Can Your AI Strategy Be Future-Proof? | Galileo’s Vikram Chatterji
And why AI can’t see gorillas.
Andrew and Ben open this week’s episode by dissecting why AI can't see a gorilla in a scatter plot, how big banks are stepping up to attract tech talent, and why focus is becoming the must-have resource for devs. Check out The Download below for links to the roundup.
Then, Vikram Chatterji, co-founder and CEO of Galileo, joins Andrew for a discussion on how engineering leaders can future-proof their AI strategy and navigate an emerging dilemma: the pressure to adopt AI to stay competitive, while justifying AI spend and avoiding risky investments.
To accomplish this, Vikram emphasizes the importance of establishing clear evaluation frameworks, prioritizing AI use cases based on business needs, and understanding your company's unique cultural context when deploying AI.
“Engineering leaders are stuck between a rock and a hard place. They know they need to experiment with AI to stay competitive, but they're under immense pressure to justify those costs.”
The Download
The Download maps your path to engineering greatness. 🗺️
1. Your LLM can’t see this gorilla, and that’s a problem 🦍
LLMs look at and understand data in different modalities than humans. And sometimes, it misses things that would be obvious to a human. A recent deep dive into LLMs shows they struggle with exploratory data analysis, failing to catch outliers and critical insights that humans spot instantly. In this case, it failed to see a literal gorilla depicted in a scatter plot. I found it interesting to learn why that is, check out the story below!
🔗 Read: Your AI Can’t See Gorillas
2. Banks are getting an edge in the developer talent war 🏦
For years, traditional finance firms lagged behind tech giants in hiring top engineering talent. As we’ve covered in recent weeks, that’s changing fast. Banks are rethinking their hiring strategies, offering remote flexibility, and embracing modern tech stacks to stay competitive. We’re seeing heavily-regulated industries like finance evolve to attract developers and adopt cutting-edge technology. Every company is about to become an AI company.
🔗 Read: How Banks Caught Up in the Battle for Developer Talent
3. The most valuable skill in an AI-driven world is focus 🎯
AI isn’t replacing engineers, it’s changing what makes them valuable. The real superpower in an age of automation isn’t knowing AI, but mastering deep, uninterrupted focus. Engineers who can cut through noise, manage cognitive load, and work on the right problems will outpace the majority in surveys who merely “use AI tools.” Want a future-proof career? Protect your focus like it’s production uptime.
🔗 Read: The Skill of the Future is Not ‘AI,’ but ‘Focus’
The 8 Habits of Highly Productive Engineering Teams 📈
Habits make or break engineering teams.
The 8 Habits of Highly Productive Engineering Teams is a practical guide packed with actionable advice and templates to help you build data-driven, durable habits. It covers:
☑️ Setting actionable team goals that align with business outcomes
☑️ Coaching developers to level up their skills
☑️ Using monthly metrics check-ins to unblock friction points
☑️ Running efficient sprint retrospectives that actually improve delivery
This isn’t just theory. These habits are battle-tested by top engineering leaders. Ready to level up your team’s productivity?
