frankie-tales

Is the future federated? Or, why the hyperscalers are here to stay

2026-08-07T19:00:00Z

Sovereignty in the EU is now the trend, at least as a conceptual idea. Someone finally discovered that most of the Western world is dependent on a few US big companies, and the current status of Geopolitics is quite confusing, causing stomachaches and concerns among multiple governments.

Under these conditions, it is a good idea to understand the status of the mainstream internet services, including the so-called cloud and social networks. As explained in a past post, for some of these services, the EU situation is not so bad. We have many good companies that offer hosting and cloud services at a good level, and we have all the skills in-house. Therefore, at least for basic services, including distributed storage, email systems, and computing resources, we are in a position to be independent within a reasonable time frame. Of course, the number and extent of our data centers are not comparable, but if we do not have ambitions of offering such services worldwide, they can be enough for European use.

About social networks and instant messaging systems, among others, the situation is more concerning. While some alternatives exist, in many cases the network effect and first-mover advantage are strong and heavily weigh against building any real alternative. The tragic reality is that a pure distributed network of peers, which has been the core of the Internet since its birth, has been disrupted by the imposition of concentrated, single-company, non-standardized services. Think of WhatsApp, Facebook, LinkedIn, X/Twitter, Instagram, YouTube, or even the so-called alternative like Telegram or Bluesky. Most of the concrete alternatives are simply regional or restricted, simply a different incarnation of the walled garden concept. Think of TikTok, WeChat, Sina Weibo, and other regional services; they are simply different, isolated networks that do not communicate with others.

Like it or not, the only true alternatives for such systems are the fully federated services, such as Mastodon, Matrix, DeltaChat, or Peertube. There are literally dozens of such independent services based on open protocols, and they fully reflect the original idea of the Internet networking. Problem solved? Unfortunately, no, because the scale of such implementations is far from being comparable. We talk about thousands (about 1,5 million monthly active users in the luckiest case) of users against billions: a full order-of-magnitude difference, which causes evident network-effect problems. Common users are simply not incentivized to participate in such alternative services unless strongly motivated.

But imagine for a moment that all Internet users would like to enter the federated worlds.

In most cases, the typical federated server hosts a few hundred to a few thousand users. For such numbers, very small management teams and even small budgets could be viable and easily covered through crowdfunding. The most populated Mastodon instance (Mastodon.social) counts less than 1 million accounts with less than 300,000 daily active users currently. In a different service context, Codeberg supports less than 400,000 users and 700,000 projects, through 1,700 active members for its association (numbers of 2026). This is perfectly viable for a small-scale service and also the ideal situation with a good tradeoff between quality of service and efforts/size.

In our hypothesis, such servers would probably be subject to an average load multiplied by 1000 times, even in the case of fully working federated mutual help by smaller instances. In order to avoid service collapse, such instances would require an intensive architecture improvement and a significant increase in human effort for management. In other words, big money and the spreading of efforts among many individuals and organizations. Finding a tradeoff to avoid a new concentration and consolidation of services in the hands of very few actors would be the next challenge.

Again and again, my consideration is always the same: it is not only a matter of open protocols, mutual peers, and technicalities; it is a matter of governance and sustainability. The crude reality is that concentration among a very few active parties (just another oligarchy of service providers) could be unavoidable as the number of participants scales up. Of course, the only possibility of avoiding such evil concentrations is to ensure sufficient fragmentation by conception, for example, by imposing a maximum number of users per instance, or by maintaining small worlds of strictly thematic/regional instances.

So, federated services could be the answer for the future, but only by ensuring enough diversification of equal-weight instances, which could not scale at the same rate as the number of active users. Small is nice and safe, and this is the natural scale of federated servers to retain. In the opposite case, that would only become the next large walled garden, with serious sustainability problems and the constant temptation of having a new king of the realm. The obvious implication is that the mainstream bigco services will not be threatened by such alternatives, even considering that a lot of people are simply not aware/interested enough in privacy and digital rights. I think the only true limitation to well-known hypertrophic services can and should be found in international and national regulations, implemented with a grain of salt to avoid excessive problems and management load for federated services. Such a grain of salt and reasonability could be the key for the future, or, in the opposite case, establish the end of the Internet dream, which is already threatened by hyperscalers.

To understand the matter, think of Gmail, which is probably the most common email service worldwide. The most credible estimate is that almost 40% of email traffic is managed there, making the whole email thing a fully federated service with a few dominant providers. Most users do not search for alternatives, and many may have multiple alternatives and Gmail in use for different purposes. Even in these conditions, email is an example of a successful federated service. I would be happy if social networks moved in such a direction, frankly.

A completely different matter is the AI drama, where I see most of the risk for the future, for both Europe and most of the free world. Incredibly enough, the only current concrete alternative to the hypertrophy of less than a handful of US giants is represented by the open-weights, Chinese models. They could also be used at a reasonable scale locally, even if not for personal use. Unfortunately, the finest models are also extremely demanding for computing resources (both in terms of memory, storage, and GPUs) and out of reach for individual use. They can be considered for business investments, but it is already evident that a lot of effort is required to create an effective harness, where most of the value is currently present. The whole framework of agentic software and the capability of aligning models to goals will be the challenge of the future, but that will be out of reach for most users (including most companies), who the limits of general providers (OpenAI, Anthropic, Google, or anyone else) will constrain.

More and more, I see personal computing in the AI context will consist of running software on someone else's cluster, with all obvious implications for privacy and security for the average user. We will live sad times about that, with personal computing becoming managed computing, and users reduced to customers. Of course, the biggest problem is the awareness of users in such conditions, which appears more and more complicated due to the absence of a fully independent alphabetization policy in this new(?) digital world.

But maybe this is matter for another post...

The problem is not only if, but how.

2026-06-01T13:30:00Z

Ok, such dramas and the whole topic are starting to be annoying. The last episode was the rsync project with the well-respected Andrew Tridgell as maintainer, who initiated a Claude-based development effort for the 3.4 series a few months ago. The rsync tool is a well-known, widely used tool for copying files between hosts in a smart way, includes a daemon to optimize file transfers, and serves as an entry point for synchronization.

Only at the end of May, when some regressions began to appear, this step by the tool's main developer triggered the opening of a rather harsh issue regarding the use of AI agents in development. One of the most consistent changes in the source tree has been the introduction of Python helpers to replace the tool's test coverage. This is not a new type of controversy; it appears as a quite common pattern. AI tooling for programming (or automatic programming, as Antirez calls it) based on specifications and natural language appears to be quite widespread nowadays.

It is no novelty that such applications provoke a divisive reaction, with fans and detractors of a tool that, at first glance, appears almost magical for creating new programs from scratch in any language, or for reviewing existing code, or for evolving any existing project through extended, progressive pull requests. This is particularly annoying for many contributors when the AI agent is blindly used as a committer or to create PRs or issues. The whole controversy comes into dramatic focus when the project is a prime-time one, as in the case of rsync.

Note that rsync has been with evidence in quite low-intensity maintenance in recent years, with several hundred issues open and almost 50 PRs proposed but still pending. This is quite normal for seasoned FOSS projects, like it or not, and specifically for low-voltage tools that have most of their life-cycle in the past. Rsync is a tiny utility based on less than 150,000 lines of C code, started about 30 years ago by Tridge. In 2024, he stepped up again as a maintainer, likely due to the project's overall status (merely not abandonware, but almost such). This is, unfortunately, the known problem of too many FOSS projects to count: they are old, seasoned programs developed years ago and substantially frozen, but for minimal maintenance. They are often written in legacy languages, such as pure C, which are quite far from the interests of average Gen Z developers. Development teams are minimally set up, even under a foundation umbrella, and interest in advancing them concretely is equally minimal. They are what I call ‘good enough’ projects, often of widespread use. They could be so legacy that they are considered carved in stone.

Of course, in 2026, the temptation to revitalize such legacy programs with AI tooling is extremely high. It is higher when developers are overwhelmed with many other tasks, and you know, maintaining such a project can be extremely boring. But when the tool in question is considered a brick of the whole FOSS basement and used as such by tons of reverse-dependent projects, the whole operation can be extremely prone to controversy and intolerance. There are not only problems of quality assurance for the final result, but also ethical and philosophical questions about the use of AI tooling. All such aspects cannot be ignored, and some kind of caution is required.

To introduce AI tooling into such a project, the first step is to reach an agreement among all parties involved. That would lead to an accepted, explicitly stated AI policy (which apparently lacked in the case of rsync). The most accepted approach currently is a rigorous human-in-the-loop development policy (as accepted in the Linux kernel, for instance). Without them, any forced use of AI tooling for community-based FOSS projects is doomed to failure and controversy, which could ultimately lead to a fork and the dispersion of effort and energy. This consideration implies that the project has already adopted some form of governance. Once the IF phase is passed, the HOW step must be consequent. It is totally unacceptable that a human-in-the-loop becomes a purely formal step before committing. In other words, the project committers need to strictly review and commit to avoid regressions and subtle bugs, which could easily be present with or without the AI contribution, but for sure are a risk when one touches legacy code. The human committer is responsible. Being proactive is a duty and cannot be neglected. Better to do nothing than mess up working code. I don’t know if this has been the Tridge’s case, but regressions have happened, which isn’t a good signal, and the whole thing could lead to unexpected upset.

But, but, but... Wasn't the AI tool the magic silver bullet to solve all software issues and productivity? Well, dudes, I’m afraid that you need to change your mind. There’s no silver bullet, even 30 years later. There’s no magic recipe to solve all problems with undersized projects, and someone has to pay the debt.

We still need engineers who do their job, damn it.

The Web is dying, long live the World Wide Web.

2026-05-27T13:30:00Z

I already dealt with the status of the WWW in the recent past. See, specifically, the authoritative opinion of Sir Tim Berners-Lee on that. Multiple dynamics have upset the initial idea of a distributed, democratic, and influential worldwide system, as conceived in the 90s, including the roles of BigCorps, socials, and geopolitics. What appears to be the last brick in the grave of the WWW is the current AI wave, which introduces two distinct elements of breaking an already compromised equilibrium.

It is now evident that a large part of the WWW content is AI-generated [3,4], often with very low quality and care. Let me point out, for instance, articles in the well-known Medium.com magazine (but that’s not specifically a problem of it, it is a general one): it is not a novelty that quite a lot of authors there are intensively writing most of their content via AI, with just minor human contributions. This is not new: in the past, the figure of the ghostwriter (who wrote slop contents by weight) was quite widespread and even present in prime-time magazines, but now AI tooling has exacerbated this approach. This is what is generally considered the enshittification of the web, and it started even before the AI hype, with content generated by extensive copy-and-paste and the addition of announcements, clickbait titles, sponsored articles, etc.

At the same time, the web search systems are also undergoing significant changes. Google introduced AI overviews, but people also changed their approach to searching for information, and that was not dependent on Google's or any other search engine's suggested overview. The possibility of having a structured summary of any argument, instead of a long list of well (or not so well) centered references, changed many people's views of the whole information search topic. Unfortunately, this also deeply impacts the overall sense of sponsoring a search engine or maintaining a site of content about any topic. For instance, why maintain a whole site about tourism in Berlin if the same information can be obtained in a short form via AI independently, and no one will visit such a site? And above all, how will content creators continue to monetize effectively in such conditions [1]?

If, as seems likely after Google I/O 2026, the next search engines will be simply AI overviews, mainly with sponsored results (typically by secretely steering AI summaries), what about independent and non-profit content? To be clear, already most traffic (I mean >90%) on small websites is bot-generated. Of course, that includes AI bots and general crawlers. The duration of such visits is typically under a few seconds. Of course, such a status is not a big problem for non-profit sites, but it can cause some frustration. That was true also before the autumn of 2022, indeed. What will be the final result of such a process is quite evident to me: the enshittificated, mechanical production of web content will go away because it will become only noise on the net, without any real revenues (or value); as it has started, it will surely go mostly to a dead end. Of course, until it can still capture a fraction of users' attention, it will stay here, but in my opinion, it will only be a matter of time before such low-profile content ends. What will remain is probably paywalled or institutional pages (only those with a decent value per se), non-profit/community websites, and AI-protected sites (with a continuous risk of abuse by new generations of autobots). Free access with announcements will become a thing of the past, as the number of active human readers declines. Mass production and poetry, to summarize.

Surely, easy monetization and SEO will soon be a keepsake. It has also been visible for ages in alternative media (such as video-based content), which is currently much less accessible to AI generation solutions. Even in such a domain, content creation has become more selective, and valuable assets are quite distinct from a more general, low-quality production. My idea is that, in the long run, most content creation (in any format, text, audio, or video) will follow a bimodal distribution (with low and high quality peaks) around its general quality, and the best quality will generally require some form of subscription, because of the involved efforts for production. Indeed, I would expect some concentration among a relatively few actors for any topics. Quality is neither spread nor democratic. One will need to exit the mass of low-quality profiles, which are and will be the majority of what is available out there on the web.

That’s already visible in the traditional mainstream media: most of their web-based content is pure garbage, and that was true even a few years ago; now it's paroxysmal. I found years ago that most of the so-called news on mobile devices was largely disseminated through announcements, dialogs, and sponsored content, making it completely unusable and unfocused, for me. Nevertheless, the mobile-first approach has already been the dominant UX for the average user for ages. Even the AI-generated content could largely become targeted to AI bots instead of humans, with unclear implications about readability and form. But the average user gets used to the most incomprehensible things, so who knows?

Therefore, the concrete perspective (or the crude reality) is a web full of AI-generated content or walled gardens, with few non-profit corners that publish mainly for fun, along with a few authoritative sources (such as Wikipedia [2], a knowledge source that will need to be defended and encouraged as well), which are becoming increasingly difficult to discover in the old way by humans.

We all become like modern Diogenes walking with a lantern on the net, during the daylight, looking for the true web value with mixed luck...

A giant step backward at a time when there were manually maintained indexes of interesting sites organized by topics. Damn it, sounds familiar. Not so bad, wasn’t it? That’s the core of the Fediverse, basically: some micro-universes oriented to small communities of focused users, all navigating in a global ocean of mere s*t.

References

The only good AI is a dead one: myth and reality of AI tooling for code

2026-05-05T13:00:00Z

Some months ago, I participated in this Mastodon poll. My thesis was that, in general, there is no presumptive quality flag that can be added to a product, whether it was created with AI-aided tools or not. My opinion sparked a small, heated controversy among some readers.

Labeling a product as AI-generated and expecting low-quality results is simplistic and prejudiced. One expects that the resulting product is accepted without review or handcrafted changes, after multiple adjustments to the LLM prompt through an iterative process. This is clearly false in general for coding (vibe coding, per se, is not a black-and-white picture; it is full of shades of grey), but it can also be applied to other creations.

Even the use of AI tooling has hundreds of nuances, especially in many articulated processes of creative production across multiple fields. AI tools or not, the human contribution is still central in the process. One can abdicate to such a role, or be fully responsible for the final result, with accurate changes and handcrafted work based on a rough draft generated by AI. The presumption of labeling AI helper use as a signal of low-quality production negates the importance of the human-in-the-loop. The point is that quality should be considered an objective aspect of any product, with or without human authoring: having a handcrafted product is not necessarily a symptom of quality per se, and the same goes for the opposite if the product used AI tooling at any phase of its creation. At least for programming, we had spaghetti code for ages, well before AI agents.

If you take a walk around GitHub and look at too many projects to enumerate, even without any AI intervention, you will find a lot of half-finished, incomplete, alpha-quality, obsolete, or partially working code that would need a good number of deep refactorings to be considered for production use. That’s not a problem with AI use; it’s simply due to the not-too-recent shift in FOSS coding as the mainstream approach to writing programs. Opening a GitHub portfolio assumed almost the same importance as opening a LinkedIn profile for techies. In many cases, such proof-of-concept products have been sitting on a developer’s shelf for years. Today, they populate their GitHub (or any other hub) repos, instead.

On the opposite side, one could read a recent Antirez’s post, which shows how much a meticulous human-in-the-loop approach for automatic programming can be productive and reasonable. Not secondary; such an approach should be currently considered essential to fully admit a copyrightable contribution to existing or new code, as explained in Simone Aliprandi’s recent book.

In conclusion, pretending that AI tooling produces only slop is clearly prejudicial, not different from past anti-FOSS prejudice that unpaid work done in free time cannot be of good quality. Does it sound familiar? Sure, there are a lot of low-quality projects out there, but again, that’s not necessarily the case, and there are also many very good FOSS projects, created and maintained with great care. Again, a license type and development workflow are not enough metrics to judge software quality, nor is the use of AI sufficient for the same purpose. And that’s true for coding as for other creative works. That’s not that simplistic, dudes.

Guess what? 97% of 3,456 respondents in the Mastodon poll answered that an AI mark on a product is a good idea for a presumptively low-quality design. I’m quite sure most of them are also AI users in some form, of course, and that says a lot about the future of this AI era and human ingenuity.

The Artificial Author: copyright and copyleft in the AI era

2026-04-30T11:00:00Z

I recently finished reading Simone Aliprandi’s second edition of a book I would recommend to many people interested in either authoring software and databases or making creative works. ‘The Artificial Author’, as its title suggests, deals with the role of generative AI in creative jobs seen from a legal point of view. This massive book seeks to shed light on a central yet complex issue that, in recent years, has affected many people, not only in the IT sector but also across many sectors of the creative industry.

As often happened in the past, technological changes largely anticipated society's ability to adapt to new developments, particularly in high-impact areas such as copyright, intellectual property, and privacy. Frankly, it is impossible to cover in this review all the aspects of Aliprandi's work that it touches on and explains. Of course, the book is purely informative, but it summarizes where we are currently, from the perspective of legal implications for code and other content generated by AI tooling. The topic is an open problem for several reasons, including the undeniable fact that copyright legislation and the legal systems vary from country to country. So, for instance, what can apply in the US needs to be reconsidered for Europe. Actually, a series of legal trials is still ongoing since the start of the main new AI wave in the autumn of 2022, and some of them have not been finalized or reached an out-of-court (and so off-record) settlement.

That’s significant in common-law systems like the US's, while in Europe, the whole process is much slower and settles based on principles and legislation, not specific trials. The questionable points are:

Is the whole training process for deep learning networks indeed legitimate under the fair use right? In most cases, it seems so, given the current state of things.
Who owns the AI-assisted outputs, and are they copyrightable? The safest answer is: it depends.
Should/could the AI outputs be considered derivative work? Moreover, if legally possible, should it be considered legitimate under any conditions?
If the outputs of independent prompts and refinement are somewhat similar, is there any condition of plagiarism?
Is there really any hope of a clean-room implementation, or even a fully original one, with AI tooling?

While it is clear that a fully AI-created work is not copyrightable under US law, the legal implications of a human-in-the-loop approach remain nuanced at this time. For sure, it seems that a simple prompt is not enough to claim rights on anything, and the whole process should be qualified by a significant human contribution. In the US, the meaning of copyrightable creative works implies involvement of skills, labor, and judgment by a person, and a simple prompt is simply not enough in most cases.

That also explains why, in some contexts, AI tooling should be considered with a grain of salt, and, for sure, the use of any AI-assisted contribution to co-authored/commissioned work should be clearly announced and stated as admitted: it could have future (if not current) impacts on authors' copyright claims.

Specific book sections also address recent European regulatory actions, as well as a general overview of pending and interesting litigations in the field in the European context. Indeed, the EU AI Act deals mostly with privacy.

I strongly suggest that interested people have a deep look at Simone’s book, because I have read too many naive claims here and there on the net about this matter. Of course, what is legally admitted could also be illegitimate or unethical, but prospects and past experiences (even considered in the book) are about future trade-offs and proper alignment, even for aspects such as laws and authors' expectations. For sure, this second edition will not be the last and definitive one for this book: we will see many sentences and regulations written in the near future, and the whole matter is in evolution, but it will still require years to settle.

AI training, copyright and the future of contents creation

2026-01-11T21:00:00Z

I have already addressed the implications of modern LLMs, specifically their training, in the context of copyright and licenses for both code and original content. A 'IANAL' disclaimer applies to this post, but my honest opinion is that such training is a legitimate type of reading and learning after study, unless explicitly excluded in licenses among the licensee's rights.

Following the exploitation of LLMs and the AI boom that began in 2022, several lawsuits and litigations emerged among multiple parties, with a few reaching a significant milestone through the first court rulings. Note that every country has a bit different regulations about copyright and fair use, so the current lawsuites could be only the starting point of a long list of legal actions.

While most of the current lawsuits seem to demonstrate that Anthropic or Meta had the right to use books bought (in paper or digital form) for LLMs training (on the basis of the fair use principle), the most problematic aspect instead is the apparent use of pirated books taken from LibGen and other known piracy websites, which - if confirmed - can result in potentially destructive damange for the companies, to compensante authors and pay fees in the order of hundreds of billions.

The same problems are present in the coding parts: again, using FOSS-licensed code for training could fall under fair use, but training using private codebases, as well as proprietary ones, could be equally destructive for the same companies, as well as for GitHub and Microsoft. The key point would be demonstrating, without any doubt, the unfair use of private or pirated content, of course.

Of course, I'm quite sure future licenses for FOSS codebases and documentation could include an explicit exclusion clause for AI training, which could jeopardize the legitimation of use even for future FOSS code. I would expect such a license change, as some projects already explicitly exclude AI-based contributions. My opinion about such a question is that it could represent shooting oneself in the foot, due to the pervasivity of AI tools among developers currently. Adoption of AIAD could represent a boost in development time if adopted with a healthy dose of skepticism (i.e., a human-in-the-loop approach). About that, I'm quite convinced of Linus Torvald's point of view: the point is not who writes the code, but who is technically responsible for it and ensures the required quality review and supervision.

Moreover, an implication of the current polarization in the AI hype is the future (present?) crisis of traditional web content providers. A symptomatic case is the StackOverflow crisis, which will, with high probability, lead to the end of the service as we know it in the near future.

That will have an impact on future AI training, too, for sure, because SO has been for years a huge source of knowledge about multiple fields in IT. What if fewer and fewer people will contribute to Wikipedia and general web content? What if more and more sources of information were to reserve the right to use their information for pure human-driven study? Knowledge has not been static in human history; AI models will need to continuously enrich their training sets and stay up to date.

It would be grotesque if the whole AI hype were brought to a halt by such copyright-based legal questions (even if I'm pretty sure a fully fair training would be possible now for such companies, who knows the impact of a more limited approach on the final result?). Surely, this seems the most serious threat to the future of such companies and the whole AI-based solutions.

The only true solution to such a threat is finally having a true open training model, which details sources and the whole process of training with full transparency, something that even the so-called open AI models are still far to be ready to provide.

References

This was for every one: about the crisis of the web

2025-12-25T15:30:00Z

I just finished reading the delightful book by Sir Tim Berners-Lee, titled This is for Everyone, published this year. It is a trip, long, almost 400 pages, about the origin and evolution of the World Wide Web, seen by those who conceived and pushed it from the start. The entire first part of the book is dedicated to the history of the web, the W3C, and the Web Foundation's operations as we have known them in the first 30 years of its development, from 1989 onwards.

I was there at the very beginning of the 90s: I was connected to the Internet since 1991, and reading such a book for a good part has been an emotional trip in my memory of those events and people. He is a visionary and an idealist who fought for an extended period to prevent his WWW creature from being intercepted and disrupted by for-profit interests.

It happened almost from the start, when first NCSA, then Netscape, and Microsoft tried one after the other to change the whole idea of openness into something proprietary, driven through the same scheme of embracing, extending, and extinguishing. In practice, the complete negation of standard and openness, with a clear goal in mind: obtaining users' lock-in into proprietary products, clearly for profit.

Tim provides evidence on multiple critical aspects of the current incarnation of the net as we know it today and over the last 20 years or more. They are both technical and social defects or drifts. The web is no longer what we learnt to know in its first years of existence. The start of the end of the original web concept was the mobile-first approach, which relegated the use of a regular computer to a second-class experience for most users. Most of the digital-native people never used a computer to access the network, and that user experience deeply affects the current vision of the web.

For years, nowadays, a browser has not been the main program for accessing content and services. Social networks are mostly not interoperable because companies have little interest in having their users leave the walled gardens of their apps. Using a browser and potentially exiting the company's services to access other servers and spaces is tolerated, but is perceived as damaging profits. That's simply because users are not users, but customers. The result is the shattered Internet about which I already wrote: the W3C standards are still relevant, but embedded in applications and frameworks that enrich and upset the user experience with proprietary workflows and extensions.

An emblematic case is Apple, which has, in practice, abandoned its WebKit engine and Safari browser in favor of apps and proprietary services to monetize customers and companies.

The concrete risk is that the whole web and its standards would become a marginalized component of the net, while most users are confined to walled-off realms of proprietary services and social networks. The recent AI innovation can mark the definitive end chapter of web content creation and search as we have used them over the last 30 years. More and more users will limit themselves to AI-provided overviews instead of collecting and consulting multiple sources of information and independent services. That will also have a concrete impact on revenues and interest in content creation and provision at large.

The second part of the book is fully dedicated to all such problems: the impact of social networks, the last few years of generative AI, the BigCo dominance, and includes all Tim's worries for the foreseeable future. He's an idealistic, optimistic, and positive guy due to his past experiences. However, he also has a good dose of sane realism. He understands that the path is nebulous and full of dangers (specifically, the AI path is highly polarizing and can hide multiple issues at many levels).

He sees in the indie web, and specifically in open and well-structured distributed standards (such as the ActivityPub protocol), a possible way to change the present and future by favoring interoperability and independence. A concrete proposal is the Solid standard for personal data wallets (or pods in Solid terminology) under complete user control for accessibility by third-party services. Such a standard is still in its infancy, but the true problem I see is the trustworthiness of involved parties, both companies and governments. Trusting is the key, and maybe we all individually lost such a superpower a long time ago.

Creating a corpus of rules to manage all such technologies and ensure ethical behavior can be a desperate illusion; the only concrete alternative would be to opt out, at the cost of exclusion from the social context (not only the digital one). But I agree there is no other way to recover the original idea of the web. The AI technologies are even more polarizing, among doomers and boomers, with a bumpy road ahead. For sure, open protocols and distributed multi-peer services are the inevitable starting point, but they won't be enough.

"It was not enough simply to release new technology and hope for the world to improve. You had to develop technology and society together. You really had to fight, in a principled and continuous way, for human rights. The web offered people a platform for their voices to be heard, reducing the cost of publishing and distributing information to effectively nothing. But, used improperly, it could also be turned into a tool of surveillance and control." (timbl)

References

Still, no silver bullet

2025-08-24T18:30:00Z

I recently re-read the seminal book by Fred Brooks about software engineering, entitled "The Mythical Man-Month" or MM-M for brevity. Specifically, I read the paper version of the 20th anniversary, which was revised and reprinted in 1995, after the first edition of 1975. I did that on purpose, firstly because it is always a fantastic read, and secondly to understand how much of its contents is still valid today, exactly thirty years later since its last revision.

Fred missed in 2022; otherwise, it would still be interesting to know his thinking nowadays after the LLMs boom and the birth of the AIAD (AI Aided Development) as a new revolutionary (or often seen as such) tool. Hi, Fred, wherever you are. It is worth mentioning that AI was already taken into consideration by Brooks at the time, even if limited to expert systems and other rule-based variants, which seemed promising and often sold as revolutionary before the mid-90s. A lot of the book's contents remained in the history of software engineering, including the famous Brooks' Law, and the whole book is still an excellent source of inspiration for any management and organization of complex intellectual projects (not necessarily limited to software systems), that heavily includes large teams of individuals.

One of the main theses of the latest book edition is that in the short term of 10 years from its proposition (the original essay was dated 10 years after the first edition of the book), he did not expect a silver bullet. That means no significant technological or managerial development was expected to be able to improve our productivity in programming by one order of magnitude. Ten years later, he confirmed the same idea, even considering exceptional tools like old-generation AI, visual programming, CASE tools, and so on. Is this thesis contradicted in 2025 by the existence of current AIAD tools, including chatbots, agents, and AI-empowered IDEs? My honest idea is no. I mean not now and not for the foreseeable future. The reason is exactly the same as Fred posed at the time. Reducing accidental problems in software creation (what AI is able to do) cannot be confused with the essential problems in software creation: the complexity of defining an articulated task, its analytical specifications, and an algorithmic solution to solve it. First of all, ignore the simplistic case of asking an AI engine to implement a very simple program. Here, the word simple means truly that. If you can specify a request by a whatever large manageable token context and formulate your request in terms of a brief question (let me suppose a question of some dozens of rows), well, that's probably an example of a simple (or dumb) problem. Too few, too easy. We are talking about a whole system that is generally difficult to describe, even in thousands of pages of specifications and documentation, written collectively by large teams of developers, architects, and domain experts.

The hard truth is that most of the real-world information systems out there cannot simply be specified in such a way. We are not able to define an unambiguous and complete enough specification to describe such systems, not to mention being truly able to write a complete and neat documentation of it, including its inner workings and use. We live in a deep illusion about that. The context size to get the required level of details to avoid bugs and ambiguities in specification would be impractical for current and even future tools, as well as for any humans. We would get in any case buggy (i.e., incomplete or misunderstood) results even if the AI engine were able to avoid hallucinations (which is not the case) and had no limitations for context size. The presence of AI hallucinations is only accidental in this regard.

In the current AI tooling, we are simply moving the complexity from the writing of a formal language step by step to using a natural language with a higher level of abstraction to express the problem. The complexity is still there, and it is inherent to the problem. Again, we resolved an accidental difficulty in a creative manner, not different from moving from assembly to using a modern programming language. Now the difficulty has moved elsewhere, but it is still there, and natural language is even more complicated to use compared to formal language. These difficulties translate into multiple refinements and trials to try to be more precise and get sensible answers and code in a continuous iteration. Isn't that so similar to the whole ordinary process of developing a program? In the most simplistic approach, such a process becomes vibe coding, and iteration could tend to infinity, with a forever loop. The smarter programmer for an easy task will do that in a reasonable (limited, hopefully) number of iterations, instead. Is that a significant improvement of one order of magnitude? I think not, as in most cases for the past. As in the case of high-level languages instead of assembly, they improved efficiency in coding as asserted in MM-M, but not by a whole order of magnitude. The AIAD is again another helper to solve accidental difficulties. The problem and all its complexity are still there. Thinking that we found the silver bullet is again (and again) an illusion or pure marketing.

So why do many CEOs insist on predicting a bright yet unlikely future of AI agents instead of having developers create applications? Brooks already wrote about that: there is a profound confusion in exchanging months and men, and an excess in optimism when approaching software development, even among techies, but that becomes paroxysmal among managers. None can seriously provide even a decent and reasonable evaluation of development time starting from incomplete, ambiguous, or vague specifications: the same simply happens systematically in overestimating the capabilities of current AI tools.

So what? AIAD is simply yet another tool among those available to developers, but the management problem of dominating complex projects is still there, with all its inherent difficulties. And the possibility to use natural language instead of a high-level formal one is only an apparent simplification of the process. It looks more familiar and easier, but it is also much more ambiguous, and the so-called prompt engineering is again a pure optimistic illusion, an euristhic approach to try to overcome our totally insufficient capabilities of dominating nuances and semantics.

Breaking dependencies on BigCos and a US centric IT world

2025-05-17T15:00:00Z

I recently read some interesting articles (see [1,2]) by Bert Hubert about IaaS and SaaS in the EU, which are generally considered cloud computing at large. He has quite a deep understanding of such topics, and the reading is enjoyable and triggered a few reflections.

The problem could be analyzed as a vast version of the indie web movement. Ensuring independence from a handful of big companies, all geolocated out of the continent and possibly subject to the inconstancies of a humoral government, as in current times, is a duty not only for individuals (who should also protect themselves locally), but also for whole countries.

First of all, it is evident enough that Europe is not that bad about infrastructure. In multiple countries on this continent, there are quite a few big companies that have nothing to envy, such as Amazon, Google, or Microsoft, for their capabilities and critical mass. There are already companies with multi-region data centres, a good level of automation, and high SLAs. Of course, they are mid-range companies, not monsters with country-size balances.

It is already perfectly possible [3] to depend on EU-based standard capabilities, including email services or file storage, which represent a primary part of common cloud services. What is truly missing is a capable enough set of web-based cloud personal productivity software based in Europe, which would be comparable to Google Workspace or Microsoft 365, including video conferencing and instant messaging.

Other important services could be Youtube equivalent, but what it is evident for me is that such kind of services are also available at small scale, what it is really missing is a sizeable financial effort to fund consistently projects that already exist in the FOSS/indie web ecosystem and the will of doing that instead of paying new consortia to develop from scratch some new solutions. Europe is full of brilliant people and companies that are just waiting for that.

As a personal example, by manual, at work, the central management recently abandoned the whole idea of maintaining fully on-premise systems to move some key services to the cloud for the entire national research network. Our non-specialistic needs were quite average profile: shared storage, email system, the usual personal productivity tools like Microsoft Office, and a teleconferencing/webinar system. The same could be enough to cover the digital needs of most of the companies and bodies out there in Italy. The result has been a national contract with Microsoft for MS365 and a more limited contract with Cytrix for GotoMeeting/Webinar. IMHO nothing is transcendental, something that could be implemented with a decent pumping of money to scale up a multi-datacenter on-premise solution to have full redundancy and an equally decent dedicated team, with many more possible features and capabilities available, at the end of the day. Maybe the only actual key point was the availability of MS Office, which is the only severe lock-in source for most users (and also why Google Workspace here has no hope of being considered). But even in the past, we paid a lot of money for desktop multi-licenses in any case, without any additional cloud solution.

I will not deal deeply with these incomprehensible dependencies on a single application: in my honest opinion, a lot of users are simply too lazy to refuse such a kind of lock-in, even if they depend on a very limited number of features of such an application. There are at least three different alternative desktop programs that most users could use successfully, but we still see Microsoft Office as the holy grail (and I would also add that its web version has an embarrassing UX).

Anyway, so what? That has been a precise abdication to autonomy of digital services and choices, whose consequence will be for sure visible in the future: loose of internal tech skills, missing investiments in FOSS alternatives, lack of human resources growing, and missed diversifications of solution providers (now both located in USA, not even Europe).

Seriously? We did not even have to externalize such services, only to reasonably invest in the right direction for additional human resources and infrastructure improvement instead of paying fees. In the last thirty years, I have not even seen a cent directly paid by my organization for FOSS projects used daily by tons of us, except for some rare fees for conference participation and sometimes indirect payments for people that incidentally worked on FOSS project during their daily job.

Let me be quite pessimistic about the actual intention of European bodies to find a concrete way of improving continental clouds, which could be perfectly viable instead. Until this moment, I have seen only an exaggerated capability of defining rules for the IT ecosystems that are not always sensed and also often misapplied. I saw instead a great lobbying capability by the well-known BigCos that have sustained their own interests and de-potentiated any past effort about this subject (hey, Gaia-X, yes, I'm talking about you).

Is this a lost war? I don't know, but I still don't see concrete signals of changes in European policies about digital innovation, except for a big regulation effort that does not change our full dependency on a handful of US companies. I have more hope in individual actions, but of course, as in the case of FOSS, they require a high level of awareness, which I still see in a limited measure: just compare the number of Mastodon accounts against Meta socials, TikTok, or Twitter/X ones. Maybe we are now at the same level of FOSS as about 30 years ago: a few visionaries and geeks see the problem and act, and most people will follow. Or at least, I hope so.

References

Digital communities, toxicity and other drifts

2025-02-08T17:56:00Z

In a previous post, I suggested that people should escape from big company-based social networks and find refuge in the Fediverse. The reason for that is simply to avoid being constantly considered a profitable customer, being profiled, and continuously bombed from advertising campaigns or sponsored posts. In brief, the purpose is returning to the original spirit of the big network of peers of the 90s.

Reading here and there on the Fediverse, I see that many people abandoned the well-known prime-time socials because of the diffused toxicity of such environments, censorship, and other bad personal experiences in their use. Unfortunately, the past examples of newsgroups and IRC channels showed that even Mastodon profiles or Matrix stanzas are not an answer for such drifts of digital life. The new Fediverse simply changed the user experience of communication services, not the core social experience of them.

Nothing is truly different between modern Fediverse services and groups, channels, or mailing lists of the old good days. Like it or not, we had trolls, spammers, and other strange beasts even in the 90s - when the men were men, to use an abused clause. Of course, the smaller the communities, the fewer the social problems of interaction among individuals in the digital world, and that's a fact of life. Therefore, a microblogging platform such as Mastodon could seem a great place to live digitally happy. IMHO, it is only a matter of time and critical mass (number of active accounts) before experiencing the same type of dynamics, unfortunately.

Of course, we had solutions to mitigate the problems that have been always the same in the last 30 years or more:

Defining netiquette and conduct codes.
Introducing community-driven pools of moderators with privileges to kick off pernicious individuals based on their behaviors and repeated violations of the conduct codes.
Never feeding the trolls.
Having a reasonable number of good bots to manage spammers and other harmful agents automatically.

Note that anonymity has never been a problem, so identifying users is not a solution and should not be considered in the equation. It does not work as a definitive deterrent, and those proposing such a practice are probably in bad faith.

That said, there is also a profound difference between a self-governed community with a set of rules chosen and defined by the community itself and censorship imposed by a company, a government, or any other external entities. This would be an excellent opportunity for the Fediverse to conjugate a non-toxic environment for users with a sane distributed network far from profit-only logic. It only needs to be caught by Fediverse communities.

Socials, they are not your home.

2025-01-20T17:00:00Z

Recently, I participated in a brief thread on Mastodon about how to maintain relations with people that have been built around a social network, specifically through Facebook. This is not different for Instagram, X/Twitter, TikTok or whatever you prefer.

I explained that this is simply not possible because, in my experience, people use multiple socials based on their age, technical experience, personal taste, and even the presence of other peers in any of the existing social systems.

This post explains in long form what I think about socials and, in brief, why you should not base your relationship life on any of them, including any serious business, of course.

In the last 30 or more years, a series of social networks appeared on the Internet with different characteristics, and all of them are (or have been until their closure) typically usable for free (as beer). Of course, they are pretty expensive toys, requiring a lot of servers, data centres, worldwide networks, software and human resources. As said briefly with a joke, if they are not selling you anything, you are the product.

The game is clear: they are profiling your personal data and preferences to create selective advertisement campaigns (included in the social network feed) if you are not paying a premium charge. That could happen even if you pay for a subscription, of course, but it is less disturbing, at least. Moreover, those networks also have been subject to data leaking from time to time, because of security issues or intentionally, and probably you would not appreciate that your personal data, telephone number, and the photo of your children/cats, or the photo of you drunk and naked in a party ten years ago walk publicly on the net.

If this is something you are not available to accept, avoid any not-so-free social network, plain and clean. Of course, any of your peers (family, friends, colleagues, any other) could have a different opinion about that. Any of them could choose one of the many social networks out there, and those networks leverage specifically the FOMO syndrome to collect and increase users/customers. If any of your friends are on Facebook or Instagram, you could be captured in the network easily because of that mass syndrome. The only way to escape is simply not playing that game.

A viable alternative is participating in modern independent networks of small community-based services, such as Mastodon for microblogging or Matrix for one-to-one communications and groups. Of course, they need to be sustained for cost coverage, and any instance can always disappear at any time because the admin(s) move to other interests or costs exceed what the admin(s) are available to pay at the end of the day. They are probably not long-term solutions, but one can always move from one instance to another when things turn down. Simply, do not rely too much on them. And probably they will not solve the problem of the leaking of photos of you naked and drunk in a party of ten years ago: shit happens even on those systems.

If your major interest is ensuring privacy and security, all the protocols and software of those distributed networks are purely FOSS, and you can always create your own instance. Of course, again, this is not something free of cost; you always have to consider computing resources (both cores and storage) and your time. This is not viable for people who lack the required skills and knowledge, but potentially, it is the only indisputable solution.

Unfortunately, after creating your own Mastodon/Matrix instance or moving to a nice maintained instance by a trustworthy party, you still have to convince your peers to participate in such a network, and that is the tricky part. The hard truth is that most people do not care about abdicating their freedom and participating in a social network as a customer. That is until the whole thing becomes a PITA because of censorship rules, excess of advertisements, moderation, and lack of active peers. That happened in the past for X/Twitter and will happen again for other social networks. It is a matter of critical mass: if the network is not large enough, you can miss a lot of your peers, and you can do exactly nothing to solve this problem.

That is the same problem you find in IM systems. For historical reasons, most of your peers have probably registered a Whatsapp account, much less a Telegram one. There are even fewer with a Discord account (not that better) or something less invasive and respectful of privacy, such as a Signal or Matrix account. The only valid reason is that WhatsApp started in 2009, Telegram in 2013, and Signal in 2014 and all of them, in one way or another, tried to maintain a user's lock-in or managed to solve scalability and add features since then.

One should ask why they all avoided systematically extending the existing XMPP protocol soon instead of re-inventing the wheel. I'm a bad guy and think that standardizing does not solve the problem of sustainability for such systems. They need to lock in the users to survive.

Think if you had to use a non-standard SMTP protocol to send emails in the 90s. That would have been an epic failure for the Internet tech community and users. Curiously, this is not true on the current shattered Internet, and this is the reason for the current social nightmare.

It's not too late: let such non-distributed and proprietary networks die as soon as possible; simply close your accounts or freeze them and move to something more standard, distributed and human-sized. Don't care about missing out on someone; they will come sooner or later if they share the same ideas, so why care? And if they do NOT share the same ideas, why care?

Come on, let's free ourselves of any social dependency on closed and proprietary networks.

And possibly, if you absolutely have to go around naked and drunk in the next party, at least avoid that people make photos of you and publish them.

Refurbish to fight against planned obsolescence

2024-09-25T18:30:00Z

The planned obsolescence of computers and other IT electronic equipment is a well-known plague of our age. For years, I stopped buying new computers and prefer refurbished ones whenever possible. That includes all my personal ICT boxes, and even at work, I try to spin out the life cycle of the equipment in use under my direct management. Proprietary OSes often limit the lifespan of IT equipment, but in some cases, vendor-independent FOSS software can replace the original one at End of Life (EOL). This is beneficial because FOSS software is often more lightweight, customizable, and has a longer support life, thereby extending the usability of your equipment.

For instance, I'm writing these notes on a dual-processor Lenovo Thinkstation C30 refurbished workstation that left the factory 10 years ago with plenty of RAM I bought 4 years ago. Thanks to the use of SSD storage instead of the old HDDs, I hope to use it for at least another 4-5 years. My living room Thinkpad L540 refurbished laptop is the same age, again with a replaced SSD, and I bought it in the same period. My main office personal HPZ320 workstation has been around for almost the same number of years, while my office laptop is a damn new Thinkpad X1 Carbon 5th-Gen of 2017. Both of them were new at buying time.

Of course, all of them run Debian GNU/Linux and have been upgraded regularly during the years. This is essential. Otherwise, the well-known proprietary OSes will obsolete your boxes, and you will be screwed. Generally, this is an easy task because reasonably aged computers are better supported by FOSS kernels. It would be better to avoid well-known vendors with problematic or unsupported devices.

I have even run a couple of aged Seagate Personal NASes in EOL for years, thanks to installing a plain Debian for ARMv7 processors distribution instead of the original Seagate one. I think they have been around for almost ten years, and one is a used unit. Of course, HDDs changed in the meantime.

Some servers still in use are the rock-solid IBM xSeries.They were born with a Suse Linux ES 11 and are still around and doing their jobs under Debian. Of course, the trade-off between power consumption, budget, and goals must be rigorously considered.

Plan for the future in advance

In order to run computers for a long time, I found it essential to buy with more RAM than needed at the moment of buying (even in the case of new boxes). You will need more, and assume you still don't know. Possibly, the same is true for the number of cores. If you buy a refurbished computer, it is inevitably a professional/business unit you would never find in a shop for home users. That's better because they generally have superior quality and decent support in the Linux kernel. In the business market, note that many companies retain computers for an extended guaranteed time only (by internal policy), so you will always find 3-5 years-old equipment recycled by medium/big companies. For personal use, they are more than enough and exceptionally usable with a FOSS OS.

Even note that current computers (but for GPUs) are comparable to reasonably old computers (let's say the last 10-12 years) in terms of the number of cores, speed of RAM, and bus throughput. They are faster, but not so much. Their average power consumption should be lower, but Moore's law is dead, sorry. So, buying new computers is quite pointless in most cases, and even worse if you purchase a consumer low-end computer for a limited budget. A refurbished box is generally the best option because it is cleaned, incorporates ad hoc changes (e.g., a new SSD for old units), is tested, and includes a one-year warranty by its vendor (generally, but just check before buying). Even the refurbished computer was at least an SOHO one, not a home product, so it is a much better option.

Be redundant, be safe

I never base my daily activities on a single box. At home and at work, I always have forklifts and replacements for emergencies. You cannot trust old (or even new) units, and not for sure in the long term. The same goes for parts such as HDDs or SSDs. Ça va sans dire that you need to take care of your data and backup with required redundancy, too.

Missions impossible

As said, the refurbishing possibility is minimal for GPUs and in some application domains. I'm not a gamer, but there are rumors about forced obsolescence every few years for commercial reasons triggered by games and vendors. Even for high-performance computing, any GPU before late 2014 is not more truly supported or usable. Again, it is partially a matter of hardware, but proprietary software, including SDKs, renders old GPUs obsolete.

Nowadays, the 2016 generations of GPUs with 8GB of VRAM are basically to be retired for many applications: that was the standard size at the time, but now vendors have decided that 8GBs or less is too few for any practical use. Too bad.

Smartphones are another area where planned obsolescence is the rule. The most expensive ones have 7 years of software support, but most can only be upgraded to a pair of major versions. Basically, you should change your phone every 3-5 years because security support is limited in time. But the average replacement cycle seems less than 3 years, anyway. Often, an older phone can still be used, but it is at risk for security support. Too bad, again.

The same happens for many so-called smart electronic equipment: having a box permanently connected to the network and missing any security support is generally a bad idea, and only a small minority of them can be upgraded to FOSS firmware. Cameras, TVs, routers, access points, and many other objects in our homes have a sort of implicit counter for end-of-life that often stops before the end of the hardware parts. You need to be very selective in equipment vendors.

In many cases - guess what? - such devices now run an embedded version of GNU/Linux that could be community-supported after the end of vendor support if the vendor provided enough information appropriately, which is rarely a possibility. In most cases, the vendor only has a public archive of third-party FOSS source packages, not the entire build system, so community support is not practically viable. Even any development documentation is usually totally missing, just to discourage people from following that path. In many cases, the devices include totally proprietary chipsets and drivers, so there is no way. That's even the reason why Android is an almost-open mobile operating system. Too bad, take three.

Will it change in the future?

In general, this battle was lost years ago. Expanding or repairing a laptop could now be challenging due to the accurate practices of many vendors to discourage self-intervention. That's true for a lot of other equipment, too. They are always ready to obsolete your products more often than you are prepared. I'm a pessimist about the future of this war.

They're coming outta the goddamn walls

frankie-tales

Is the future federated? Or, why the hyperscalers are here to stay

The problem is not only if, but how.

The Web is dying, long live the World Wide Web.

References

The only good AI is a dead one: myth and reality of AI tooling for code

The Artificial Author: copyright and copyleft in the AI era

AI training, copyright and the future of contents creation

References

This was for every one: about the crisis of the web

References

Still, no silver bullet

Breaking dependencies on BigCos and a US centric IT world

References

Digital communities, toxicity and other drifts

Socials, they are not your home.

Large social networks are an expensive game

The distributed small social networks can be a solution

Refurbish to fight against planned obsolescence

Plan for the future in advance

Be redundant, be safe

Missions impossible

Will it change in the future?