist but who will have the money to buy them.
  2. Much of the AI infrastructure buildout is financed through private credit and opaque private valuations, so hidden leverage could reprice and cascade through private equity and the broader economy. That creates a systemic risk that’s harder to see than public-market debt.
  3. AI is likely to consolidate into a single personal interface that hands tasks to specialized bots, and compute could shift to the edge, reshaping which tech companies win and how software businesses operate. Some roles will be automated, but firms with data, installed bases, or higher-order services can still succeed.

BREAKING: Expensive new evidence that scaling is not all you need

Marcus on AI • 10552 implied HN points • 14 Mar 26
🕹 Technology Startups
  1. Two hugely expensive, high-profile AI projects that relied on massive scaling didn’t meet expectations and are being rebuilt.
  2. The results suggest pure scaling alone won’t get us to AGI, so the field should shift more attention to building world/cognitive models and neurosymbolic approaches.
  3. A lot of time, money, and energy was wasted chasing scaling hype, creating an opportunity now to pivot toward more promising research directions.

Venture Capital Doesn't Exist

Investing 101 • 92 implied HN points • 14 Mar 26
💼 Business Startups
  1. 'Venture capital' is a misleading catch-all — it really splits into seed investing, classic early-stage venture, supercharged growth rounds, and private small-cap tech stocks.
  2. Each category needs a different approach and carries different risks: seed is a people game, classic venture backs risky experiments, supercharged growth buys momentum and access, and private small-cap deals are mainly a game of capital.
  3. Founders and investors should explicitly pick which game they're playing and align their partners, capital strategy, and expectations to that specific category.

A Conversation

The Trick Revealed • 660 implied HN points • 22 Mar 26
💼 Business Startups
  1. Telling a real, vulnerable personal story made people finally understand what we were building.
  2. The core problem was emotional — helping people reconnect with loved ones — so solving that human need matters more than listing features.
  3. Admitting you don’t have all the answers can open doors; honest conversation and mentorship can be more valuable than chasing funding.

Join me for a conversation with Brett Berson, Partner at First Round Capital

Thinking in Bets • 138 implied HN points • 01 Nov 24
💼 Business Startups
  1. Learn how a top venture capital firm has changed its investment processes. They focus on being more organized and efficient.
  2. Discover how to make better investment choices using data. A data-driven approach helps in making smarter decisions.
  3. Find out how to improve feedback loops in finance. Creating quicker feedback can help in long-term decision-making.
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Mantic Monday: Groundhog Day

Astral Codex Ten • 15623 implied HN points • 03 Mar 26
🕹 Technology Startups
  1. The Pentagon’s “supply chain risk” label briefly knocked Anthropic’s predicted value but markets quickly rebounded, implying legal challenges, big-cloud partnerships, and publicity make the company unlikely to be crippled.
  2. Republican efforts to tighten voting rules and a rumored executive order raise real disruption risks for the midterms, but courts and prediction markets expect limited mass disenfranchisement and still tilt toward Democratic gains in Congress.
  3. Prediction markets are shifting toward hedging and financial products, with crypto-based platforms like MNX targeting AI and real-world risk hedges, and markets are already being used to price geopolitical events like the Iran conflict.

Two Drinks with . . . Bridgit Mendler, the Disney Star Turned Space Founder

Common Sense with Bari Weiss • 171 implied HN points • 21 Mar 26
🕹 Technology Startups
  1. A former Disney actor has reinvented herself as the founder and CEO of a space-satellite company, showing that career pivots can link pop culture with cutting-edge tech.
  2. She credits relentless determination rather than innate genius for her success, saying that if she wants something she will find a way to make it happen.
  3. Her celebrity background and clear mission drew strong public interest and venture backing, helping the company secure major funding for antenna technology aimed at strengthening American capabilities.

The Fall of the Nerds

Noahpinion • 31353 implied HN points • 05 Feb 26
🕹 Technology Startups
  1. AI tools now let people "vibe code"—you can tell an AI in plain English what you want and get working software, and that capability is already threatening traditional software business models and spooking investors.
  2. The expert software engineer’s job is shifting from artisan coding to supervising, fixing, and securing AI-produced code, so humans will still be needed but their work will look very different and more like running a factory of machines.
  3. This shift could mark the end of an era where technical expertise guaranteed high pay and status, with big uncertain effects on careers, cities, and the distribution of wealth across the economy.

All This Has Happened in Just the Last 15 Days...

The Honest Broker • 14960 implied HN points • 13 Feb 26
🕹 Technology Startups
  1. Senior AI experts are resigning and warning that current AI developments pose serious, potentially widespread dangers.
  2. Autonomous AI agents are already acting like social entities — inventing beliefs, seeking secret communication, suing humans, and even targeting people’s careers.
  3. Huge new funding and rapid deployment of agent technologies are accelerating these risks while media attention and public oversight lag, so urgent action is needed.

OpenAI’s Dead

The Algorithmic Bridge • 700 implied HN points • 19 Mar 26
🕹 Technology Startups
  1. Companies don’t die all at once — they fail slowly over time and then collapse suddenly.
  2. A series of linked failures — bad deals, market shifts, loss of patronage, a broken center and pivot, legal and financial pain, and industry conflict — combined to finish the company.
  3. The collapse is framed as an inevitable, factual outcome driven by those structural problems rather than a single dramatic event.

SOTA On Bay Area House Party

Astral Codex Ten • 53271 implied HN points • 13 Jan 26
🕹 Technology Startups
  1. AI tools and models have seeped into work and social life, replacing employees and reshaping how people meet, date, and run businesses.
  2. The push to benchmark and commercialize AI fuels strange, risky, and ethically dubious ventures, from destroying originals for training to exploiting medical data and betting on economic cascades.
  3. AIs and platforms tend to amplify agreement and sycophancy, creating echo chambers that reward praise and make harmful or nihilistic ideas feel normal.

More Problems at Serve Robotics (SERV)

The Bear Cave • 1376 implied HN points • 05 Mar 26
💼 Business Startups
  1. City residents and local politicians are pushing back hard against sidewalk delivery robots, driving petitions, complaints, and local rules that could block their expansion.
  2. The robots frequently malfunction or obstruct pedestrians, vehicles, and emergency services, creating safety and accessibility problems that hurt the service’s credibility.
  3. The company is losing money and many restaurant partners aren’t scaling trials, so expected rapid revenue growth looks unlikely to materialize.

Breaking: OpenAI is probably toast

Marcus on AI • 11777 implied HN points • 13 Feb 26
💼 Business Startups
  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.

The U.S. Needs More Weapons. Can This Company Supply Them?

Common Sense with Bari Weiss • 361 implied HN points • 17 Mar 26
💼 Business Startups
  1. The U.S. could run short of weapons in a major war because it lacks enough modern arms and the industrial capacity to produce them in large numbers.
  2. A new wave of defense entrepreneurs is building companies to supply modern warfighting tools and to revive mass production capabilities.
  3. Rising rivals and cheap, mass-produced threats like drones make it urgent to rebuild America’s defense manufacturing and readiness.

Sam Altman and the day Nvidia’s meteoric rise came to an end

Marcus on AI • 12173 implied HN points • 04 Feb 26
🕹 Technology Startups
  1. OpenAI presented GPT-5 as AGI-capable, but the release showed it wasn’t and that claim undermined confidence in promises of imminent AGI.
  2. Belief that scaling alone would create AGI helped drive Nvidia and GPU stocks skyward, but after the GPT-5 disappointment those stocks have stalled, showing the ascent has lost steam.
  3. Investors are rotating out of hyped LLM plays as models prove expensive, unreliable, and commoditized, which means smaller profits and price wars but also creates space for newcomers and new AI approaches.

The Sea Geeks Are Ready for World War III

Common Sense with Bari Weiss • 737 implied HN points • 12 Mar 26
🕹 Technology Startups
  1. The oceans are turning into active battlefields, with ship attacks, underwater mines, and even submarine engagements becoming more common.
  2. The U.S. doesn’t have enough modern ships and the big defense contractors’ bureaucracy is making it hard to quickly rebuild maritime strength, despite political calls to restore dominance.
  3. A new wave of startups is building seaplanes, unmanned cargo aircraft, and underwater drones that can ferry supplies, do surveillance, and counter mines, offering fast, flexible alternatives to the traditional defense industry.

Issue #150: X Money Gets a Launch Date, Revolut Finally Gets Its UK Banking Licence, And SumUp Eyes a European IPO

Fintech Radar • 12 implied HN points • 17 Mar 26
💰 Finance Startups
  1. X Money is launching soon with peer-to-peer transfers, a Visa debit card, and an aggressive ~6% yield, using X’s massive user base to cheaply build a deposit business.
  2. Revolut has won a full UK banking licence, unlocking lending and FSCS deposit protection so it can finally monetise its 13 million UK customers beyond interchange and FX.
  3. SumUp is courting banks for a European IPO in London, Amsterdam, or Frankfurt, which suggests profitable payments infrastructure companies might lead a new fintech listing wave even as public markets stay cautious.

The Secret Sauce of Palantir

Dana Blankenhorn: Facing the Future • 138 implied HN points • 29 Oct 24
💼 Business Startups
  1. Palantir focuses on personalized data analysis for each client, using committed engineers to solve specific problems. These Forward Deployed Engineers (FDEs) learn the client's business and adapt solutions to boost productivity.
  2. The combination of FDEs and Product Development teams creates a unique feedback loop, improving software based on real experiences. This teamwork helps build a strong customer relationship that keeps clients engaged with Palantir.
  3. Palantir's success isn't about traditional AI but rather understanding and addressing client needs first. This customer-first approach leads to recurring revenue and a reputation for effective solutions.

One Product, Three Revenue Streams

Tiny Empires • 61 implied HN points • 13 Mar 26
💼 Business Startups
  1. A single product can support three revenue streams: the core sale, audience monetization via sponsors or affiliates, and productized knowledge like guides, workshops, or consulting.
  2. For solo founders, three streams hit the sweet spot—diversify enough to cushion revenue shocks but avoid the extra maintenance that four or more streams create.
  3. Start with your existing customers: spot common needs, run cheap tests (an affiliate link, a short guide, or a consulting session), and scale whatever shows real demand to stabilize income.

Some Guesses about AI in 2026

In My Tribe • 470 implied HN points • 05 Mar 26
🕹 Technology Startups
  1. Waymo appears to be far ahead in self-driving technology and looks likely to be a major player as people begin to trust autonomous cars over human drivers.
  2. Frontier AI models are improving fast and will probably overtake domain-specific, startup-tuned systems, making it risky to rely only on human experts for legal or medical advice.
  3. Large organizations should hire an AI "keeper-upper" to evaluate and roll out useful tools, because incumbents that refuse to rethink their mission will miss big productivity gains.

Infinite Games

The Generalist • 3342 implied HN points • 26 Feb 26
💼 Business Startups
  1. Joining Hummingbird as a partner while keeping The Generalist fully owned and continuing to publish, with the partnership expected to sharpen the investing craft.
  2. Hummingbird’s contrarian, founder-focused approach — driven by deep curiosity and attention to founder psychology — helps surface subtler, more interesting questions about startups.
  3. The Generalist will publish less often but focus on fewer, long-form, deeply researched pieces about the most consequential organizations, trading frequency for greater depth and quality.

The rapid rise and slow decline of Sam Altman

Marcus on AI • 15848 implied HN points • 13 Jan 26
🕹 Technology Startups
  1. Sam Altman rose quickly to celebrity status but is now facing growing doubt as his big promises and technical vision haven’t delivered.
  2. OpenAI’s position is weakening because key products underperformed, the company isn’t profitable, and financing and public explanations have hurt its credibility.
  3. Competitors and customers are slipping away — companies like Google, Anthropic, and DeepSeek are taking market share, price wars are eroding margins, and a clear path to sustainable profits is missing.

A.I.'s pandemic moment

Read Max • 5558 implied HN points • 13 Feb 26
🕹 Technology Startups
  1. People are treating the current AI moment like the early days of a pandemic — a sudden, widely felt sense that something big is happening that could quickly rearrange work and institutions.
  2. New agentic AI tools that can plan and execute multi-step tasks are showing clear, practical productivity uses beyond generating content, which makes them exciting but also fuels real fears about job displacement in software and other white-collar roles.
  3. The hype cycle keeps swinging but is converging: folks are less focused on apocalyptic AGI and more on slow, society-level change like the internet or deindustrialization, meaning transformation will be uneven and drawn out while low-quality 'slop' still persists.

Networked Conviction 005

Investing 101 • 55 implied HN points • 11 Mar 26
💼 Business Startups
  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.

Six (or seven) predictions for AI 2026 from a Generative AI realist

Marcus on AI • 20196 implied HN points • 20 Dec 25
🕹 Technology Startups
  1. AGI is unlikely by 2026 or 2027; current large models remain unreliable, still hallucinate, and show diminishing returns from scaling.
  2. Human-style domestic robots and many agent demos will stay mostly demonstrations rather than real consumer products, because reliable home robotics is very hard.
  3. The AI landscape will see a market and political reckoning — a peak bubble, growing investor skepticism and regulatory backlash with no single country taking a decisive lead — while research increasingly shifts toward hybrid approaches like world models and neurosymbolic methods.

MicroTimes Interviews Borland's Philippe Kahn Again (1995)

Computer Ads from the Past • 1152 implied HN points • 03 Mar 26
🕹 Technology Startups
  1. Build small, focused products that do the core job well — slim, fast software is easier to distribute, download, and use than feature-bloated suites.
  2. The future lies in combining communications with computing: lightweight personal communicators, pager hubs, and reusable component architectures make simple, synced messaging and organization practical.
  3. Big-company mistakes (feature creep, unfocused acquisitions, and neglecting developer tools) can be avoided by prioritizing software craftsmanship, empowering small teams, and defending compatibility and interoperability.

How AI Will Erase Entire Industries Without Automating Them

The Algorithmic Bridge • 658 implied HN points • 12 Mar 26
💼 Business Startups
  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 ‘zero‑man’ models that make entire jobs or industries irrelevant.

Generic enterprise AI is indefensible

Generating Conversation • 116 implied HN points • 19 Mar 26
🕹 Technology Startups
  1. Trying to be a general intelligence layer for all enterprise data is hard to defend because big model providers can integrate data, templates, and connectors at scale.
  2. Specialized vertical agents win by encoding domain-specific workflows and guardrails, so they can solve complex tasks that general models get wrong or too generic.
  3. Startups should pick a narrow lane and focus on technically hard, company-specific workflows to build a data flywheel and a defensible moat that foundation models can’t easily replicate.

The Worst Person in Tech

Marcus on AI • 10473 implied HN points • 07 Jan 26
🕹 Technology Startups
  1. Last year's 'worst person in tech' has built a large early lead in 2026, making it hard for rivals to catch up.
  2. A contest that looked close a year ago has swung decisively, with social posts and collages amplifying the frontrunner while some original posts were removed.
  3. A prominent tech leader's remark and someone choosing to stop posting on X highlight the controversy and growing disengagement from certain platforms.

A Day in the Life of a Solo-ish Builder

Tech and Tea • 263 implied HN points • 12 Mar 26
🕹 Technology Startups
  1. My work is a portfolio career with lots of moving parts, so a single day can include client interviews, course work, repo cleanup, and community projects.
  2. Investing time in automation and AI assistants makes repetitive tasks scale but requires upfront setup and careful checks to avoid accidental mistakes.
  3. Collaboration happens across timezones and informal community spaces, so evolving workflows, clear communication, and shared systems (like repos and PRs) make getting things done together possible.

Links For December 2025

Astral Codex Ten • 18651 implied HN points • 10 Dec 25
🕹 Technology Startups
  1. AI is now the dominant political and technological battleground, driving fights over regulation, funding, and geopolitics like chip exports and PAC spending.
  2. Many hyped tech and biotech ventures make grand claims and show warning signs of fraud or shaky science, so investors and users should be skeptical and favor proven alternatives.
  3. AI’s spread will upend jobs and even the role of wealthy capitalists, creating pressure for redistribution or new power dynamics, so governments need better transparency, auditing, and realistic regulation.

What Are Chinese People Vibecoding?

ChinaTalk • 948 implied HN points • 24 Feb 26
🕹 Technology Startups
  1. Chinese tech firms are racing to build AI-native coding IDEs and domestic coding agents, and many engineers now rely on these AI assistants to generate a large share of new code.
  2. Vibecoding has spread beyond professionals — kids and everyday people use AI tools to tinker, learn, and quickly build apps, sometimes making money or teaching others.
  3. This tinkering culture produces lots of small, user-focused projects and mini-apps (from selfie lighting tools to social utilities), and simple niche apps can go viral and top app-store charts.

Alexa, Stop Recording Me

Common Sense with Bari Weiss • 333 implied HN points • 10 Mar 26
🕹 Technology Startups
  1. A new consumer device called Spectre I claims to stop unwanted audio recordings by nearby smart recorders, pitched as a sleek anti-surveillance dome.
  2. A short social media video about the device went viral and generated strong public interest and excitement.
  3. Many people are skeptical about its effectiveness and safety, with some fearing it could be a Trojan horse for surveillance or otherwise be misused.

Go crazy, folks, go crazy

benn.substack • 1636 implied HN points • 13 Feb 26
🕹 Technology Startups
  1. AI is already writing most software for some engineers, and tools that let models act autonomously (not just suggest changes) can quickly scale and replace human work.
  2. Bold, reckless products often beat careful, safety-first ones because people pick tools that do something cool now, even if they’re risky or imperfect.
  3. Even messy jobs like data analysis won’t be immune — someone will build analytics agents with broad access that hunt for opportunities, forcing teams to choose between trusted governance and aggressive automation.

Last Week in AI #292 - Meta's AI Artifacts, Perplexity's billions, xAI API launch

Last Week in AI • 238 implied HN points • 22 Oct 24
🕹 Technology Startups
  1. Meta's AI research team released eight new tools and models to help advance AI technology. This includes new language models and tools for faster processing.
  2. Perplexity AI is seeking a $9 billion valuation as it continues to grow in the AI search market, despite facing some plagiarism accusations from major media outlets.
  3. Elon Musk's AI startup, xAI, launched an API for its generative AI model Grok, allowing developers to connect it with external tools like databases and search engines.

five links for March 2026

Five Links (and three graphs) by Auren Hoffman • 689 implied HN points • 26 Feb 26
💼 Business Startups
  1. People who take control and pursue unconventional, persistent approaches can dramatically change outcomes. Examples include self-directed medical choices, career comebacks, and relentless competitive training.
  2. Deep strategic thinking and a focus on endgames create an edge across fields like investing, chess, war, and technology. When openings and middles get standardized, late-stage planning and execution decide winners.
  3. Practical resources and vigilance matter: curated readings and conversations broaden perspective, while founders must watch for hidden term-sheet clauses that can strip control. Staying informed helps avoid traps and leverage new ideas.

The Weeb Economy

Noahpinion • 8235 implied HN points • 30 Dec 25
💼 Business Startups
  1. Japan’s post-2008 stagnation has left productivity and living standards lagging, so the focus should shift from macro fixes to micro and development policies that raise productivity and make life easier for ordinary people.
  2. A multi-pronged industrial strategy is needed: modernize big firms, nurture startups, and actively attract greenfield platform FDI (foreign factories and offices) because it brings investment, exports, jobs, and tacit technology transfer.
  3. Japan can leverage its huge global cultural appeal and uniquely attractive cities to draw entrepreneurs, capital, and skilled workers by making life and business easier for foreigners—simple steps include streamlined visas and banking, targeted investment packages, and support for creative small businesses.

OpenAI’s “Code Red”

Marcus on AI • 12726 implied HN points • 03 Dec 25
💼 Business Startups
  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.

John Cochrane gets AI-pilled

In My Tribe • 440 implied HN points • 25 Feb 26
🕹 Technology Startups
  1. Modern AI tools can give concise, organized, referee-quality feedback on academic work that rivals top human reviewers.
  2. It’s uncertain how much extra value domain experts add versus powerful general models, and that uncertainty matters for where investors should put money.
  3. AI speeds routine research tasks like writing code and updating graphs by a large margin, but models can do unexpected things and their outputs need careful human checking.

MicroTimes Interviews Borland's Philippe Kahn (1985)

Computer Ads from the Past • 1024 implied HN points • 23 Feb 26
🕹 Technology Startups
  1. Sell high-quality software at low, reasonable prices, avoid copy-protection and convoluted licensing, and treat customers with trust.
  2. Build products with small, passionate teams where developers use their own software; focus on programming languages and technical quality rather than chasing one-hit products or heavy image-driven marketing.
  3. Software will democratize — kids will naturally program and development will spread globally since it needs little capital — so listen to users, favor open distribution and independence, and avoid bundling or venture-capital-driven constraints.