Recent Writings — Loren Kohnfelder

The NY Times teases a paywalled article, “A.I. won’t take all our jobs because it can’t reason like a human, Zeynep Tufekci writes.” linking to the article behind a paywall. Simply searching for [it can’t reason like a human, Zeynep Tufekci] provides a nice summary of the article, not only penetrating the paywall but also saving time and skipping the ads.

Neil Postman’s book, Amusing Ourselves to Death: Public Discourse in the Age of Show Business, is shockingly relevant today. He strips away the facade of mainstream media revealing its dark side and four decades later it’s all very recognizable as applicable today. Not only is it prescient, but making his points about the quaint legacy of now old school media makes everything very easy to follow, as well as demonstrating that today these same effects have kicked in orders of magnitude more so. Here are a few highlights but there is so much more in there.

In yet another breach of sensitive data (passports), Bruce Schneier makes a good point that using such powerful credentials as proof required for an unimportant purpose is the design flaw behind this operational snafu. This is the equivalent to the superintendent of a large apartment building giving the master key to someone who only needs access to a storage closet for a day.

TIL the origins of the concept of software waterfall development: it was first used to advise against the practice. There are a number of analogous examples of terminology for criticism being adopted by fans, either unaware or unswayed by the critic’s words.

The point of this fascinating story: now that we can vibe code there are all kinds of creative uses; and because these applications do not need the rigor that commercial software requires, prototyping “alpha” quality is no problem.

• The real AI; Is AI profitable?; Very Important Words the Tech Industry Ruined
• System modeling
• Guardrails?
• Anthropic sandboxing
• What’s a Virus?
• Threat model or triage guideline?
• Big Tech priorities

The real AI Seth Godin, based on Woz’s definition of “AI” (spoiler: Actual Intelligence).

• Anthropic Mythos: security superpowers?
• Threat model scope matters
• Anyone ready for quantum break in 2029?
• Trains with 5G windows and noise-cancelling cabins: only in Japan
• The NAND gate of continuous mathematics: all elementary functions from one operator

Anthropic holding back Mythos because they claim it has extraordinary powers to discover security flaws (whether the claims hold up or not) was a master marketing/PR move. It instantly made a big splash, generated great demand, and as a side effect it at least made the software security community wonder, “what if it’s true?” Naturally, there are all kinds of opinions, rebuttals, and reactions.

“AI” on my view is already and will certainly be a massive disruption to software in the coming years. Furthermore, we have an unprecedented wave coming that’s only just now beginning to break. Yet the biggest unknown, as I see it, is how the software community will respond, and that will be more due to social factors than purely technical. This is very much as it should be, however our very human frailties and limitations will inevitably drive how this unfolds.

• Google security methodology compendium
• Threat modeling
• Are attacks the only threat?
• Why is threat modeling ignored?
• Miscellaneous
• e16n next Stage 4

Google is sharing a lot of their impressive security methodology in a recent collection of articles: How Google Does It: An inside look at cybersecurity. Of special interest to me: Threat modeling, from basics to AI.

• On “the end of security bugs”
• STRIPPED
• Incident response threat modeling?
• Using CSS and PDF as emulators running code

Claude Code Security has people predicting the end of security bugs as we know them I can’t imagine anything in the forseeable future doing that because all software has bugs, and vulnerabilities are by definition a subset of all the bugs (in a properly designed system). Bug-free code seems computationally infeasible for large systems, if only for the amount of testing required to confirm there are no bugs. What am I missing, or is it AI hype?