imageswoeuxkqbieswdwy3wg6fkxgcrae3bh83bc6png">You Don’t Need an “AI Stack” as a Product Manager
By @etosova [ 6 Min read ]
Product managers do not need a perfect stack of specialized AI apps. They need clear judgment, useful context, and a few flexible tools. Read More.

Top Kubernetes-Native Inference Servers Ranked (2026)

By @merry-n-proprietary [ 6 Min read ]
Compare the best Kubernetes-native inference servers for AI workloads in 2026, ranked by scaling, multi-model support, production readiness, and more. Read More.

Meet the Hackathon Winner: Packworks on the Future of Phygital Retail and Building With Bright Data

By @proofofusefulness [ 4 Min read ]
Meet Packworks, a Bright Data Award winner using retail data, AI, and fintech to support more than 335,000 sari-sari stores in the Philippines. Read More.

Meet the Hackathon Winner: SpyderBot on the Future of Brand Discovery in AI Search

By @proofofusefulness [ 3 Min read ]
Meet SpyderBot, winner of a Bright Data award in the Proof of Usefulness Hackathon, building real-time analytics for brand visibility across AI platforms. Read More.

The Credential Problem Behind Agentic AI

By @alex-vainer [ 4 Min read ]
AI-assisted commits leak secrets at 2X the baseline rate. A working credential architecture for agents: references, runtime resolution, scoped vaults, wrapper. Read More.

The Future of the Internet May Depend on Proving You Are Human, Without Revealing Who You Are

By @ishanpandey [ 7 Min read ]
Bots now generate 53% of web traffic and AI fraud is surging. Inside privacy-preserving proof of human: World, Self Protocol, Humanity Protocol and what's next. Read More.

How GMX Liquidity Pools Work

By @sentra-bureau [ 15 Min read ]
Explore GMX BTC-USDC pool mechanics through on-chain data: fees, trader PnL, BTC exposure, and Non-Fee Component behavior. Read More.

10 Hottest Startups to Watch in 2026

By @ruth-hasson [ 5 Min read ] Read More.

Digital Transformation 2.0: What You Need to Know

By @robertmoskal [ 3 Min read ]
Business Process Engineering was once the purview of the wealthiest institutions. Thanks to coding agents, organizations of every size can reimagine work. Read More.

How to Run ONNX Transformer Models on iOS With Swift

By @kagangirgin [ 6 Min read ]
This article explores how to integrate an ONNX transformer model into an iOS application using Swift. Read More.
🧑‍💻 What happened in your world this week? It's been said that writing can help consolidate technical knowledge, establish credibility, and contribute to emerging community standards. Feeling stuck? We got you covered ⬇️⬇️⬇️ ANSWER THESE GREATEST INTERVIEW QUESTIONS OF ALL TIME
We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.
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Hacker Noon - Medium LinkedIn’s AI Slop Crackdown Could Expose the Fake Experts Flooding the Digital Marketing Industry


LinkedIn is taking aim at one of the biggest problems facing professional networks: the explosion of low-quality, AI-generated content designed to appear insightful, authoritative, and useful, but often delivering little more than recycled information dressed up as expertise.

The platform has introduced a new “Seems like AI slop” reporting option, allowing users to flag posts they believe rely heavily on artificial intelligence and contribute to the growing wave of generic content overwhelming online discussions.

For years, LinkedIn has positioned itself as a place where professionals share knowledge, build relationships and exchange industry insights.

However, the growing use of generative AI has created a new class of content creators who can produce thousands of posts without necessarily understanding the subjects they are discussing.

In a post on LinkedIn, chief product officer Hari Srinivasan acknowledged the scale of the problem, saying the company considers AI slop a major priority.




“We are ramping the ability for members to tell us if they believe a post or comment seems like AI slop. Slop is hard to define and the definition changes; this lets us tune our models and make better feeds.” Srinivasan said.



“We continue to improve and invest in our automation defenses. On comments alone, everyday we are now catching hundreds of thousands of automated comment attempts, and have blocked billions of other automation attempts (posting at scale, slop) in the last couple months alone..” he said.




The significance of the move is that LinkedIn is no longer relying solely on behind-the-scenes moderation systems. It is asking users to help identify content that damages the quality of professional conversations.

The platform is also expanding its automated defences, blocking hundreds of thousands of automated comment attempts every day and millions of other suspicious automation attempts in recent months.

New detection systems are being developed to identify AI slop and low-value content before it reaches recommendation feeds, while reports submitted through the new feature will provide additional data to improve these models.

However, the problem goes beyond AI-generated text.

The deeper issue is the growing number of online personalities, influencers and digital marketing operators who have built professional reputations around repeating information they have little experience or understanding of.

Across the digital marketing industry, countless freelancers and agencies have turned content creation into a production line. Articles are rewritten, repackaged and redistributed with minor wording changes, often giving the appearance of expertise without adding any new analysis, research or original thought.

The result is a professional internet increasingly filled with people commenting on industries they do not understand, promoting strategies they have never tested and presenting basic summaries as specialist knowledge.

For legitimate journalists, researchers and experienced professionals, this creates a serious credibility problem.

Expertise is not created by publishing hundreds of posts. It is built through experience, investigation, accountability and the ability to provide information that others cannot easily find.


Generative AI has made it far easier fo[...]

r people to imitate those qualities.


A person with limited knowledge of cybersecurity, marketing, technology or business can now generate convincing-looking articles, social media posts and industry commentary within minutes. The writing may appear polished, but the underlying knowledge may be shallow or completely absent.




The problem is not the technology itself, but how easily it can be used to imitate expertise.




Using AI as a tool to improve grammar, structure research or assist with editing is very different from using it to manufacture a false impression of authority.

LinkedIn’s changes could help expose this growing problem by making authenticity, originality and expertise more important signals than simply posting frequently.

The company is also planning to privately notify users when their content appears overly dependent on AI-generated writing. The goal is not to punish professionals who use AI responsibly, but to encourage users to maintain their own voice and perspective.

As part of the changes, LinkedIn is removing its previous “enhance your post” AI writing feature and replacing it with a proofreading tool designed to fix errors without rewriting a person’s style.

The battle over AI slop is not limited to LinkedIn.

Newsletter platform Substack recently partnered with Pangram to help identify when content may have been created using AI. Pangram has also raised $9 million to develop technology focused on detecting AI-generated material across the internet.

Smaller platforms are facing similar challenges. Digg shut down its Reddit competitor after struggling to control the number of bots flooding the service.

Cloudflare has warned the problem is accelerating, reporting that bot traffic across the internet has now surpassed human-generated requests — a milestone the company said arrived sooner than expected.

The challenge for platforms is no longer simply stopping spam. It is protecting the value of genuine knowledge in an environment where anyone can create the appearance of expertise.

If LinkedIn’s approach works, it could become an important filter against the growing economy of fake authority, recycled opinions and automated professional branding.

The future of online credibility may depend on a simple question: did a real person with real experience create this, or is it just another piece of content created to feed an algorithm?

Hacker Noon - Medium How to Build an Education Platform That Supports People Through Different Stages of Life
Over the past few years, the online education market has gone from niche courses to large-scale ecosystems capable of supporting people through different stages of life. One of the entrepreneurs who doesn't simply watch these changes but shapes them is Timur Ibragimov, founder and CEO of the education platform Sotka.



Starting with exam preparation for school students, Ibragimov has built one of the largest education platforms on the market: today, more than 70,000 customers choose the company's products each year, and its annual revenue exceeds $25 million.


In this interview, Timur Ibragimov explains why the future of education extends far beyond individual courses, how the role of edtech companies is changing, and why in ten years the main product will not be education itself but long-term support for a person at every stage of their development.



Why do most education platforms limit themselves to one product or one stage of a customer's life?

A lot of it has to do with the way the market developed. Most companies were built around one specific task: preparing for an exam, learning a language, mastering a profession, or upgrading qualifications. That approach is understandable and logical. Solving one problem is much easier than tackling several at once.

But the model has a limit. It makes you look at a person through the lens of a particular product rather than through the lens of their life path. In reality, people's needs keep changing. First, they need help at school, then with getting into university, then with learning a profession, and later with a career change or a new set of skills. So I think the companies that win in the long run will be the ones that learn to support a person through the different stages of their development.



When did you start looking at education technology companies this way?

Gradually, I suppose. We started by preparing students for university entrance exams. Then came the all-in-one model, which let us combine preparation for several subjects within a single product. After that, we launched a track for the exams students take to move from ninth grade into tenth.





Later, we began asking ourselves: if we already know how to help older students, why can't we help younger students? If the platform helps people prepare for exams, why not extend it to those interested in professions that are in demand? At some point, we stopped looking at separate stages of a person's life and began building a technology service for continuous development.



Is that why the company launched a track for students in grades 1 through 8?

Yes. We could see that many families only discovered us when their children reached the upper grades, with a year or two left before the exams. But helping a child earlier makes far more sense.

So we began developing a track for students in grades 1 through 8 and building a technology platform for younger students, supported by a strong team of engineers and teachers, including recipients of Teacher of the Year awards, winners of professional competitions, and specialists with a great deal of practical experience. That lets us work not only on exam preparation but also on building the foundational knowledge that develops much earlier.


<h2 id="h-why-were-professional-[...]

tracks-the-next-step">Why were professional tracks the next step?
Because the demand for new skills doesn't end after school. Look at the labor market, and it becomes obvious that people increasingly have to master new fields over the course of their lives.

So it seemed logical to add tracks to the platform that give people practical materials and tools for in-demand fields and help them start earning. Today, these are tracks in artificial intelligence, content creation, design, programming, and other in-demand areas. In effect, we have expanded the range of problems we can help our users solve.



So development is gradually turning into a lifelong process?

I think it always has been. What has changed is the pace at which the world is changing. There was a time when a person could acquire the knowledge they needed once and use it for decades; today, many professions change far faster. New technologies, new tools, and new employer requirements keep appearing.

So the ability to keep improving stops being an extra advantage and becomes a necessity. That is exactly why the service model that allows people to update their skills independently and regularly continues to grow.



Many companies sell education as a one-off service. Why do you consider that model limited?

Because it ends the moment one of the customer's problems is solved. Creating long-term value is far more interesting to me. Take the professional tracks: we built the model from the start so that a person retains access to the materials and information for a long time, and the materials themselves are updated regularly.

Technology changes too fast. What was relevant two years ago may no longer work today. So a company's job is not only to hand over materials. It is to keep updating both the information and the tools needed to master it, and to keep everything current.



What connects the products for school students, graduates, and adults inside one platform?

The idea of a person's development. Despite the age difference, people are solving a similar problem: they are trying to move to the next level of what they are capable of.

For a school student, that might mean getting into university. For a university student, access to the tools for a first set of professional skills. For an adult, a career change or a step up. The tools change, but the logic itself stays the same.



What does the ideal education platform look like ten years from now?

I think the boundaries between different digital education products will gradually disappear. People need separate courses or programs less and less as ends in themselves. What they need is a concrete result and a clear path to it.

So education platforms will increasingly turn into systems that support people over time. They will help people gain knowledge, master new skills, adapt to changes in the market, and find new opportunities to grow. In my view, that is where the future of education lies.



If you had to state the main principle of this model briefly, what would it be?

Don't build a product around one stage of a person's life. Build a system that helps them grow over many years. I think that is the direction the whole edtech industry is gradually moving in.

Hacker Noon - Medium What Happens During a Production Deployment? A Behind-the-Scenes Guide
You push your code. A few minutes later, it is live for real users.

Between those two moments runs a long chain of machinery: builds, artefacts, migrations, health checks, traffic shifts. Every production engineer depends on that chain, and many teams still build and operate it themselves.

Deployment infrastructure has quietly become operational overhead. It started as a technical necessity, something every team had to assemble because nothing else existed.

Today it is a second system your engineers maintain alongside the product, consuming on-call rotations, sprint capacity, and 2 a.m. attention that could go somewhere better.

In this article, we will walk through each stage of a real production deployment: the build, the artefact it produces, database migrations, health checks, rolling updates, and rollbacks. Along the way, we will look at why <underlineplatform-as-a-service (PaaS) tools handle most of these steps for you, and what it costs a team to keep handling them itself.



The Build: Turning Code into Something That Can Run

A deployment does not ship your source code as-is. It ships the result of a build. The build stage takes your code and turns it into something a server can run.

What this looks like depends on your stack. A Java or Go project gets compiled into a binary. A JavaScript front end gets bundled and minified. A Python app gets its dependencies resolved and pinned. In most modern setups, all of this gets packed into a <underlinecontainer image, which is a frozen snapshot of your app plus everything it needs to run.

The build stage also runs your tests. Unit tests, linting, and security scans all happen here. If any of them fail, the deployment stops before it can touch production. This is the cheapest place to catch a bug. A failed build costs you a few minutes. A failed deployment can cost you customers.

Teams that run their own pipelines spend real effort here. They maintain build servers, cache dependencies, and debug flaky test runners.

None of that work ships a feature. It is pure upkeep, and it never ends. A PaaS bakes this whole stage into the platform. You push code, and the platform detects your language, builds it the same way every time, and fails fast when something is wrong. The build still happens. Your engineers just stop paying for it in hours.



The Artefact: One Version, Frozen in Time

The output of a build is called an artefact. It might be a container image, a compiled binary, or a zipped bundle. Whatever the format, the artefact has one job: to be exact. It represents one precise version of your app, frozen at one point in time.

This matters more than it sounds. The artefact that passed your tests must be the exact same one that reaches production. If you rebuild between testing and shipping, you risk shipping something slightly different. A dependency may have updated. A build flag may have changed. "It worked in staging" often means "we built it twice and got two different results."


Good pipelines build once and promote the same artefact through every stage. Artefacts get versioned and stored in a registry, so any version can be pulled and run again[...]

later. That stored history is also what makes rollbacks possible, which we will get to soon.


On a PaaS, artefact handling is standard practice by default. Every deploy produces a numbered release. The platform stores it, tracks it, and can restore it. You do not have to design a registry strategy, write promotion scripts, or assign an engineer to own them. The discipline is built in.



Database Migrations: The Riskiest Step

Before new code goes live, the database often has to change with it. Maybe the new version needs a new column or a new table. These changes are called migrations, and they are the most dangerous part of most deployments.

Why? Code is easy to replace. Data is not. If you deploy a bad code version, you can swap it out. If a migration corrupts or drops data, there may be no clean way back. Migrations also create a tricky window of time. For a few minutes, old code and new code may run against the same database at once. Both versions have to work with the schema during that window.

The safe pattern is to make migrations backwards-compatible. Add the new column first, deploy code that can handle both shapes, then clean up the old column in a later release. It takes more steps, but each step is safe on its own.

A PaaS cannot write your migrations for you. No tool can know what your data means. But a good platform gives migrations a defined place in the release process, runs them in order, and logs exactly what ran and when. That structure prevents the classic failure where someone runs a migration by hand and forgets to tell the team.



Health Checks: Proving the New Version Is Alive

Once the new version starts, the platform does not just trust it. It checks. A health check is a small endpoint in your app, often just a route that returns "OK." The platform calls it over and over. If the app answers, it is considered healthy. If it does not, the platform assumes something is wrong.

There are usually two kinds of checks. A readiness check asks, "Are you ready to receive traffic?" A liveness check asks, "Are you still working, or should I restart you?" The difference matters. An app can be alive but not ready, such as when it is still warming up a cache.

Health checks are the gatekeepers of a deployment. No traffic reaches a new version until it proves it can handle requests. Without them, you would be routing real users to an app that might still be crashing on startup.

Every serious PaaS runs health checks automatically. You define the endpoint, and the platform handles the polling, the timeouts, and the decisions. Teams that build this themselves tune all of those settings by hand, and they usually learn the right values through painful trial and error. That tuition is paid in engineering time, on a problem the industry solved years ago.



Rolling Updates: Replacing the Plane's Engine Mid-Flight

Here is the hard part. Your old version is serving live traffic right now. You need to replace it without dropping a single request. The most common answer is a <underlinerolling update.

It works like this. Say you have four copies of your app running. The platform starts one copy of the new version and waits for its health checks to pass. Then it shifts a slice of traffic to it and shuts down one old copy. It repeats this, one copy at a time, until only the new version remains. Users never notice, because at every moment there are enough healthy copies to serve everyone.


Some tea[...]

ms use variations of this idea. A blue-green deployment runs the full new version beside the old one, then flips all traffic at once. A canary release sends a tiny share of users to the new version first, watching for errors before going wider.


Doing this by hand means writing orchestration logic, managing load balancer rules, and handling every edge case where a step fails halfway. That is months of engineering effort to build and a permanent tax to maintain, all for behaviour a PaaS ships as the default. On a platform, you get zero-downtime releases out of the box, not as a project your team has to staff.



Rollbacks: The Escape Hatch

Sometimes the new version passes every check and still breaks something real. An error rate climbs. A page loads blank. Now speed matters more than anything, and the fastest fix is rarely a new patch. It is a rollback: redeploying the previous artefact that you already know works.

This is why frozen, versioned artefacts are so important. A rollback is only fast if the old version is stored, tested, and ready to run. Teams that rebuild from an old commit under pressure are gambling at the worst possible time.

On most PaaS platforms, a rollback is one command or one click. The platform keeps your release history and can restore any previous version in seconds. That single feature has saved more on-call engineers' nights than perhaps any other.



When you don't need a PaaS

The case for handing deployment to a platform is strong, but it isn't universal. There are teams for whom owning the pipeline is not overhead; it is a deliberate and justified engineering decision.

When compliance demands it

Regulated industries like finance, healthcare, and government often operate under requirements that a standard PaaS cannot satisfy out of the box. Data residency rules may dictate exactly which physical infrastructure your builds touch. Audit requirements may demand a level of provenance and access logging that a managed platform doesn't expose.

Security controls may need to extend into the build environment itself, not just the runtime. In these contexts, the cost of owning the pipeline is real, but it is the cost of operating in that industry.

When deployment is your product

If your company sells deployment infrastructure, a CI/CD platform, a release orchestration tool, an internal developer platform, then your pipeline is not overhead at all. It is the product.

The engineers maintaining it are doing product work, not distraction work. The same applies to platform engineering teams at large organisations whose explicit charter is to build and own the deployment layer for dozens of other internal teams. In both cases, the question of "why are we running this ourselves" has an obvious answer: because this is what we do.

When your infrastructure is genuinely unusual

Most PaaS platforms are optimised for stateless web services and standard container workloads. If your system falls outside that envelope, GPU clusters, real-time systems with strict latency requirements, hybrid on-premise and cloud deployments, hardware-in-the-loop testing, a general-purpose platform may simply not fit.

Shoehorning an unusual workload into a PaaS often produces more friction than building narrow, purpose-built deployment tooling around the specific constraints you actually have.

The common thread across all three cases is specificity. The teams that are right to own their pipelines can usually state clearly why a platform doesn't fit. If the answer is "we've always done it this way" or "we like having control," that's worth questioning. If the answer is "our compliance requirements mandate X" or "we sell this," that's a reason.



<stron[...]

g>Should You Still Be Running This Yourself?
A PaaS does not make any of these steps disappear. The build still runs. Artefacts still get stored. Migrations still execute, health checks still poll, and traffic still shifts one copy at a time. Abstracting these mechanics does not eliminate them. It standardises them, and pushes their maintenance onto a team whose entire product is deployment.

That is the question every product team should now ask plainly: why are we still building and operating this machinery ourselves? A decade ago, a custom pipeline was unavoidable. Today it is a choice, and for most teams it is the wrong one. Every hour spent debugging a flaky build agent, tuning a health check timeout, or patching orchestration scripts is an hour taken from the product your customers actually pay for. The pipeline does not differentiate you. It cannot. Your competitors' deploys work the same way yours do.

Know how the chain works, because on-call at 2 a.m. demands it. But knowing how it works is not a reason to own it. "We built our own deployment system" is not a badge of honour anymore. It is an admission that your team maintains a second product with no customers. Unless deployment infrastructure is your business, hand the machinery to a platform, and put your engineers back on the work only they can do.



Hope you enjoyed this article. You can <underlineconnect with me on LinkedIn.

Hacker Noon - Medium Sony's disc-free PlayStation strategy could reshape China's console market
On <underlineJuly 1, 2026, Sony Interactive Entertainment announced that it would stop producing physical discs for PlayStation games. This announcement was relatively ill-received by many around the world, but its implications are especially significant in China, where Japanese console makers play a unique role despite China’s relatively small console market.

This move might seem inconsequential, particularly given the fact that China’s gaming market is dominated by PC-based and mobile game platforms in comparison to consoles, which comprise a paltry <underline11% of the market. However, for China’s dedicated minority of console players, physical media is a critical lifeline for game preservation, enabling accessibility while still navigating strict domestic regulations. For Sony, whose PlayStation brand has spent years trying to expand its footprint in China, this decision could unintentionally weaken one of its ecosystem’s strongest competitive advantages.



The complex evolution of China’s video game market

Despite its current <underlineheavyweight status as one of the world’s largest video game markets, developing this ecosystem has not been without its challenges. In the early days of China’s video game industry, intellectual property protections were a particularly hot-button issue, with a <underlinecommon theme being the controversial practice of “reskinning” of popular video games from international sources for the Chinese market. The Chinese government compounded this effect by also <underlineinstituting bans to restrict adolescent gaming due to gaming being perceived as “<underlinespiritual opium.”

Another factor stifling the video game industry in China comes from the government’s <underlineconsole ban from 2000 to 2015, which restricted the growth of the video game industry in peak years. The implications from this ban are still being felt today, with companies like Japan’s Sony and Nintendo having <underlinerelatively limited offerings for their console-based games in comparison to PC and mobile games.


However, since that time, cultural perceptions have shifted significantly. The <underlinelate 2019 launch of the Nintendo Switch in China with Tencent’s help was one of the most concerted pushes in recent history to change said cultural perception. Additionally, the Chinese government has played a role in this as well, with its embrace of gaming via blockbuster titles like Black Myth: Wukong as <underlinesymbols of cultural and technological advancement he[...]

lping to revitalize the domestic console scene. This changing landscape has also created new opportunities for Japanese console makers seeing growth beyond their mature home market.




Why physical video games matter to Chinese gamers

The Chinese government has a <underlinevery lengthy and robust process for approving video games, with a particularly onerous process for Western-based video games, which has stirred consternation from gamers eager to collaborate and experience new gaming experiences. As such, the gray market for physical games has long been a <underlinecornerstone of China’s gaming culture, enabling gamers to access video games in a timely fashion.

Ranging from <underlinephysical marketplaces like Huaqiangbei to online platforms like Xianyu/Taobao, this booming grey market enables gamers to experience and subsequently resell games accordingly. These physical discs also enable access for gamers, bypassing Chinese censorship requirements imposed for game localization and production companies alike.

By removing physical discs from this equation, Sony is inadvertently closing this vital backdoor, removing domestic Chinese access from internationally well-acclaimed video games that may not yet have received official regulatory approval from Chinese authorities. For a Japanese company that has spent years trying to cultivate Chinese gamers while still complying with the Chinese government’s regulations, this shift to digital-only distribution risks narrowing the practical appeal of the PlayStation console. As such, if these backdoors are closed, a digital-only console would effectively become a paperweight for highly acclaimed, yet unapproved, global releases.



The tangible value of physical discs

Beyond bypassing Chinese censorship, the physical disc holds immense tangible value for Chinese gamers, serving both as an economic subsidy and a highly-coveted collectible. Global game releases cost roughly $70 USD (around ¥500 RMB), making this a luxury expense. By comparison, an approved release for the Chinese market is often around <underline30% to 55% cheaper. Physical media also enables a robust secondhand market, with gamers able to purchase a new title, play it, and resell it to recoup a portion of their initial investment. Removing the physical disc destroys this resale subsidy, pricing out the underserved and middle-class gamers from the console ecosystem.

Furthermore, the <underlinerecent boom in Chinese-origin collectibles, driven primarily by PopMart’s Labubu character, could also leave a significant economic growth opportunity on the table. The gaming collectible market has been estimated to be worth <underline$142b, with console-driven launches accounting for 26% of this market. In fact, collectibles have even expanded to quasi-”vintage” games, with the <underlineretro video game market itself experiencing surges in popularity in recent times.


In fact, this demand for physical ownership is so strong that local developers are actively pushing [...]

back. On <underlineJuly 11, 2026, game publisher AstroLabe Games, of F.I.S.T.: Forged in Shadow Torch fame, reaffirmed its commitment to offer physical discs for all its upcoming game titles. This recognition by AstroLabe Games points to the fact that the market explicitly recognizes how discontinuing physical media alienated a core, highly dedicated gamer audience.




Conclusion

With video games already being such a substantial market in China, it becomes clear that these same games are a massive cultural and economic force in China. The emergence of collectibles, toys, and other gaming-adjacent products will undoubtedly be a significant economic opportunity for China.

However, the removal of video games’ physical discs will have a significant impact on this ecosystem, which operates out in the open, though under technically illegal circumstances. For Chinese gamers, physical discs represent the final safeguard for ownership, affordability, and unrestricted access to the global gaming community, and the move by Sony to pursue a disc-free future will have disastrous effects on China’s console gamers. As such, Sony’s digital-only plan may intentionally make its flagship PlayStation console less attractive to one of Asia’s most strategically important and largest gaming markets.

Image Credit: CNBC

Hacker Noon - Medium The HackerNoon Newsletter: AI’s Water Problem Is Smaller Than You Think (8/9/2026)
How are you, hacker?


🪐 What’s happening in tech today, August 9, 2026?


The HackerNoon Newsletter
brings the HackerNoon homepage
straight to your inbox. On this day, US military dropped the nuclear bomb "Fat Man" over the city of Nagasaki, Japan in 1945, Computer Pioneer Marvin Minsky was born in 1927, First Email Sent From Space in 1991,

and we present you with these top quality stories.

From I Scored a Perfect 996 on Anthropics Claude Certified Architect Professional Exam
to A Netflix Engineer Built a Free Tool That Cuts Your AI Token Bill by 88%,
let’s dive right in.

I Scored a Perfect 996 on Anthropics Claude Certified Architect Professional Exam




By @pranavsaji [ 8 Min read ] How I scored a perfect 996 (100% in all 7 domains) on Anthropics Claude Certified Architect Professional exam, and the architect mindset it rewards. Read More.

AI’s Water Problem Is Smaller Than You Think




By @zbruceli [ 42 Min read ] AIs water problem is smaller than youve been told. Waters problem is far bigger — and, for the first time, solvable. Read More.

A Netflix Engineer Built a Free Tool That Cuts Your AI Token Bill by 88%




By @cloudsavant [ 18 Min read ] A Netflix senior engineer built Headroom, an open-source context compression layer that cuts AI token usage by 60–95% with zero accuracy loss. Read More.

Easiest Way to Deploy Open-Source Models to Production in 2026




By @merry-n-proprietary [ 9 Min read ] You picked the open-source models. Now comes the hard part: production. Compare DIY inference, managed APIs, and SIE for scaling AI agents. Read More.

The Cooling Revolution That Could Save a Warming World




By @zbruceli [ 18 Min read ] Cooling has quietly become the most critical public infrastructure of the 21st century. Read More.

What Happens to Your Engineering Platform When AI Raises the Baseline




By @indrivetech [ 11 Min read ] How AI is reshaping engineering platforms, hiring, developer workflows, MCP infrastructure, governance, and the role of human judgment. Read More.

The AMPED Architecture: An Enduring Blueprint for Efficient Web Servers from 1999




By @darshshah [ 4 Min read ] How a 1999 paper defined the AMPED web server architecture. See how separating control flow from I/O shapes modern caching, performance system design Read More.

RAG, AI Agents, and Agentic AI: Most Developers Are Confusing All Three




By @santoshmahale [ 7 Min read ] RAG, AI Agents, and Agentic AI are three different things. Most developers are building the wrong one. Here is the clearest explanation you will find. Read More.


🧑‍💻 What happened in your world this week?

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We hope you enjoy this worth of free reading material. Feel free to forward this email to a nerdy friend who'll love you for it.See you on Planet Internet! With love,
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Hacker Noon - Medium A Perfect Example of a Web3 Product Launch PR&Comms Disaster: Ledger Recover, 2023
Launching a new Web3 product without proper communication to the media and public can quickly turn into a nightmare. The PR failure during the launch of Ledger Recovery is a perfect example.

A bit of context.

In the crypto community, there's a well-known saying: "Not your keys, not your coins" — this is the golden rule of security in the world of digital assets, meaning that without full control over your seed phrase (private keys, password, or recovery phrase), you are not the true owner of your coins. The ColdCard hack once again confirmed this.



Ledger Recovery is a service that allows storing a seed phrase in a special way. It's split into three parts, each stored "in the cloud" by a different company, and in case of loss, it can be recovered like a forgotten password.



It was precisely to solve this problem that Ledger Recovery was proposed as a solution, but users grew alarmed — since enabling such a service could mean access to the password being opened up to a third party in the form of the three companies storing it, meaning there would exist a technical possibility for accessing cryptocurrency without the user's knowledge, without their desire, and without their permission. This is where the story of one of the most epic PR disasters begins.

Ledger's PR&Comms Mistake






You’re saying this is not what customers want. Actually, this is what future customers want

Pascal Gauthier, CEO Ledger




Source: <underlinehttps://www.coindesk.com/tech/2023/05/16/ledger-bats-back-criticism-of-new-wallet-recovery-service



After announcing the new service, the company received negative feedback from the community. In response, the company’s director decided to clarify (what he considered) the key points during a Twitter Space. During the broadcast, he essentially accused the community of being ignorant, shortsighted, and lacking understanding of the technology — which only made the PR disaster worse.



To try and put out the fire, the former CEO attempted to fix the situation by posting a message on Reddit.

__ __

This post is more constructive, but it breaks an important logical sequence. It begins with a description of personal feelings and emotions, followed by accusations of inciting hatred, then an apology, and only after that — a clear explanation of what actually happened.



A more appropriate order would be as follows:



First and foremost: emphasize that the issue concerns a failure in communication with the media and the public.



Second: offer an apology for the negative emotions caused, express understanding, and promise that such a situation will not happen again.

Causes of the PR Disaster and Key Mistakes:

* The company’s spokesperson lacks charisma.
* The company ignores the med[...]

ia, relying solely on its own social media channels.
* The spokesperson entered into an open confrontation with the community.
* A second spokesperson failed to properly shape their message.


The company had no media communication strategy and did not build transparent relationships with journalists. It focused entirely on technical product development while neglecting external communications. Notably, after criticism in May, the company postponed the launch — but in October, once again, went ahead in a way that ensured a public failure. The situation was finally defused only after the company published a detailed technical breakdown of the new service.


Commercial Impact

How a product or service is presented in the media is more important than its technical specifications. In 2023, Ledger was the leading cold wallet provider, with a market share of 70–80%, compared to 10% for its closest competitor, Trezor.



In the first week after the Ledger Recovery announcement, Trezor’s sales surged by 900%, and by the end of 2023, Trezor had tripled its total sales. Its market share rose to 30%, while Ledger’s share dropped to 60%.

Trezor’s Response

Trezor took the opposite approach, publicly expressing full support for its users. Company representatives emphasized that their devices are completely open-source and cannot — under any circumstances — be used to extract a seed phrase remotely. Trezor’s CEO stated that 100% control must remain with the user and that such a backup recovery service will never be implemented in Trezor devices.

What Actually Happened:

1. The company announces the service.
2. It receives a wave of backlash.
3. Postpones the launch for 6 months — but does not revise the PR strategy.
4. Launches the service without any changes to its communication approach, repeating the same mistake as in step 1.
5. Faces an even stronger negative reaction.
6. The CEO enters into a confrontation with users.
7. A co-founder acknowledges the PR failure.
8. The company publishes technical documentation and offers detailed explanations.



The community accepts the explanations, and the crisis slowly dies down. The commercial damage, however, is already done.

What Should Have Happened:

1. The company announces the service.
2. After receiving backlash, it reassesses the situation, adjusts its strategy, and works to minimize the damage.
3. Publicly acknowledges the PR failure and announces that those responsible have been let go.
4. Postpones the launch — giving time for the new team to properly prepare a media strategy.
5. Publishes detailed technical information and provides transparent explanations.
6. The community accepts the explanation, and the crisis begins to resolve.
7. The company launches the service.



A dismissive attitude toward media relations and communications, combined with the founder's desire to personally represent the product, led to losses of millions of dollars. I'm confident that having a professional Head of PR & Comms on staff would have prevented these entirely avoidable losses.



Crisis communications isn't just about what to do when a problem occurs — it's about knowing what kinds of problems can happen and when. Was it really so hard to imagine that issues might arise when launching an innovative product in the high-tech segment? Wasn't the risk of an ambiguous reaction obvious?




At the height of the crisis, Ledger refused for a long time to demonstrate the source code that would confirm the full security of t[...]