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Spotlight: July 28, 2026
Published about 8 hours ago • 3 min read
The Weekly Dispatch
Top interviews from this week
Michael Bernzweig, Founder, Software Oasis
Reader
📍 Weekly Exclusive Interviews
This week’s Dispatch looks at the difference between using AI and using it well. Matthew Brown’s manufacturing insights show that not all AI matters, pushing manufacturers to focus on the applications that actually improve production and operational efficiency.
Brad Micklea’s security data makes the risk side just as clear, with AI incidents and attacks rising fast and forcing companies to strengthen defenses as AI spreads through enterprise systems.
Antonio Bustamante’s system-failure lens ties it together, arguing that the model is no longer the bottleneck; the surrounding system is, which makes visibility, auditability, and continual improvement the real work.
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As AI continues to evolve, companies like Wherefour Inc, led by experts like Matthew Brown, are at the forefront of leveraging this technology to optimize manufacturing operations. These AI Manufacturing Statistics 2026 reveal key insights into the strategic use of AI in production environments. “AI is everywhere these days, but as a lot of us know, not all of it necessarily matters.” — Matthew Brown, Expert, Wherefour Inc. The role of AI in manufacturing continues to evolve, offering new efficiencies and capabilities. Matthew Brown, founder and CEO of Wherefour Inc, shares how his company leverages AI to optimize production and enhance operational efficiency.
In the rapidly evolving field of AI security, understanding the latest statistics is crucial for industry leaders. Brad Micklea, with his extensive experience, provides a wealth of data on the current state of AI security. His insights are drawn from his work at Jozu and his previous roles at leading tech companies.
“AI incidents and attacks are rising even faster.” — Brad Micklea, CEO, Jozu. The data collected by Brad Micklea across various engagements reveals significant trends in AI security. The increase in AI incidents highlights the urgent need for robust security measures. Companies must adapt quickly to mitigate risks associated with AI integration. With AI's growing role in enterprise applications, security strategies must evolve to address new challenges.
In 2026, AI systems are becoming integral to enterprise operations, yet they face significant hurdles, particularly in maintaining accuracy and accountability. This article compiles comprehensive data from Antonio Bustamante's expert insights and leading research institutions to provide a nuanced view of AI system failures. “The model is not the bottleneck anymore. The system around it is.”
— Antonio Bustamante, Bem. In 2026, understanding AI system failures is crucial for enterprises. Antonio Bustamante, with his extensive experience in AI data interfaces, provides first-hand insights into the industry's challenges. His data, collected across numerous engagements, highlights the critical need for visibility, auditability, and system improvement.
Three themes stand out across manufacturing, security, and system design. First, AI in manufacturing is becoming practical and selective, with leaders separating useful automation from noise. Second, AI security is now a moving target, as rising incidents demand better monitoring and stronger guardrails. Third, system failures are increasingly about process, accountability, and instrumentation rather than model quality alone. Together, these trends point to a 2026 where operational discipline matters more than AI novelty.
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Get ahead in your B2B tech career. Top 3% SaaS, Consulting & Creators Community. Get our weekly industry research data, trends, and exclusive interviews to your inbox every Tuesday. Attend our free weekly educational webinars, and connect with peers in our global forum. Leading B2B Consulting & SaaS community. Founded 1998.
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