Welcome to Open Channels News, your go-to source for the latest insights on open source and digital innovation. In today’s episode, Robert Jacobi highlights the stories shaping technology and security right now:
Remembering Robert X. Cringely and the Human Side of Tech History:
Robert Jacobi looks back at the legacy of Mark Stevens, pen name Robert X. Cringely, who explained the personal computer revolution by focusing on the people, personalities, and the unpredictable moments that created the industry.
AI Inference and the Developer Feedback Loop:
Faster and cheaper AI inference is changing how developers build applications. Accessible, open-source AI models shorten the time from idea to working product, making iteration easier and spurring innovation beyond just having the smartest model.
WordPress Vulnerability Triggers Millions of Attacks:
A critical WordPress flaw went from public disclosure to millions of attack attempts within days. Attackers quickly adapted their methods, showing how automation and fast iteration now shape both cyber threats and defenses. Robert Jacobi stresses the need for immediate patching, thorough log reviews, and understanding your security posture.
Tune in as Robert Jacobi connects the dots between faster innovation, evolving cyber threats, and the importance of understanding what’s truly happening behind the technology.
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Takeaways
- Technology Evolves Rapidly: The pace of technological change is relentless, making it challenging to understand what is truly happening at any given moment, and history often reveals just how inaccurate previous predictions were.
- Personal Computing Revolution Was Driven by People: Cringely (Mark Stevens) focused on the human stories, personalities, and messy, unpredictable decisions that shaped the early personal computing industry, rather than just the products or technical achievements.
- AI Inference Speed Matters for Developers: The speed and cost of AI inference and how quickly and cheaply models can produce results, directly impacts the development cycle, making it possible for developers to experiment and iterate rapidly.
- Open Source Enhances Developer Agility: Open models, open tooling, and accessible infrastructure allow developers to test and experiment freely, reducing vendor lock-in and enabling a faster feedback loop.
- Security Threats Evolve as Fast as Technology: Attackers quickly adapt their approaches once vulnerabilities are disclosed and initial defenses go up, shifting tactics and exploiting automation and possibly AI to accelerate the pace of attacks.
- Patching Alone Isn’t Enough: While updating to the latest software versions is critical, it’s equally important to review logs, scan for malware, and understand if there was any compromise before patching.
- Speed Has a Double-Edged Effect: Faster iteration benefits both innovators and attackers, making the ability to quickly understand and adapt to new situations a crucial advantage, while still recognizing the need to pause and verify changes to maintain security and accuracy.
Mentioned Links and Resources
- Accidental Empires (Book by Robert X. Cringely) – Coverage on the formation of the personal computer industry and its leading personalities. (Note: the transcript says “Mark Stevens.” The author is Mark Stephens, who writes under the pen name Robert X. Cringely.)
🔗 https://en.wikipedia.org/wiki/Accidental_Empires - Triumph of the Nerds (PBS Documentary) – A documentary explaining how the personal computer industry came together, featuring key industry figures and insights.
🔗 https://www.pbs.org/nerds/ - All Things Open (Tech Conference) – Examining advancements in AI-accelerated inference for agile developers. (Note: I couldn’t match this description to a specific session or page, so this is the general site. The 2026 conference is October 19-20 in Raleigh.)
🔗 https://allthingsopen.org/ - MalCare (WordPress Security Platform) – Recorded over 3.18 million attack attempts on a recent WordPress vulnerability and offers ongoing security insights.
🔗 https://www.malcare.com/blog/wordpress-core-rce-attacks - Tech Business News (News Outlet) – Reported on the surge in WordPress vulnerability attacks protected by MalCare.
🔗 https://www.techbusinessnews.com.au/news/millions-of-attacks-target-critical-wordpress-vulnerability-as-exploitation-methods-shift/
Episode Transcript
Robert Jacobi:
Welcome to Open Channels News. I’m your host, Robert Jacobi. And it’s Monday, October 5th, 2026. Today we’re looking at 3 very different parts of technology. One of the people who helped explain the original personal computer revolution, what faster AI inference means for developers, and what happens when a WordPress vulnerability moves from disclosure to millions of attack attempts. And oddly enough, they all come back to the same thing. Technology moves fast. Understanding what is actually happening is the hardest part.
Our first story. I went down a bit of an internet rabbit hole looking for Robert X. Cringley, or is it Cringely? If that name means something to you, congratulations, you are probably of a certain technological age. Robert X. Cringely is the pen name most associated with technology journalist Mark Stephens. He wrote the book Accidental Empires and hosted the PBS documentary Triumph of the Nerds, which remains one of the better explanations of how the personal computer industry actually came together. And Cringely is interesting because he wasn’t really trying to write formal technology history. He was explaining the people. Steve Jobs, Bill Gates, Steve Wozniak, Paul Allen, Larry Ellison, the engineers, entrepreneurs, weird personalities, accidents, arguments, and decisions that eventually became an industry.
Even the name has a wonderfully messy technology industry history. Robert X. Cringely began as an InfoWorld persona used by multiple writers. Stephens eventually became the Cringely most people remember and continued using the name after leaving InfoWorld. What sent me looking again was Reddit and the surprising account of the affection people still have for Triumph of the Nerds and Accidental Empires decades later. And I think there’s a lesson in that. We tend to explain technology through products, the PC, the web, cloud, AI, but technology history is usually much messier. It’s people making bets with incomplete information, companies fighting over standards, somebody building something because they thought it was cool or interesting, which sounds especially like the AI industry right now. Sometimes the best way to understand where technology is going is to go back and look at how badly everyone understood where it was going the last time. Rest in peace, Mark Stephens.
Our next story. All Things Open is looking at AI-accelerated inference for agile developers. And there’s an important distinction here, because we spend an enormous amount of time talking about training AI models. Training is the expensive, glamorous part, with giant CPU clusters, billions of parameters, and datasets galore. Inference is what happens after that. It’s the model actually doing the work when your application asks it a question, generates code, analyzes an image, or runs an agent.
For developers, faster and cheaper inference changes something much more practical: the development loop. If using an AI model takes too long or costs too much, you treat it like a scarce resource. You design around it carefully. You batch requests. You hesitate to experiment. Make inference fast enough and cheap enough, and suddenly it becomes another component you can iterate against. Build something, test it, throw it away, change the model, so on and so forth. Sounds obvious, but it’s basically the same thing cloud computing did for infrastructure. You no longer have to buy the server before discovering whether the idea worked.
AI infrastructure is moving in the same direction. The interesting competitive advantage may not simply be who has the smartest model. It may be who gives developers the shortest distance between an idea and a working application. And that’s where open source matters as well. Open models, open tooling, and accessible inference infrastructure give developers more places to experiment without locking the entire application to one vendor. The model matters, but the speed of the feedback loop may matter just as much.
And finally, this is the less fun version of moving fast. Tech Business News reports that MalCare has now recorded more than 3.18 million attempted attacks targeting a critical WordPress vulnerability across sites protected by its network. The vulnerability affects WordPress versions 4.7 through 7.1.1 and was patched in 7.1.2 on September 22nd. The flaw involves unauthenticated path traversal in page template handling. Under certain server and theme configurations, an attacker could potentially get WordPress to include a readable PHP file outside the active theme directory, creating a path toward remote code execution.
That’s bad enough, but the more interesting part is how the attacks changed. MalCare says the early exploitation attempts were primarily delivered through URLs. Within days, a substantial share shifted toward requests that looked more like normal website form submissions. That’s the security aspect. Attackers don’t just discover vulnerabilities, they iterate. A firewall rule works? Change payload. Pattern gets blocked? Change delivery method. Something new gets disclosed? Automate the scanning and start looking for machines that haven’t been patched yet.
MalCare has suggested AI may be helping attackers modify their requests more quickly, though there isn’t any evidence proving AI caused this particular shift. And that distinction is important. We don’t need to blame AI for everything to recognize that automation makes iteration cheaper for both attackers and defenders. Don’t forget to update your WordPress to 7.1.2. Patching today does not tell you whether somebody got in, but it’s still good to prevent tomorrow. Review your logs, scan for malware, all the typical security things you need to do. It’s not just applying patches and stuff, it’s understanding what happened before you applied it.
And that brings us back to the beginning. Cringely documented an era where personal computing was evolving faster than most people could explain it. AI infrastructure is now compressing the time between an idea and working software, and attackers are compressing the time between vulnerability disclosure and mass exploitation. Faster is useful, but faster also means the feedback loops, good and bad, happen faster. So the advantage increasingly belongs to the people who can understand what is happening quickly, adapt quickly, and still know when to slow down long enough to verify it.
That’s it for today’s Open Channels News. I’m Robert Jacobi. Be open and stay secure.
