Tag: WebDev

The stochastic challengeTraditional software is predictable: Input A plus function B always equals output C. This determinism allows engineers to develop robust tests. On the other hand, generative AI is stochastic and unpredictable. The exact same prompt often yields different results on Monday versus Tuesday, breaking the traditional unit testing that engineers know and love.To ship enterprise-ready AI, engineers cannot rely on mere “vibe checks” that pass today but fail when customers use the product. Product builders need to adopt a new infrastructure layer: The AI Evaluation Stack.This framework is informed by my extensive experience shipping

The most expensive AI failure I have seen in enterprise deployments did not produce an error. No alert fired. No dashboard turned red. The system was fully operational, it was just consistently, confidently wrong. That is the reliability gap. And it is the problem most enterprise AI programs are not built to catch.We have spent the last two years getting very good at evaluating models: benchmarks, accuracy scores, red-team exercises, retrieval quality tests. But in production, the model is rarely where the system breaks. It breaks in the infrastructure layer, the data pipelines feeding it, the orchestration logic wrapping it, the retrieval systems grounding it, the downstream w

During Operation Lunar Peek in November 2024, attackers gained unauthenticated remote admin access — and eventual root — across more than 13,000 exposed Palo Alto Networks management interfaces. Palo Alto Networks scored CVE-2024-0012 at 9.3 and CVE-2024-9474 at 6.9 under CVSS v4.0. NVD scored the same pair 9.8 and 7.2 under CVSS v3.1. Two scoring systems. Two different answers for the same vulnerabilities. The 6.9 fell below patch thresholds. Admin access appeared required. The 9.3 sat queued for maintenance. Segmentation would hold."Adversaries circumvent [severity ratings] by chaining vu

The whale has resurfaced. DeepSeek, the Chinese AI startup offshoot of High-Flyer Capital Management quantitative analysis firm, became a near-overnight sensation globally in January 2025 with the release of its open source R1 model that matched proprietary U.S. giants.It's been an epoch in AI since then, and while DeepSeek has released several updates to that model and its other V3 series, the international AI and business community has been largely waiting with baited breath for the follow-up to the R1 moment.Now it's arrived with

Eighty-five percent of enterprises are running AI agent pilots, but only 5% have moved those agents into production. In an exclusive interview at RSA Conference 2026, Cisco President and Chief Product Officer Jeetu Patel said that the gap comes down to one thing: trust — and that closing it separates market dominance from bankruptcy. He also disclosed a mandate that will reshape Cisco's 90,000-person engineering organization.The problem is not rogue agents. The problem is the absence of a trust architecture.The trust deficit behind a 5% production rateA recent Cisco survey of major enterprise customers found that 85% have AI agent pilot programs underway. Only 5% moved those agents into production. That 80-point gap defines the security problem the entire in

For several weeks, a growing chorus of developers and AI power users claimed that Anthropic’s flagship models were losing their edge. Users across GitHub, X, and Reddit reported a phenomenon they described as "AI shrinkflation"—a perceived degradation where Claude seemed less capable of sustained reasoning, more prone to hallucinations, and increasingly wasteful with tokens. Critics pointed to a measurable shift in behavior, alleging that the model had moved from a "research-first" approach to a lazier, "edit-first" style that could no longer be trusted for complex engineering. While the company initially pushed back against claims of "nerfing" the model to manage demand, the mounting evidence from high-profile users and third-party benchmarks created a significant trust gap. Today,

After months of rumors and reports that OpenAI was developing a new, more powerful AI large language model for use in ChatGPT and through its application programming interface (API), allegedly codenamed "Spud" internally, the company has today unveiled its latest offering under the more formal name GPT-5.5.And to likely no one's surprise, it's hardly a "potato" in the disparaging sense of the word: GPT-5.5 retakes the lead for OpenAI in generally available LLMs, coming ahead of rivals Anthropic's and Google's latest public offerings, and even beating the private Anthropic Claude Mythos Preview model narrowly on one benchmark (essentially a statistical tie). "It’s definitely our strongest model yet on coding, both measured by benchmarks and base