You hit a bug.
AI: "That wasn't in scope."
Bro. You are the only one who has ever touched this codebase.
🔗 https://t.co/4ZyotaoE5Z
#AI#AIAgents#SoftwareDevelopment#GenAI
20 tech leaders on evaluating engineers:
Learning velocity matters.
But speed only pays off when it’s pointed at the right problem. Almost nobody interviews for problem selection.
https://t.co/4zXW38Yy8K
The companies that navigate this best won't be the ones adopting AI fastest.
They'll be the ones building AI fluency and systems depth simultaneously — instead of trading one for the other.
Full piece on what good engineering leadership does about it: https://t.co/o1P1UfXzNi
In the 1990s, the industry was certain mainframe developers were obsolete.
Today, 70% of global business transactions still run on mainframes.
The average COBOL programmer is 60 years old. Salaries: $121K–$150K.
The "dead" skill became irreplaceable.
Water cooling shows where this leads.
Standard knowledge in the '80s. Obsolete by 2010. Now Goldman Sachs projects liquid-cooled AI servers will go from 15% of deployments in 2024 to 76% by 2026.
The engineers who understand it? Suddenly very hard to find.
We are going live TODAY with a conversation we have been building toward all month.
Andy and Eric have been testing AI agent systems against real product specs, comparing notes on what works and what breaks - REGISTER BELOW!
https://t.co/HHThlkyrmq
There’s a gap between companies using AI—and actually understanding it.
Where does it help? Where does it break? Who owns it?
Register for our Live this Thurs, April 16 • 11am CT
https://t.co/CyvsXbyXRG
#AI#EngineeringLeadership#Discussion#Webinar
We put together a session on what AI is actually doing, and not doing, for companies like yours. It is about 40 minutes...
Check out "When Is It Time for a Major System Implementation — and When Is It Not?" below!
https://t.co/3bVpC71L4i via @YouTube
AI coding tools boost output 🚀
But they amplify your codebase.
Clean systems get faster. Messy ones get messier ⚠️
“The Brownfield Problem” explains why.
https://t.co/myW9iEKIuv
#AI#EngineeringLeadership#TechnicalDebt
At Inventive, we see it all the time: scaling tech isn’t a tooling problem ⚙️ it’s an enforcement problem 📏
Our CEO Andrew Siemer was featured in @ForbesCouncils:
“When compliance, security and cost controls are enforced through code, complexity becomes manageable.”
We were featured in @ForbesTechCncl discussing where reinforcement learning + human oversight works best.
On the factory floor, AI alone isn’t enough. Context matters. Operators matter.
That’s where real performance gains happen.
Check it out 👉 https://t.co/9yjVfozf9u
More data ≠ better decisions.
As visibility improves, hesitation often follows. Internal metrics lag markets, customers shift, and efficiency gaps widen.
Clarity comes from knowing what to trust and when to act 🎯
#DecisionMaking#Operations#DataStrategy#Inventive
AI won’t replace your workforce.
Another company that enables theirs might.
Check out what the data says, via our Forbes Technology Council article 👇
https://t.co/dMxcL2vNog
#AI#Leadership#Productivity#Inventive
☎️ Call us when...
your systems technically work, but progress feels slower than it should. ⚙️
Small changes feel risky.
Only a few people know how things really work.
That quiet friction is worth paying attention to.
#DigitalStrategy#PlatformHealth#Inventive
Most teams don’t fail at AI because the tech is bad.
They fail because they lock themselves in too early.
AI isn’t “set it and forget it.”
It’s infrastructure — build it like you plan to grow. 🚀
#automation#ai#Inventive
🎁 Year-end is a great time to sanity-check your digital experience—especially as accessibility & compliance expectations evolve.
Thinking about an accessibility or compliance review
DM us ⚡