The hottest Startups Substack posts right now

And their main takeaways
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Top Business Topics

Why Industry Leaders Are Betting on Mutually Exclusive Futures

The Algorithmic Bridge • 318 implied HN points • 15 Dec 25
🕹 Technology Startups
  1. Two leading AI figures are pursuing opposite goals: one is focused on building and containing a possible future superintelligence, while the other is building practical tutor-like agents for today’s use cases.
  2. Their stark disagreement, despite similar training and prestige, shows that even top experts don’t agree on AI’s ultimate path or timeline.
  3. That deep uncertainty extends across industry, academia, and investors, producing fragmented, independent bets instead of a coordinated plan for the future.

Problems at Pattern Group (PTRN)

The Bear Cave • 303 implied HN points • 04 Dec 25
💼 Business Startups
  1. Pattern Group claims to use technology and data to help brands sell better on e-commerce platforms, but many say it's just a middleman selling products on Amazon.
  2. The company's business model, which involves buying from brands at wholesale prices and reselling at retail prices, has slim profit margins and isn't easy to grow.
  3. During an interview, the CEO struggled to explain how the business works, leading some to question if it's worth investing in.

IPO Watch: Ethos and Bitgo edition

Alex's Personal Blog • 131 implied HN points • 21 Jan 26
💼 Business Startups
  1. AI is reshaping markets fast: consumer and enterprise AI products are driving big revenue and valuations, while demand for AI coding tools is soaring and companies are promising to limit their energy and water impact.
  2. Geopolitical and demographic risks are growing, with fraying alliances, market jitters over treasuries, and falling birth rates that together threaten long-term economic stability.
  3. The IPO and venture exit picture is tough: Ethos is growing but listing below prior private valuations, BitGo shows huge topline crypto flows but thin core profits, and many software unicorns face low exit multiples that make strong returns harder.

4 Truths About OpenAI’s Wild Financial Position

Big Technology • 5504 implied HN points • 18 Oct 24
💼 Business Startups
  1. OpenAI plans to change how it looks at training costs, suggesting these might not be fixed over time. This could impact their profits, as training expenses are significant.
  2. OpenAI believes that ChatGPT will generate more revenue than its API, showing confidence in its widespread use. They expect more people will want to interact with AI in the future, which could be risky if the growth doesn’t happen as hoped.
  3. OpenAI is already making big payments to Microsoft, which is one reason they expect to lose a lot of money this year. If their losses continue at this rate, they will need to raise more money soon.

Silicon Valley's Slaughterhouse

Where's Your Ed At • 15430 implied HN points • 08 Sep 23
🕹 Technology Startups
  1. Elon Musk is involved in a legal battle over accusations of anti-semitism and his actions have had significant impacts on advertising revenue and Twitter's valuation.
  2. Silicon Valley culture has devolved into a profit-driven, empty innovation environment fueled by venture capital, lacking real societal impact.
  3. The tech industry, led by venture capital, has created a culture of labor exploitation, hollow promises, and superficial startup culture, with the focus on profitability rather than meaningful innovation.
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How to get to Product Market Fit: what it is, step by step guide and success cases like Notion, Canva and Stripe

The VC Corner • 659 implied HN points • 04 May 24
💼 Business Startups
  1. Product Market Fit (PMF) means having a product that people really want or need. It's not just about making the product; you also have to learn how to sell it well.
  2. To achieve PMF, start by identifying a specific problem people face and create a strong solution. It’s important that the problem is significant enough for people to want to pay to solve it.
  3. Successful startups often follow a process to reach PMF, which includes finding a niche, validating pricing, and continuously improving the product based on customer feedback.

How to build the perfect pitch deck: a step by step guide with examples and an analysis of my Airbnb's deck

The VC Corner • 419 implied HN points • 08 Jun 24
💼 Business Startups
  1. A pitch deck is a short presentation that startup founders use to attract investors. It's essential to communicate your business idea clearly and make it appealing.
  2. Investors often have limited time to review pitch decks, so it's important to make your slides simple and direct. Help them easily understand your business and its value.
  3. Including a strong story in your pitch deck is crucial. Outline your business's problem, solution, and unique value in a way that resonates with investors.

He Shut Down Time’s Moscow Bureau. Then He Built His Own Magazine

Simon Owens's Media Newsletter • 24 implied HN points • 18 Feb 26
💼 Business Startups
  1. The collapse of legacy newsrooms pushed journalists to build new, independent outlets instead of following old corporate paths.
  2. Starting small and using niche entry points like food or quirky platforms can grow into a powerful creative brand, but heavy reliance on brand partnerships or star contributors can leave a media venture vulnerable.
  3. Moving to reader-supported, membership-driven models and combining digital work with an annual print edition can provide a more durable financial foundation after major setbacks.

VC's Framework for Evaluating an AI Startup's Tech Stack. | VC Jobs

Venture Curator • 419 implied HN points • 06 Jun 24
🕹 Technology Startups
  1. The value proposition of AI companies now lies not just within models but predominantly in underpinning datasets, emphasizing the importance of data quality.
  2. When evaluating AI startups, VCs use frameworks to assess data quality, considering relevance, accuracy, coverage, and bias in the datasets used to train the AI models.
  3. To avoid investing in ineffectual AI startups, VCs focus on evaluating the processes behind data generation by asking questions about data automation, storage, access, processing, governance, and management.

How to Break into VC🎓, Europe VC Dealmaking Funnel🔍, The Billionaire Battle For AI's Future⚔️

The VC Corner • 359 implied HN points • 16 Jun 24
💼 Business Startups
  1. To get into venture capital, you need to build connections and understand the industry well. Networking and learning from experiences are crucial steps.
  2. The European venture capital market has a specific deal-making process that can be different from other regions. Knowing this funnel can help you navigate opportunities better.
  3. There's a growing competition among billionaires for AI technology. Understanding this battle can give insights into where future investments might be directed.

The Sequence Radar #795: The New Inference Kids

TheSequence • 112 implied HN points • 25 Jan 26
🕹 Technology Startups
  1. Serving models (inference) is now the main battleground, drawing huge funding as startups race to make model serving boring, reliable, and infinitely scalable.
  2. New kernel-level tricks are cutting recomputation and memory waste: RadixAttention reuses KV cache blocks like an LRU to avoid recomputing prefixes, and PagedAttention pages KV memory so GPUs can pack many more requests without VRAM fragmentation.
  3. Latency and per-turn cost now define product quality, causing a split in the stack between orchestration/hardware layers that manage scale and kernel teams that squeeze every FLOP to make models fast and cheap.

Levels of greatness

next big thing • 37 implied HN points • 12 Feb 26
🕹 Technology Startups
  1. Greatness exists in distinct layers, and the gap between each level can be enormous — someone who’s great at one level can be thoroughly outclassed by the next.
  2. Many systems follow a power-law pattern where a tiny number of people, companies, or places capture most of the attention, wealth, or returns.
  3. AI, especially models that can help build and improve themselves, is accelerating that concentration, so a small set of firms is likely to pull much farther ahead.

How to Build an AI Agent Company in 2026: Lessons from Glean’s $7.2B Playbook

Market Curve • 100 implied HN points • 26 Jan 26
🕹 Technology Startups
  1. Make AI agents easy and reliable by hiding RAG and knowledge-graph complexity, connecting across apps, and grounding answers in company data so the system retrieves facts and says “I don’t know” instead of hallucinating.
  2. Get early customers by solving a real internal pain with long free trials and usage-first metrics, use high-touch onboarding and customer advocates to expand pilots into large enterprise deals.
  3. Start in a language-heavy vertical, build deep integrations and reusable agent templates (amplified by influencers), then scale with sales-led motions, bundling features while making security, permissions, and governance core.

AI-driven layoffs, up close and personal

Alex's Personal Blog • 262 implied HN points • 15 Dec 25
🕹 Technology Startups
  1. Roomba's maker has filed for bankruptcy and looks set to be sold, showing how failed deals and market-power fights can wipe out small hardware companies.
  2. CEOs are planning bigger AI budgets while workers, especially in writing and small agencies, are already losing jobs as cheaper, 'good enough' automation replaces paid labor.
  3. A nearby mass shooting made gun violence feel immediate and personal, highlighting how these events disrupt communities and how social media often spreads harmful rumors.

Programmers should hedge against AI

Amaca • 47 implied HN points • 11 Feb 26
💼 Business Startups
  1. The job market for programmers has tightened a lot since 2021; interviews are harder and landing roles feels much more difficult.
  2. AI tooling levels the playing field so anyone can build software, which lowers the economic value of individual software products and startups and risks making many programming jobs obsolete.
  3. To protect themselves, programmers should aim for stable, unionized roles at large companies with legacy revenue and/or financially hedge by investing in semiconductors and datacenter/AI infrastructure (e.g., call options or relevant stocks).

Demystifying Venture Capital: Realities and Challenges of the sector

The VC Corner • 299 implied HN points • 22 Jun 24
💼 Business Startups
  1. The venture capital market is very crowded, making it hard to find unique investment opportunities. To succeed, it's crucial to stand out from the competition.
  2. Many venture capitalists have never built a company themselves, which may limit their ability to help startups effectively. Practical experience is important in providing useful guidance.
  3. Successful founders are good at raising money quickly so they can spend more time on their products. They focus on building strong connections with the right investors to make fundraising easier.

Clouded Judgement 3.6.26 - Get in the Token Path

Clouded Judgement • 16 implied HN points • 06 Mar 26
💼 Business Startups
  1. The biggest cloud-era infrastructure winners aligned their revenue with the platform's core consumption unit — they "owned the meter" so more usage automatically meant more revenue.
  2. In AI, tokens are becoming that core unit, so companies directly in the token path (models, inference platforms, and coding agents) can structurally scale as token consumption rises.
  3. Being in the token path is necessary but not sufficient — companies must build real differentiation and moats (better developer UX, vertical models, security/compliance, or proprietary data) and move quickly before token economics commoditize.

The startups are thriving

Alex's Personal Blog • 262 implied HN points • 12 Dec 25
💼 Business Startups
  1. The federal government moved to preempt state AI laws by creating a task force and directing agencies to build a uniform national AI policy that can challenge conflicting state rules.
  2. A coalition of allied countries is coordinating to secure AI supply chains—investing in chips, rare earths, and infrastructure to reduce reliance on strategic rivals.
  3. AI-first startups are growing far faster than traditional benchmarks, posting huge ARR gains and forcing investors to expect growth well beyond the old T2D3 model.

Not all media outlets are worried about declining Google traffic

Simon Owens's Media Newsletter • 324 implied HN points • 19 Nov 25
💼 Business Startups
  1. Many new media startups are doing well without depending on Google for traffic. They focus more on building strong connections with their audience.
  2. The Economist is seen as a luxury brand like Ferrari because it maintains high standards and limits supply, making it more valuable to its subscribers.
  3. Vox is teaming up with Patreon to create exclusive content, showing that media companies are finding new ways to attract paying audiences.

Getting Even

Tigerfeathers! • 24 implied HN points • 27 Feb 26
💼 Business Startups
  1. India’s healthcare incentives are misaligned: fee‑for‑service and fragmented delivery reward more procedures while payers try to limit payouts, which drives opaque pricing, catastrophic out‑of‑pocket bills, and inefficient care.
  2. Vertically integrating care (telehealth → salaried primary care → in‑house diagnostics → lean secondary hospitals) aligns incentives, captures provider margins, lowers claims, and improves retention by making prevention and appropriate care financially sensible.
  3. Existing hospitals and insurers find this integration hard to copy because it cannibalises incumbent economics or requires new capabilities, so startups can build a durable advantage — but the model must guard against new risks like under‑treatment and needs long time horizons and smart regulation.

Stages of Board Deck Preparation📝, How to be helpful as a VC📚, Secondary Market VC Funds🔄

The VC Corner • 279 implied HN points • 23 Jun 24
💼 Business Startups
  1. Preparing a board deck requires several key stages to make sure everything is clear and organized.
  2. As a venture capitalist, being helpful includes providing valuable insights and support to the startups you invest in.
  3. Secondary market VC funds allow investors to buy and sell stakes in venture funds, providing more flexibility and liquidity.

State of Pre-Seed🌱, Gulf money is flooding into European startups🌏, Looking for AI use-cases🧐

The VC Corner • 579 implied HN points • 28 Apr 24
💼 Business Startups
  1. Gulf countries are investing a lot of money into startups in Europe right now. This means European startups have more funding opportunities to grow.
  2. There's a strong interest in finding use-cases for artificial intelligence. Companies are looking for new ways to apply AI technology effectively.
  3. The pre-seed funding stage is important for new businesses to get started. This is when they first seek money to develop their ideas and products.

Cursor's Unfair UX Advantage

Generating Conversation • 46 implied HN points • 12 Feb 26
🕹 Technology Startups
  1. Make tasks tiny: small, incremental units of work let users catch mistakes early, build trust, and produce dense feedback that powers a strong data advantage.
  2. A low‑stakes autocomplete/IDE UX makes it easy to accept or reject suggestions, so even imperfect prompts save time and generate lots of useful training signals.
  3. Design agents for fast iteration and cumulative correctness rather than one‑shot perfection — cheap inference and quick feedback loops let users get to the right answer over a few tries and move much faster.

Ambition, fun and not

benn.substack • 1252 implied HN points • 04 Jul 25
💼 Business Startups
  1. Starting a startup sounds great because you can choose your projects and team, but it comes with a lot of hard work and stress. Many founders regret getting into it despite the glamorous idea of freedom.
  2. Once startups grow into businesses, they lose some of their initial fun and freedom. The excitement of being a creator changes to dealing with corporate responsibilities and customer demands.
  3. Even if a startup has bold ideas, like Cluely's innovative concept, they often end up focusing on practical business solutions. This shift can make their original ambitious vision seem smaller than intended.

The next big thing in 2026 will be...

next big thing • 141 implied HN points • 01 Jan 26
🕹 Technology Startups
  1. Autonomous, end-to-end AI agents will move from being copilots to pilots, owning whole workflows and delivering outcomes rather than just answering prompts.
  2. Persistent memory, proactive behavior, and on-device inference will make AI feel like a personal companion and unlock a wave of new consumer products, generative media, and personalized experiences.
  3. AI will start showing up in the bottom line, driving real deployments, new pricing models, hardware launches, and a surge of IPOs and M&A, while human-heavy AI services get exposed if they can’t prove machine-driven margins.

33 predictions for 2026 in AI: consumer, enterprise, AI capex, and more

Enterprise AI Trends • 168 implied HN points • 27 Dec 25
🕹 Technology Startups
  1. AI progress will accelerate in 2026, causing fast, widespread change that can create big winners and losers.
  2. AI agents will become mainstream across consumer and enterprise use cases, with coding agents able to autonomously complete multi-hour tasks and driving strong enterprise adoption and FOMO.
  3. Intense competition, cost optimization, and open-source model advances will shape which platforms and startups win, making AI capex and strategic investment decisions essential.

Saying The Quiet Part Out Loud

Investing 101 • 64 implied HN points • 24 Jan 26
💼 Business Startups
  1. People in venture and business are playing different games — playing to win, playing for power, or playing to survive — and each game leads to different goals and behaviors.
  2. The real mistake is pretending everyone is playing the same game; not recognizing others' aims will make you compete on the wrong terms and cost you.
  3. Be deliberate about which game you choose and play it well; don’t let winners or power players drag you into their game if it doesn’t fit your goals.

Wafer Scale - Trilogy Systems: Part 2

The Chip Letter • 4149 implied HN points • 27 Oct 24
🕹 Technology Startups
  1. Trilogy Systems, founded by Gene Amdahl in 1979, aimed to revolutionize the mainframe market with a new technology called Wafer Scale Integration, which promised to be faster and cheaper than existing solutions. However, the company struggled with technical challenges and internal issues.
  2. As delays mounted and financial troubles grew, Trilogy abandoned its mainframe plans and, ultimately, its Wafer Scale technology. Distractions like personal tragedies and a lack of cohesive vision contributed to the company's downfall.
  3. After losing credibility and facing mounting losses, Trilogy merged with Elxsi, but that too did not lead to success. Amdahl felt a deep personal responsibility for the failure, which haunted him even after the company's collapse.

Letters to a Young Founder: Immad Akhund of Mercury

The Generalist • 1160 implied HN points • 17 Jul 25
💼 Business Startups
  1. Shipping products with clear intention is crucial for success. It helps in creating items that truly meet customer needs.
  2. Being open to innovative and unconventional ideas can lead to unique products. This can set your company apart in a crowded market.
  3. Growth as a leader involves constant learning and adapting. It's important to reflect on your experiences and make improvements over time.

Elon Musk’s xAI raises Monster $6B Series B for AI Supercomputer and Grok 3

The VC Corner • 379 implied HN points • 28 May 24
🕹 Technology Startups
  1. Elon Musk's company xAI just raised $6 billion to build an advanced AI supercomputer and improve their AI model, Grok 3. This new funding makes xAI a key player alongside OpenAI and Anthropic.
  2. The $6 billion Series B funding round is a big deal in the AI world, showing a lot of investor confidence. Musk plans to use this money to get the hardware needed for more powerful AI.
  3. xAI aims to compete with top AI companies by developing a massive number of semiconductors for training their models. This means more competition in the market and potentially exciting innovations in AI technology.

How to Raise Your First Fund💼, 2024 Midas List🏆, Analyzing Startup Financials 📊

The VC Corner • 319 implied HN points • 09 Jun 24
💼 Business Startups
  1. Raising your first fund can be a challenging but rewarding process. It's important to prepare thoroughly and understand your investors' needs.
  2. The 2024 Midas List highlights top performers in venture capital. This list can give insights into successful investors and trends in the industry.
  3. Analyzing startup financials is vital for making informed investment decisions. A solid grasp of finances helps in assessing a startup's potential for growth.

The Sequence AI of the Week #797: The New Companies that can Change the Inference Landscape

TheSequence • 84 implied HN points • 28 Jan 26
🕹 Technology Startups
  1. Two new commercial companies from the vLLM and SGLang teams—Inferact and RadixArk—raised huge funding and are positioning themselves as major players in the inference stack.
  2. The focus is shifting from building bigger models to improving inference unit economics, so the software that manages memory, scheduling, and kernels is now the main battleground.
  3. Serving models efficiently is bottlenecked by scarce VRAM and the KV cache tax, because asynchronous and unpredictable inference patterns drive up cost and complexity.

You should be playing with AI agents for marketing

Kyle Poyar’s Growth Unhinged • 1301 implied HN points • 02 Jul 25
💼 Business Startups
  1. Using AI agents for marketing can boost efficiency by handling various tasks that would normally require multiple team members. These agents are like having a group of helpers that can work around the clock.
  2. Each business can create a tailored set of AI agents specific to their needs. This means that instead of treating AI like just another tool, businesses can think of AI agents as part of their team.
  3. It's important for leaders to delegate tasks to AI agents. The benefit comes from identifying workflows that can be automated and training the AI to take over those responsibilities.

How to Invest in Space Tech: The Case of Rocket Lab

Space Ambition • 179 implied HN points • 12 Jul 24
💼 Business Startups
  1. Rocket Lab focuses on launching small payloads which is a growing need in the satellite market. This makes their service essential for companies needing timely deliveries.
  2. The company's innovative technology, such as 3D-printed engines, allows them to offer flexible launch options. This gives customers more control over their launch schedules.
  3. Despite some competition, Rocket Lab has a good chance to become a leader in its niche. Their strong team and existing client commitments make them an appealing investment.

How Successful Startups Solved the Chicken and Egg Problem: A Case Study of Tinder, Uber and Airbnb! | VC Jobs

Venture Curator • 359 implied HN points • 30 May 24
💼 Business Startups
  1. The Chicken and Egg Problem is common in marketplace-type businesses, requiring both supply and demand to succeed.
  2. Successful startups like Tinder, Airbnb, and Uber found creative solutions to attract their first users and overcome the challenge of building a two-sided platform.
  3. Timing is crucial for startups; being in a small market that is growing quickly can greatly increase your chances of success.

The 49-Year Unicorn Backlog🦄, AI has a gross margin problem🤖, The Path to CFO📚

The VC Corner • 379 implied HN points • 26 May 24
💼 Business Startups
  1. There is a significant backlog of unicorn startups that have yet to go public. This may impact the market's dynamics.
  2. Artificial Intelligence is facing challenges with its gross margins. Companies need to find ways to improve profitability as costs rise.
  3. There are clear steps and paths for finance professionals aiming to become CFOs. Understanding the necessary skills and experiences is crucial for career advancement.

OpenAI in Davos…Looking Back on 10 Years of Unicorns With Aileen Lee...Stripe and SpaceX’s Secondary Pricing

Newcomer • 1238 implied HN points • 19 Jan 24
🕹 Technology Startups
  1. OpenAI has faced challenges as a 'big tech' company early in its life, including raising significant funds and experiencing executive drama.
  2. OpenAI removed its 'Don't Be Evil' slogan and is now collaborating with the Department of Defense on cybersecurity projects.
  3. Aileen Lee's research on unicorns reveals that strong unicorns are more involved in enterprise tech than consumer tech, with many 'papercorns' yet to prove their value.

“The Hardest Coordination Problem on Earth”

The Generalist • 1060 implied HN points • 24 Jul 25
💼 Business Startups
  1. Focus on velocity, not just speed. It's important for your team to move quickly but also in the same direction towards the same goals.
  2. Use clear decision rights to maintain order. Make sure everyone knows who is responsible for what decisions to avoid confusion and internal politics.
  3. Don’t try to change everything at once. Some old practices may still be effective, and it's better to identify which parts need innovation rather than reinventing the entire process.