The hottest Adoption Substack posts right now

And their main takeaways
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The Algorithmic Bridge 828 implied HN points 06 Mar 26
  1. A metric that mixes LLMs' theoretical abilities with real-world usage reveals a huge gap between what models could do and what they're actually used for. For example, models theoretically cover ~94% of computer/math tasks but are used for only ~33%, and a similar gap appears in legal work (~90% vs ~20%).
  2. There are two ways to read this gap: one is optimistic that adoption will expand until real use matches theoretical capability, and the other is that the gap shows real limits and inflated lab benchmarks rather than a temporary lag.
  3. The practical lesson is that the industry may be overestimating AI's near-term labor impact and needs to focus on rigorous evidence of real-world competence and adoption, not just benchmarked capabilities.
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.
Common Sense with Bari Weiss 1474 implied HN points 19 Dec 25
  1. A person can grow up not wondering about their birth family, then later seek them out and uncover hidden truths and lies about their origins.
  2. Reuniting with a birth parent after decades can be emotional and surprising, with moments of recognition and complicated feelings on both sides.
  3. The first few months of life are deeply formative, so even being adopted at four months means the baby has already experienced many important early bonds and routines.
Bet On It 130 implied HN points 03 Feb 26
  1. A rescue-style thought experiment doesn’t settle whether embryos and babies have equal moral worth because the likely chances of survival and future life matter, and different technologies or circumstances could change people’s intuitions.
  2. Making abortion illegal would likely increase the number of infants available for adoption, but real-world data show only a small fraction of women denied abortions choose adoption, so policy design and financial support for parents are crucial and costly considerations.
  3. Claims that moving children to richer countries or preventing abortions clearly improves outcomes deserve humility, since survival and quality-of-life comparisons across contexts are complex and shouldn’t be assumed without careful evidence.
Freddie deBoer 17171 implied HN points 06 Apr 23
  1. Physical intervention can be necessary to prevent harm, even in challenging situations.
  2. Adoption serves as a vital solution for children in need of homes and families who want to provide love.
  3. Real-world complexities often require pragmatic solutions, even if they may not align with idealistic views.
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Interconnected 169 implied HN points 03 Dec 25
  1. Forward deployed engineers (FDEs) are the on-the-ground builders who turn AI models into working systems inside large enterprises and governments, handling integration, customization, and deployment.
  2. FDEs are scarce and highly sought after, so companies are rapidly expanding FDE teams and partnering with global system integrators to scale capacity and meet enterprise demand.
  3. The FDE function originated in firms like Palantir and has become a core, strategic role that many AI labs now prioritize to drive real-world adoption of their technology.
QTR’s Fringe Finance 36 implied HN points 07 Feb 26
  1. Bitcoin just had a dramatic ~50% drawdown that feels like a real moment of truth, forcing both believers and skeptics to rethink what the asset actually is, not just its price,
  2. Mainstream adoption in the U.S. — ETFs, banks, retirement accounts, political support — means there may be fewer new buyers left domestically, which is the core bearish case about demand peaking,
  3. From here the paths split: it could slowly fade into a niche asset, enter a long sideways crypto winter, or rebound to new highs; either way, volatility remains Bitcoin’s defining feature.
QTR’s Fringe Finance 25 implied HN points 05 Feb 26
  1. People are coming home to see big losses in their brokerage accounts after a crypto crash and are suddenly asking what crypto even is.
  2. A lot of investors bought crypto because they were told it was the future and would only go up, not because they understood it.
  3. This collapse shouldn’t be surprising — the market was built on hype and unrealistic expectations, which made it fragile.
Tippets by Taps 19 implied HN points 07 Jan 26
  1. Self-driving tech loses its novelty fast and becomes an expected part of daily life after only a few weeks.
  2. Using self-driving removes low-level stress and cognitive load, turning long or stressful drives into relaxed, usable time.
  3. The real barrier is psychological trust, not capability — people resist ceding control to algorithms, though younger generations will accept it sooner.
Perspectives 7 implied HN points 30 Jan 26
  1. AI adoption has happened extremely quickly, with consumers embracing tools like ChatGPT far faster than past technologies, and we’re still in the early stages of broader impact.
  2. Training and running large AI models is very expensive and investment and infrastructure are concentrated in a few firms, so the ecosystem is still in a heavy build/investment phase rather than a mature, profitable one.
  3. Benefits are uneven: many corporate pilots fail to reach production, executives tend to gain more productivity than frontline workers, women use AI less, and entry-level jobs are being disrupted, so careful redesign and policy are needed to avoid widening gaps.
Software Snack Bites 10 implied HN points 16 Jan 26
  1. AI is an enablement shift, not a slow paradigm change — it's making people more capable right now because it’s easy to adopt and useful across skill levels.
  2. We’re still very early: most users treat AI as a simple answer engine, and that’s just the tip of the iceberg for self-teaching, new creators, and deeper technical work to come.
  3. Don’t dismiss the momentum — value and spending can grow quickly along an S-curve, and monetization paths like ads, commerce, and healthcare are only beginning to emerge.
Perspective Agents 6 implied HN points 25 Jan 26
  1. AI itself is incredibly powerful, but many companies see little value because they haven't invested enough in people, workflows, and everyday use.
  2. Big enterprise buys and long roadmaps often leave AI as expensive shelfware, while starting small and embedding AI into real team workflows drives adoption and impact.
  3. Real returns come from investing in a 'Human OS'—systems, habits, coaching, clear outcomes, exec sponsorship, and relentless testing—or else AI sits idle and becomes a competitive drag.
Moly’s Substack 58 implied HN points 28 Jan 24
  1. Immigration may not always lead to happiness and stability in a foreign land; think carefully about choices.
  2. Equality in marriages means different standards for who people choose to marry.
  3. Concerns exist about the safety and well-being of Chinese babies adopted by America, raising questions about adoption policies.
Tanay’s Newsletter 113 implied HN points 19 Feb 25
  1. The cost of using advanced AI models has dropped dramatically, making it easier for businesses to experiment and integrate AI into their products. This change opens up new possibilities for reaching millions of users.
  2. Reinforcement learning is proving effective for tasks with clear outcomes, which could lead to better performance of AI models over time. As these models improve, we can expect more widespread use of AI.
  3. The journey to adopting AI takes time, but it's happening faster than past innovations like electricity or telephones. Today, a significant portion of people are regularly using AI tools.
The Algorithmic Bridge 254 implied HN points 02 Feb 24
  1. New innovations are not instantly accepted by everyone, there is a gradual process of adoption.
  2. ChatGPT quickly gained popularity, breaking the norm that tools are not instantly widely accepted.
  3. ChatGPT did not have a 'hipster' phase; it became popular almost instantly.
Sunday Letters 79 implied HN points 26 Mar 23
  1. Simplicity often beats complexity when it comes to technology. A simple solution that works now can be more effective than a complex one that may take longer to perfect.
  2. In the tech world, being first is crucial. The first company to launch a new idea or product often wins, especially if it benefits from network effects.
  3. It's important to focus on what can be quickly addressed. Don't get stuck on minor issues when bigger, more impactful problems need immediate attention.
Africa Crypto Report (ACR) 19 implied HN points 27 Mar 23
  1. MetaMask partnering with MoonPay to allow Nigerian users buy crypto assets through bank transfers.
  2. The adoption of MetaMask in Nigeria shows a potential for easier onboarding experiences in the crypto space.
  3. eNaira in Nigeria is experiencing increased usage due to cash shortages.
The Digital Anthropologist 19 implied HN points 17 Aug 23
  1. Societies tend to fear new technologies initially, then overhype their potential once the fear subsides, influenced by norms, behaviors, and customs.
  2. Fear of new technologies can be a survival mechanism, signaling potential threats to culture and society.
  3. Adopting and adapting to new technologies in a fast-paced world requires new mental models, frameworks for unintended consequences, and agile governance mechanisms.
The Digital Anthropologist 19 implied HN points 06 Jan 23
  1. Culture plays a crucial role in how societies adopt technologies, influencing norms, behaviors, and decision-making processes.
  2. The adoption of technologies is influenced by factors such as cultural norms, political systems, and societal needs, leading to varied acceptance or rejection.
  3. Understanding cultural elements in technology adoption is key to creating impactful solutions that benefit society and anticipate potential challenges.
The Held Report 37 implied HN points 03 Jan 24
  1. Bitcoin DeFi is important for Bitcoin's future and adoption
  2. DeFi can lead to more speculative use cases and adoption
  3. The Held Report will focus on Bitcoin DeFi and may switch to paid in the future
Platform Papers 19 implied HN points 16 Feb 22
  1. Hackathons can help introduce new platform technologies by bringing developers together to collaborate and learn, ultimately boosting platform adoption.
  2. Temporary gatherings like hackathons provide a catalyst for technology platform companies to create positive buzz, align expectations, and accelerate platform growth through social learning and social coordination.
  3. Sponsoring temporary gatherings can be a strategic way for firms launching new platforms to attract initial users and complementors, but it's important to manage the sentiment that emerges from such events.
Coin Metrics' State of the Network 0 implied HN points 18 Nov 25
  1. Zcash has seen a huge price increase of almost 10 times since October due to growing interest in privacy in blockchain transactions.
  2. The amount of Zcash stored in private, shielded wallets has risen significantly, indicating that more users value privacy while using digital currencies.
  3. Recent technological improvements, like better wallets and easier cross-chain swaps, have made it simpler for users to use Zcash's privacy features.