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  <title>Diomidis D. Spinellis Web Log</title>
  <link>https://www.spinellis.gr/blog</link>
  <description>The Internet soapbox of Diomidis Spinellis</description>
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  <dc:title>Diomidis D. Spinellis Web Log</dc:title>
  <dc:identifier>https://www.spinellis.gr/blog</dc:identifier>
  <dc:date>2004-08-20T18:00:00-03:00</dc:date>
  <dc:language>en</dc:language>
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    <title>Diomidis D. Spinellis Web Log</title>
    <url>https://www.spinellis.gr/dds.gif</url>
    <link>https://www.spinellis.gr/blog</link>
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  <item>
    <title>Thinking will become a hobby</title>
    <link>https://www.spinellis.gr/blog/20261008</link>
    <description>
 These lines are very difficult for me to write
because I feel like digging my own grave.
AI systems are improving by leaps and bounds.
From the early 2022 fumbling release of ChatGPT, which
couldn’t correctly count the number of a’s in my name
(it claimed two),
we reached OpenAI’s
 release of math papers 
where an internal AI model
solved many hundreds of previously open math problems.
Aside from philosophical arguments,
practical claims regarding the superiority of human thought,
on grounds such as hallucinations or bias,
increasingly appear to me like rearguard defence.
For the bulk of today’s cognitive work,
the writing’s on the wall:
AI will take over. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Thinking will become a hobby</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20261008</dc:identifier>
    <dc:date>2026-10-08T09:42:45-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>A controversial proposal for hallucinated references</title>
    <link>https://www.spinellis.gr/blog/20260817</link>
    <description>
 Many prestigious scientific venues have suffered from papers
containing hallucinated citations.
 GPTZero  reports finding
 100 hallucinations in NeurIPS 2025 accepted papers 
and
 50 hallucinations in ICLR 2026 submissions .
Hallucinated citations are references generated by an AI system that
appear credible but point to sources that do not exist or do not support
the claims attributed to them.
They may contain plausible-looking but incorrect authors, titles, journals,
dates, DOIs, or URLs, making them difficult to detect without
thorough verification.
Such citations, justifiably, undermine the confidence in
both scientific publications and in the process that produces them.
How should the scientific community address this issue? 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>A controversial proposal for hallucinated references</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260817</dc:identifier>
    <dc:date>2026-08-17T15:28:22-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Blockchain technology in 500 simple words</title>
    <link>https://www.spinellis.gr/blog/20260803</link>
    <description>
 A recent Financial Times long-read  article 
outlined how diverse financial
institutions try to promote the use of blockchain technology to optimize
how their transactions are performed.
This will allow them to take place instantly, rather than waiting for clearing,
around the clock, rather than during working hours, and with automated
actions, such as the rebalancing of a tracker fund when asset prices change.
Obviously this entails many risks.
Although the article tried to explain the basics of how blockchain technology
works, it left out many important elements.
Read on to learn the absolute essentials of blockchain technology
in fewer than 500 simple words. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Blockchain technology in 500 simple words</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260803</dc:identifier>
    <dc:date>2026-08-04T10:27:51-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Barings, Boeing, and Bots</title>
    <link>https://www.spinellis.gr/blog/20260715</link>
    <description>
 For decades the accepted management wisdom has been
for managers to delegate tasks and
for organizations to outsource activities that aren’t core to their operations.
Yet, when the proposed delegate or supplier is an AI agent, these
established practices are suddenly portrayed as irresponsible,
dehumanizing, or even immoral.
Much of this resistance has all the marks of a moral panic:
a novel technology is judged through its most alarming failures, its benefits
are discounted, and its use is treated as crossing a boundary rather
than as another management decision.
Here’s the thing: delegating work to an AI agent is neither inherently
wise nor inherently reckless.
As with human delegation and organizational outsourcing, what matters
is the task, the controls, and who remains accountable. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Barings, Boeing, and Bots</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260715</dc:identifier>
    <dc:date>2026-07-15T15:54:20-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Why agentic AI needs better experts</title>
    <link>https://www.spinellis.gr/blog/20260708</link>
    <description>
 Over the past few days I  changed 
the way the  uutils  project’s
 sed  program
handles data to default from characters to raw bytes.
This improves compatibility with GNU  sed  and also performance.
Given the change’s size and extent
(13 changed files, 1740 insertions, 609 deletions),
I worked with an AI agent (OpenAI Codex),
which allowed me to experience first-hand both its power and limitations. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Why agentic AI needs better experts</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260708</dc:identifier>
    <dc:date>2026-07-08T10:30:24-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Documenting AI-generated code commits</title>
    <link>https://www.spinellis.gr/blog/20260702</link>
    <description>
 With ever-more program code created through generative AI,
it is important to document its provenance.
In industry this can help
diagnose the root cause of problems discovered long after the code was written,
locate issues with a similar cause,
and evaluate the cost and benefits of AI.
In educational settings it can help students be honest, mindful, reflective,
and transparent regarding their use of generative AI
and provide educators with data they can use
to evaluate objectively student work.
In both settings, provenance information can guide a code review’s focus
because humans and AI  fail in different ways . 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Documenting AI-generated code commits</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260702</dc:identifier>
    <dc:date>2026-07-08T08:00:37-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Why reviewing AI-generated code is devilishly hard</title>
    <link>https://www.spinellis.gr/blog/20260523</link>
    <description>
 Here’s the thing: when working on code with GenAI assistance
(from a chat-bot, through IDE auto-completion, or, increasingly,
with an AI agent)
you need a better understanding of the system than when working without.
Cognitive psychology and the workings of large language models (LLMs)
give us four clues on why this happens. 
</description>
    <guid isPermaLink="true">https://www.spinellis.gr/blog/20260523</guid> <!-- Hardcoded site here -->
    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Why reviewing AI-generated code is devilishly hard</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260523</dc:identifier>
    <dc:date>2026-05-23T18:53:28-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Empirical software research in the age of AI</title>
    <link>https://www.spinellis.gr/blog/20260413</link>
    <description>
 In a keynote presentation at the 2026 Mining Software Repositories
Emerson Murphy-Hill, a star researcher at Microsoft, presented his
view on the role of an empirical software engineering researcher in the age of generative AI.
His talk focused on three themes: the durability, differentiation, and
dissemination of research. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Empirical software research in the age of AI</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260413</dc:identifier>
    <dc:date>2026-04-13T14:06:11-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Vibe coding toward the incident horizon</title>
    <link>https://www.spinellis.gr/blog/20260302</link>
    <description>
 We are living through a golden age of generative AI: a time when progress is both breathtaking and somehow still unable to reliably open a PDF without hallucinating the author’s middle name. The curve is real, the funding is real, and the demos are so real that they must be watched on a stage with dramatic lighting, because ordinary lighting reveals too much. The modern model does many things remarkably well—summarization, translation, code generation—and then it will confidently assert that 9 is a prime number “depending on your threat model,” which is how you know you’re witnessing history. 
</description>
    <guid isPermaLink="true">https://www.spinellis.gr/blog/20260302</guid> <!-- Hardcoded site here -->
    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Vibe coding toward the incident horizon</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20260302</dc:identifier>
    <dc:date>2026-03-02T16:44:31-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>An initial analysis of the discovered Unix V4 tape</title>
    <link>https://www.spinellis.gr/blog/20251223</link>
    <description>
 Several news outlets
 reported 
the  discovery of a 1970s Fourth Edition Research Unix magnetic tape 
at the University of Utah in July 2025 and its successful restoration.
This is a significant find, because up to now only
the Fourth Edition’s manual was thought to have survived.
Over the past few days I incorporated the tape’s source code into the
 Unix History Repository 
hosted on GitHub (see it  here )
and studied the code’s composition. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>An initial analysis of the discovered Unix V4 tape</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20251223</dc:identifier>
    <dc:date>2025-12-23T18:18:55-00:00</dc:date>
    <dc:language>en</dc:language>
  </item>

  <item>
    <title>Why I choose email over messaging</title>
    <link>https://www.spinellis.gr/blog/20250926</link>
    <description>
 My colleagues and friends know that I prefer to communicate
with them via email rather than chat messaging.
There are many benefits in such a choice.
You may want to consider them and adopt the same stance. 
</description>
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    <dc:creator>Diomidis Spinellis</dc:creator>
    <dc:type>Text</dc:type>
    <dc:title>Why I choose email over messaging</dc:title> <!-- Hardcoded site here -->
    <dc:identifier>https://www.spinellis.gr/blog/20250926</dc:identifier>
    <dc:date>2026-03-02T16:47:22-00:00</dc:date>
    <dc:language>en</dc:language>
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