by Gary Mintchell | Jun 11, 2026 | Commentary, Leadership
I have appreciated Kevin Meyer’s thinking on Lean, manufacturing, leadership, and life for many years. He recently wrote on his blog:
Bob Sutton posted something on LinkedIn this week that stopped me mid-scroll. He was flagging a Brené Brown interview in the Financial Times, in which she described a troubling shift: leaders feeling a sense of relief and permission from the current political climate to be, as she put it, the assholes they’ve always been. Sutton, who literally wrote the book on this (The No Asshole Rule, 2007), has been tracking the organizational costs of toxic leadership for decades. The fact that he was amplifying Brown’s warning suggests they’re both seeing the same thing.
So am I, and it’s been bothering me.
And also, me. As an aside, Brown’s new podcast conversation with Adam Grant called The Curiosity Shop is my new favorite listen
Meyer points to Brown’s deeper meaning:
Brown’s framing is more precise than it might first appear. She isn’t saying the political climate is creating bad leaders. She’s saying it’s licensing them. Leaders who previously kept their worst instincts in check because social and institutional norms demanded it now feel liberated. The restraints have loosened. That’s a fundamentally different, and more dangerous, problem.
Ah, research from the PhD:
Sutton’s research makes the case against this directly. His concept of the “Total Cost of Assholes” is real and measurable: talented people leave, honest input dries up as psychological safety collapses, decision quality erodes. As he put it, “It takes numerous encounters with positive people to offset the energy and happiness sapped by a single episode with one asshole.” The “but he gets results” rationalization doesn’t survive contact with the longitudinal data.
How many of us have followed leaders from many walks of life who have seemingly build careers on character and morals only to be shown to have been deceived?
I can almost understand, not excuse but understand, a purely transactional leader who drops the character mask when the costs of wearing it exceed the benefits. Cynical, but at least internally consistent. What I cannot get my head around is the behavior of people who have spent careers, sometimes entire lifetimes, building identities around moral and ethical frameworks, often explicitly religious ones, and then abandon those frameworks the moment a convenient “end” appears on the horizon.
Character as relationship, not transaction.
But character works like a relationship, not a transaction. Anyone who has watched someone enter a marriage or a partnership convinced they can change the other person already knows how this ends. You don’t change people by accepting their worst behavior; you ratify it. And you signal to everyone watching that the behavior is acceptable, which is how norms collapse.
The harder path, the one that actually maintains what you claim to believe, is staying true to the principle when the shortcut looks most appealing. Especially then. And the irony is that the shortcut rarely delivers what was promised anyway. The downstream effects of tolerating poor character accumulate quietly at first, then loudly: institutional trust erodes, the culture coarsens, the people who care most either leave or go silent. What looked like a faster route to the goal has created an environment in which the goal is now harder to achieve, not easier, because the foundation it required has been eaten away.
He ends his essay much like I often do on my other blog—making it personal.
So the next time you find yourself excusing a leader’s behavior you would never accept from your own kids, your employees, or your friends, ask what that rationalization is actually costing. Not them. You.
by Gary Mintchell | Jun 8, 2026 | Commentary
I’ve been reading about the brouhaha over new owners and management at CBS and specifically 60 Minutes. I haven’t watched the program for more than 30 years. I haven’t a strong opinion about the journalists or the program.
When Mike Wallace was the lead guy, he practiced “gotcha” journalism. He’d set someone up then spring a trap question designed to throw the subject off guard and show how superior Wallace was. Even if I didn’t like the interview subject, I didn’t like the style. Quit watching—except for maybe Andy Rooney’s commentary, which was always thought provoking and a little off the wall.
Guess who copied the Mike Wallace schtick? President Trump. Remember early in this administration when he’d have a foreign leader visit, invite the press for what is always a smile and greet session, and then spring a trick question along the lines of “when did you stop beating your wife”? I still don’t like that style.
I became a magazine editor in my second career. I used to put people I was about to interview at ease by telling them I wasn’t Mike Wallace there to interrogate them. And smile. I wanted the latest technology and application news, not just to show someone embellishing marketing hype. That’s too easy. And not useful. All y’all can see through marketing hype—I hope.
New ownership and management comes with peril for writers. Check my pivot in 2013 from magazine to independent. At the level of network TV these days everything is political. The people there must learn to live with it or find an alternative. The tensions about trade press always revolve around treatment of advertisers or potential advertisers. (I once met PC Magazine contributing editor John C. Dvorak. Even in the 90s, PC Mag Editors’ Choice awards were influenced by advertising. Not surprised. I’ve seen it, too.)
Being independent means lower income, but I can pick. I truly respect the company that sponsors me. If I didn’t, I have FU money enough to walk away.
But for CBS and 60 Minutes, I’m glad I’m not there. Like they say, it’s the golden rule—those who have the gold make the rules.
by Gary Mintchell | Jun 3, 2026 | Commentary, Marketing
John Gruber at Daring Fireball pins the Meta strategy regarding more AR glasses:
Spitball: Meta’s entire business is predicated on knowing as much about people as possible. Their interest in building out a virtual “metaverse” world was motivated by the fact they could track everything people do, see, say, and hear there. That didn’t play out so they’re pivoting to building out devices that will let them track everything people do, see, say, and hear in the real world.
PSA: Do you log out after every visit to a Meta site? If not, it continues to track everyplace you visit and everything you do.
by Gary Mintchell | Jun 1, 2026 | News
AVEVA held a customer conference in Milan, Italy in May. I did not attend. They did publish several announcements. Some of these should not be surprising, since they were necessary to at least maintain pace with other industrial software companies. There was an acquisition announcement. I have expected something like that for some time without knowing who and when.
AVEVA has entered into an agreement to acquire TwinThread.
The proposed transaction represents a shared vision to advance industrial intelligence through the combined strengths of AVEVA’s data and analytics platforms and TwinThread’s AI, digital twin, and predictive analytics capabilities. The completion of the transaction remains subject to customary closing conditions, including regulatory approvals. Until that time, AVEVA and TwinThread will continue to operate as independent businesses and remain fully committed to delivering the same high level of service, innovation, and support our customers expect.
AVEVA and Snowflake Forge Strategic Collaboration
Partnership will enable direct, zero-code integration between CONNECT (AVEVA’s industrial intelligence platform) and Snowflake, removing data silos and accelerating time-to-insight across industrial enterprises.
AVEVA launches the first ever Industrial Intelligence Report with IMD Business School on Digital Ecosystems and the Future of Connected Industries
- The Industrial Intelligence Report reflects input from over 275 senior leaders across 12 industry sectors
- It demonstrates that organizations are seeking to construct digital ecosystems to confront higher-order business challenges, whether that is innovating faster, navigating supply volatility, or decarbonizing complex global operations.
- Yet the findings unearth a key paradox: while 74% of leaders consider digital ecosystems a top strategic priority, only 27% report sharing data extensively with ecosystem partners
AVEVA and IFS Announce Partnership to Advance AI-Powered Continuous Asset Decision Intelligence
AVEVA and IFS announced a technology partnership to enable complex industrial organizations to connect operational intelligence, enterprise execution and strategic capital planning. CEOs Caspar Herzberg and Mark Moffat shared the first wave of the collaboration at AVEVA World in Milan: Continuous Asset Decision Intelligence. This new solution is designed to turn real-time operational and asset data into smarter maintenance, investment and execution decisions across the integrated asset lifecycle. The benefit for customers is simple: less guesswork and timelier, evidence-based decisions.
AVEVA and Amazon Web Services Announce Multi-Year Strategic Collaboration to Accelerate Industrial Intelligence in the Cloud
The agreement brings AVEVA’s industrial software portfolio to AWS, enabling customers to design, operate, and optimize industrial assets with greater efficiency, lower cost, and AI-powered insights
Under the terms of the agreement, AVEVA will expand its CONNECT industrial intelligence platform on AWS, as part of its broader move to a multi-cloud architecture. By using services including Amazon Bedrock, Amazon Bedrock AgentCore, and Amazon Elastic Compute Cloud (Amazon EC2), AVEVA will deliver both public and private SaaS capabilities for industrial customers worldwide, accelerating this multi-cloud strategy and reinforcing AVEVA’s commitment to flexibility and scalability. The collaboration also encompasses listing AVEVA products on AWS Marketplace, joint customer migration programs, and a shared commitment to training and certification across both organizations.
by Gary Mintchell | May 19, 2026 | News
Voice interaction with our computing devices continues to become more powerful—and useful. Deepgram has been reaching out with a continuing stream of advancements to its Voice AI capability. (Now, if I could introduce them to Siri—but I digress.)
The TL;DR: One model, ten languages, and monolingual-grade accuracy for voice agents worldwide.
Deepgram announced April 29 the general availability (GA) of Flux Multilingual, expanding its conversational speech recognition model beyond English to support 10 languages, with the ability to automatically detect, understand, and switch languages dynamically within a single conversation in real time.
Pause here and reflect on that statement. That’s pretty powerful.
Developers, enterprises, and product teams building voice agents now have access to the first real-time conversational speech recognition model, delivering accurate turn-taking, interruption handling, low latency, and natural human-like conversations at global scale.
Traditional automatic speech recognition (ASR) is designed for transcription. Flux introduced a new approach, conversational speech recognition (CSR), built from the ground up to understand dialogue flow and enable real-time interaction. Flux has rapidly become foundational infrastructure for real-time voice agents, powering production systems that developers trust to deliver fast, natural conversational experiences with best-in-class accuracy in turn detection and speech recognition. Prior to today’s release, extending these experiences across multiple languages required stitching together multilingual transcription models, language detection, and routing logic, introducing latency, complexity, and brittle user experiences. Flux Multilingual replaces that complexity with a single model and API, making it possible to build conversational voice agents across 10 languages without re-architecting systems or sacrificing performance.
With native support for turn-taking, interruptions, and code-switching within a single interaction, voice applications remain fluid, responsive, and natural regardless of language or region. Flux Multilingual delivers monolingual-grade accuracy across languages. Developers can guide the model with language hints or let it auto-detect, adapting in real time even mid-conversation.
“Voice AI agents will soon become the default for how global enterprises interact with customers,” said Scott Stephenson, CEO and Co-Founder, Deepgram. “Today is a major step forward towards that future. Flux Multilingual gives developers a single perception model to build global voice agents, with the ability to switch language mid-call. Now, enterprises can deliver the same seamless experience to any customer, in any market. Deepgram is the leader in real-time AI infrastructure, and Flux Multilingual is the latest in our suite of capabilities that enables developers to deliver real-time products across the globe.”
“Customers told us that Flux transformed what’s possible for real-time voice AI agents in English,” said Omar Paul, Vice President of Products, Twilio. “It stood to reason that Deepgram would solve this globally too. Our customers’ teams no longer need to sacrifice accuracy with legacy multilingual systems, nor stitch multiple models with complex routing themselves. With Flux Multilingual, teams take the exact conversational experience they built for English and extend it across languages with a single system.”
Flux Multilingual Capabilities
Supported Languages
English, Spanish, French, German, Hindi, Russian, Portuguese, Japanese, Italian, and Dutch
Ultra-low latency conversational speech recognition, now global
Flux Multilingual is built for understanding and interaction, not just transcription. It uses model-based turn detection, not simple silence detection, to deliver accurate end-of-turn decisions in under 400 milliseconds, keeping conversations fluid and responsive across languages.
Monolingual-grade accuracy with real-time language control
Flux Multilingual delivers monolingual-grade accuracy across languages, with flexible real-time control through language hints or automatic detection, native code-switching, and dynamic adaptation as conversations evolve.
Build and scale global voice agents with one model
Flux Multilingual supports 10 languages in a single conversational model, enabling teams to build and deploy voice agents globally with one integration. One model, ten languages, one API, with no additional infrastructure or model orchestration required.
Key Features
- Native turn detection and interruption handling for natural dialogue flow
- Low-latency streaming transcription for real-time responsiveness
- Automatic language detection and language hint support for accuracy control
- Mid-session configurability for dynamic language adaptation
- Native code-switching within a single conversation
- Fully compatible with existing Flux API integrations
Flux Multilingual is now generally available (GA). As part of the launch, Deepgram is offering a limited-time promotional rate on streaming speech-to-text, including Flux Multilingual and Nova-3 models.
Flux Multilingual is available via Deepgram’s Cloud API or as a self-hosted deployment, with support for EU endpoints, SDKs, and seamless integration into voice agent architectures. Developers can get started today at deepgram.com or try Flux Multilingual directly in the Deepgram Playground.
by Gary Mintchell | May 18, 2026 | Business, Commentary, Marketing
John Gruber nails it in a recent Daring Fireball post. He refers to a news item quoting incoming Apple CEO John Ternus saying Apple has always shipped products, not technologies. Steven Levy writing in Wired ripped Ternus for not laying out a plan to ship AI. But AI is a technology. Apple will continue to add AI into products that we will find useful and enjoyable.
Check my preceding blog post about “Physical AI” humanoid robots at the upcoming Automate show. Looking at that market, A3 president Jeff Burnstein told me that the developers are throwing out a technology hoping users will find a use. The major AI companies are doing the same thing. Flailing around searching for a market to justify billion-dollar investments.
I was taught, and still believe, that product development means looking for potential user pain points and solving them with a product probably using the latest technologies.
