The hottest Startups Substack posts right now

And their main takeaways
Category
Top Business Topics
MKT1 Newsletter • 0 implied HN points • 31 Jul 25
  1. Finding the right mix of 'Fuel' and 'Engine' is key for startup growth. If these two are not balanced, it can hinder progress.
  2. Evaluating your startup's Fuel and Engine helps you identify what's holding you back. This can accelerate your brand development.
  3. You can access resources and templates that provide tools to help balance your startup's Fuel and Engine effectively.
Organic SaaS Growth • 0 implied HN points • 22 Aug 25
  1. If a YouTube channel isn't growing, it might just need a fresh strategy. Sometimes slow progress gives valuable insights for improvement.
  2. Using short, engaging videos can really help attract viewers and subscribers. It's about creating content that people find easy to watch and share.
  3. Balancing reach and resonance is key to success. You want your videos to reach lots of people while also connecting with your target audience.
Alex's Personal Blog • 0 implied HN points • 18 Nov 25
  1. Klarna had a strong first earnings report, with higher revenue than expected, showing that tech companies can grow while keeping costs stable.
  2. The value of Bitcoin dropped below $90,000, indicating a rough time for cryptocurrency markets.
  3. Databricks is looking to raise more funds privately, which raises questions about why it's staying out of public markets despite impressive growth.
Experiments with NLP and GPT-3 • 0 implied HN points • 03 Dec 25
  1. OpenAI is struggling against Google, which has a lot more resources and technical power to back its AI efforts. This puts OpenAI in a tough spot.
  2. The new strategy to improve ChatGPT might not be enough because Google has a strong advantage and can easily adapt as well.
  3. OpenAI is losing money and needs a huge amount of funding just to keep running. This isn't a sustainable way to operate a business.
The Green Techpreneur • 0 implied HN points • 21 Nov 25
  1. CleantechHUB connects climate entrepreneurs in Latin America with investors and resources they need to grow. This helps local innovators turn their ideas into successful businesses.
  2. The network aims to replicate its success by opening more hubs and supporting startups across the Global South. Their goal is to empower more founders while addressing local climate challenges.
  3. Tracking its impact is important, as CleantechHUB measures success not just by funding but also by the number of jobs created and COā‚‚ emissions avoided. They focus on building a diverse and inclusive startup ecosystem.
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Digital Native • 0 implied HN points • 11 Dec 25
  1. Generative media goes mainstream — expect a big share of social feeds and startups to use AI for video, audio, avatars, and personalized content, plus cultural and legal shocks like hit songs made with AI.
  2. Big tech and AI firms focus on monetization and consolidation: ChatGPT will adopt ads, companies like Anthropic and Stripe will make major acquisitions (with Anthropic likely to IPO), and incumbents will buy up smaller teams and products.
  3. Work and business models shift: autonomous agents will negotiate with each other and power new AI-enabled services that can scale into billion-dollar firms, pricing will move from per-seat to platform+usage, and there will be renewed demand for real-world experiences and ticketing reform.
Digital Native • 0 implied HN points • 03 Dec 25
  1. AI was the defining theme of 2025: companies leaned into augmentation over full automation, while IP and a growing backlash against fully AI-generated creators became major conversations.
  2. Big market moves reshaped tech — TikTok survived, a record VC-backed acquisition was set, prediction markets and space/defense heated up, and robotics began to help re-shore manufacturing.
  3. Applied AI showed tangible wins in healthcare and mental health, but consumer AI hardware and mainstream digital clones remain early and haven’t broken through yet.
Digital Native • 0 implied HN points • 26 Nov 25
  1. Powerful new creative models sharply lower the cost and skill needed to make high-quality images, videos, and content, triggering a surge of creators and shifting value toward discovery and curation platforms.
  2. AI is evolving from assistant to executor, so most knowledge workers will become middle managers who direct suites of automated agents, reshaping hiring, pricing, and organizational structure.
  3. Models enable extreme hyper-personalization—bespoke apps, ads, and synthetic people tailored to individual tastes—which will change marketing and media while also amplifying social backlash, inequality, and regulatory pressure.
Digital Native • 0 implied HN points • 19 Nov 25
  1. New York is an industry town with deep hubs for finance, healthcare, media, advertising, law, restaurants, fashion, real estate, and more.
  2. Many of those industries run on manual, fragmented workflows and large markets, so applied AI can quickly improve efficiency and create new business models.
  3. While San Francisco leads on foundation models and infrastructure, New York’s proximity to domain experts, customers, and operators gives it an edge in building and scaling industry-specific AI companies.
Organic SaaS Growth • 0 implied HN points • 02 Dec 25
  1. Many early-stage SaaS founders hit a "growth desert" around $1k–$15k MRR where early hacks stop working, churn rises, and revenue stalls.
  2. Fixing it requires a repeatable system instead of random marketing — focus on three engines: retention (a Shadow Concierge protocol), pricing that targets a "Level 3 Niche", and building one scalable acquisition channel.
  3. There’s a limited founding-member option offering a discounted price and 1-on-1 email support for a small cohort in exchange for honest feedback.
Organic SaaS Growth • 0 implied HN points • 28 Nov 25
  1. Black Friday-style discounts are being avoided because they turn serious products into cheap commodities.
  2. A hands-on SaaS Growth OS is being offered for founders stuck at $1k–$15k MRR to diagnose bottlenecks, plug retention leaks, and build one scalable acquisition channel — it’s not a video course or a swipe file.
  3. A Founding Member cohort opens Tuesday, December 2 at 10 AM EST with only 15 spots, lower pricing, and personal email support; reply "Interested" for first access.
ASeq Newsletter • 0 implied HN points • 04 Dec 25
  1. A prominent investor associated with Nucleus Genomics made a Nazi salute in public, creating a major reputational issue for the company.
  2. Multiple posts allege problems with Nucleus's legitimacy and integrity, and the company's aggressive response appeared to make things worse.
  3. The critic behind the allegations is controversial and shares risky health advice, but their claims still raise important concerns people should consider.
ASeq Newsletter • 0 implied HN points • 28 Nov 25
  1. The old Roswell company appears to be rebooting as SemiConBio with a new CEO (Mike Aicher) and a small team still active, which is surprising given expectations they were out of cash.
  2. Recent successful demonstrations of DNA expansion by companies like Roche could lower the technical bar for solid‑state readout technologies, making such sensors more attractive as alternatives to bilayer nanopores.
  3. SemiConBio’s specific sequencing approach probably isn’t a direct fit for reading expanded DNA, but some of its components or techniques might be repurposed to build a high‑speed, solid‑state readout.
Experiments with NLP and GPT-3 • 0 implied HN points • 27 Dec 25
  1. ARR can overstate the value of AI products because it counts one-off or novelty-driven payments; VRR measures sustainable revenue by applying a Utility Decay Coefficient based on workflow integration, model independence, and churn.
  2. Investors should run cohort utility audits and calculate a VRR gap using metrics like boring-day ratio, month-5 retention, integration depth, and model independence to separate ā€˜vibe’ revenue from durable revenue.
  3. VRR changes valuation logic by penalizing short-lived, novelty revenue to avoid inflated paper valuations and focus on products that create real habits and deep integrations.
Respectful Leadership • 0 implied HN points • 19 Dec 25
  1. A community meetup can deliver concentrated, practical business education that teaches what investors want, how to manage personal and company finances, and the basics of product development.
  2. Product work now demands attention to ethics and AI, and UX-focused practitioners can show how to build responsible, user-centered products that scale.
  3. Practical frameworks for leadership and people management, plus founder stories and networking, give attendees concrete tools and peer support to grow their ventures.
MKT1 Newsletter • 0 implied HN points • 07 Jan 26
  1. The Gen Marketer skillset is becoming the new baseline, so marketers must upskill in AI-driven tools and strategies to stay relevant.
  2. Effective campaigns in the AI era combine strategic thinking with AI-enabled creation and optimization to improve performance and scale.
  3. Slide decks, videos, and a template library explain these approaches, though some assets require a paid subscription to access.
Tippets by Taps • 0 implied HN points • 04 Jan 26
  1. Reading widely across subjects is the best way to build useful mental models, so prioritize and protect time for books.
  2. China’s industrial and AI progress may be underestimated and has major strategic implications, while tech wealth often favors startups over civic institutions, weakening cultural infrastructure.
  3. Young people are turning to high-variance bets (crypto, prediction markets, sports betting) because AI shortens career timelines and social media raises comparisons, and without strong capital taxation AI-driven capital gains could concentrate wealth across generations.
Tippets by Taps • 0 implied HN points • 28 Dec 25
  1. AI agents that hold and use decision history and surrounding context (a "context graph") will become the primary interface and could act as a new system of record on top of existing tools.
  2. AI is this generation’s foundational material—like steel—so when integrated deeply it can let organizations be redesigned rather than just having chatbots tacked onto old processes.
  3. Making knowledge work much cheaper will likely increase demand rather than reduce it, enabling small teams to tackle work that used to require big firms and creating new jobs and projects.
Digital Native • 0 implied HN points • 22 Dec 25
  1. AI is gaining persistent memory and true "world" understanding through agents and world models. That will unlock lots of new consumer and enterprise products, from lasting personal assistants to smarter household robots.
  2. Interfaces and go-to-market will decide the winners: assistant brands will dominate while UI becomes the main differentiator. Buyers will shift to finance teams focused on P&L, and traditional CRMs will be displaced by AI that ingests unstructured data.
  3. Policy and markets will accelerate AI with big M&A and new prediction-market ecosystems. Those gains will likely concentrate wealth and raise inequality, and some speculative AI rollups will fail even as non-AI, anti-tech products find real demand.
Curious futures (KGhosh) • 0 implied HN points • 11 Jan 26
  1. AI often produces imaginative but unreliable outputs that can be misleading or false, and those hallucinations can trigger real-world confusion and disruption.
  2. Organizations need human-led guardrails like futures literacy, workshops, and pragmatic labs to turn AI creativity into useful work and to prevent chaotic or harmful decisions.
  3. AI is already reshaping jobs, business models, and culture, prompting investor attention and community responses like repurposing spaces and experimenting with new social practices.
Alex's Personal Blog • 0 implied HN points • 20 Jan 26
  1. Global politics are fraying as the United States strains alliances and Europe moves toward more tech and economic self-reliance, which could shrink American influence and market access.
  2. AI adoption is skyrocketing worldwide, with multiple big players gaining massive user and enterprise traction, even as regulation lags and political favoritism complicates oversight.
  3. Venture capital is heavily concentrated in AI, creating pressure for big AI IPOs to return liquidity to investors while overall VC fundraising is down and non-AI startups—especially female-founded teams—are being left behind.
Alex's Personal Blog • 0 implied HN points • 08 Jan 26
  1. Venture capital fundraising has fallen a lot, but the U.S. — especially AI startups — grabbed a much bigger share of global funding, making American AI the easiest path to raise capital and non-American, non-AI startups the hardest.
  2. Anthropic’s sky-high $350B valuation can be justified by its rapid revenue growth and familiar revenue multiples, so the raise looks defensible even on conservative growth assumptions.
  3. New dev tools like Claude Code let individuals build powerful apps quickly (for example a GTO poker trainer), and there’s clear demand for cheap, simple hosting so creators can publish and run personal AI apps on the go.
Alex's Personal Blog • 0 implied HN points • 07 Jan 26
  1. Investors are pouring huge sums into AI labs — xAI’s $20 billion raise underscores how frenzied and competitive the AI race has become among well-funded indies and tech giants.
  2. Consumer-facing developer tools like Anthropic’s Claude Code are powerful and promising, but setup complexity and subscription costs still limit broader adoption; if they get easier and cheaper, many more people could build personal AI toolkits.
  3. Prediction markets are growing fast but suffer from brittle, vague resolution language, causing payout disputes and lost winnings; platforms need much clearer rules to preserve trust and avoid costly disagreements.
Digital Native • 0 implied HN points • 28 Jan 26
  1. Tech companies often build products for themselves and the wealthy, missing the needs of everyday people and large underserved markets.
  2. Big opportunities exist in building practical, vertical tech for non-technical users—like automating hospital discharges or early disease detection for farmers—which can be both impactful and profitable.
  3. Founders and early adopters should spend time with users outside the Valley and act as translators, turning powerful but complex technology into simple, trustworthy products people will actually use.
Digital Native • 0 implied HN points • 26 Jan 26
  1. Make your company synonymous with a clear category early so you become the go-to name in that space. Great product is the foundation, but strong marketing and positioning amplify how far you can go.
  2. Tell your own narrative and be proactive — if you don’t define your story someone else will take the spotlight. As categories get crowded, your message must get more specific.
  3. Hire a growth or brand marketer earlier than you think so distribution, messaging, and creative execution aren’t an afterthought. Put growth and brand skills on your early team to stay top-of-mind both online and offline.
davidj.substack • 0 implied HN points • 21 Jan 26
  1. Practical guidance on the must-have AI tools and skills to grow your career and business in 2026 will be a core focus.
  2. Expect a VC-focused perspective on whether AI is a bubble and which kinds of AI startups are likely to get funded next year.
  3. The message stresses that AI is accelerating fast and may make AGI imminent, and it looks at what's dying and what's next—AI agents, automations, prompting—using examples like AI-driven viral LinkedIn growth.
Simon Owens's Media Newsletter • 0 implied HN points • 09 Feb 26
  1. Pubity Group became a massive platform-native media network with roughly 170 million followers and about 240 billion annual views, sustaining that scale across multiple platform cycles without outside capital.
  2. The founder learned the platforms early by experimenting and treating posting like a game, using systematic testing to figure out what content scales.
  3. The company is turning platform-native virality into longer-term value by leaning into wholesome content as a business opportunity and building durable brands, original franchises, and real revenue.
Experiments with NLP and GPT-3 • 0 implied HN points • 13 Feb 26
  1. AI diffusion is the next big shift for organizations, and companies must move quickly to integrate AI across workflows or risk falling behind.
  2. Adopting AI isn't just buying subscriptions or tools; it means redesigning processes so AI use measurably improves outcomes and lets employees do more than before.
  3. People resist change, so leaders must set new processes to drive adoption; platforms for AI agents will help but enterprises will need stronger, purpose-built solutions and many startups will emerge to meet that need.
Curious futures (KGhosh) • 0 implied HN points • 01 Mar 26
  1. Reliable facts are fraying as authoritative sources retreat and amateur fact-checkers and myths rush in, making it harder to agree on what’s true. This growing uncertainty fuels confusion and reshapes how people build narratives about the present and future.
  2. Geopolitical and economic shifts — changing trade relationships, tariff moves, and semiconductor bottlenecks — are creating real strategic and market risks. Commodities and tech supply chains are now flashpoints that can quickly reshape industries and national security.
  3. AI and platform tech are remaking business models, social behavior, and security: chatbots testing ads, transport shifting toward service models, and agent platforms posing new attack surfaces. These changes bring fresh privacy and surveillance concerns, alter attention and work patterns, and produce novel vulnerabilities.
On Engineering • 0 implied HN points • 27 Feb 26
  1. Companies are shifting toward platform-style products where customers compose features from core primitives, which reduces the number of people needed to build and support those features. This is a strategic architectural change, not just a short-term cost cut.
  2. Many recent layoffs are as much a correction for pandemic-era overhiring as they are about intelligence tools, and AI is often used as a convenient narrative; the quieter impact shows up as unfilled requisitions and paused hires rather than dramatic firings.
  3. Engineers can’t just ā€œbuildā€ and expect success — competition is fiercer and the moat is now distribution, trust, and business skills, so actively learning adjacent skills, experimenting, and adapting is wiser than staying passive.
Organic SaaS Growth • 0 implied HN points • 25 Feb 26
  1. Most growth problems in early-stage SaaS aren't what they first look like; surface symptoms often hide the real issue.
  2. Founders often keep trying new tactics and channels because they haven't diagnosed where growth is actually breaking.
  3. The right move is to find the root cause of the slowdown and fix that instead of constantly experimenting with new growth hacks.
The Healthtech Initiative • 0 implied HN points • 02 Mar 26
  1. Small, autonomous teams that own their entire stack unlocked velocity and scale, while splitting functions (like mobile and backend) slowed delivery.
  2. Only use AI when it truly outperforms simple rules—reserve models for cycle prediction, symptom analysis, personalization, and fine-tune on women’s health data to reduce bias and improve safety.
  3. Build the core competitive advantage (the health AI and data flywheel) and buy everything else, using wearable time-series models to proactively predict conditions and power growth.
My Home Office Hacks • 0 implied HN points • 16 Mar 26
  1. Line makes you assign money to tasks and you forfeit that money if you don’t complete them, with the funds going either to the app or a friend you choose.
  2. That setup can punish procrastination twice — you lose the value of the task and also the money you put up as a penalty.
  3. It’s unclear and risky where forfeited funds actually go, creating trust and fairness concerns, though some people might still try the app.