October 19 - managers meet to recalibrate ratings aka decide which employees to throw under the bus with a needs improvement and target for layoff next year.
October 23 - managers meet to kickoff recruitment for new hires to replace old talent.
Tasks that should take days now take months due to knowledge loss but go on and keep doing what you’re doing GP&T enablement.
@f3
Getting rid of Robin would save 550 actual true workers. Vince could easily be replaced by Eliza with mortuary statistics and AI reduction logic.
When is AI coming for Senior Management positions? The company can save huge dollars if they let this happen.
Not a shock…. In the last 10 months, Treasury Services has let 4 product managers go who were legacy Mellon, all over the age of 50. I’m guessing Enablement will face the same fate.
Yep. My manager has already altered several of my stuff yo meet sr management requests for certain %’s. Its beyond bullshjt because they have zero clue what anyone does to do this sh-t and the people team is in on it. They gave reminders at mid year on how to rate so it hits the eoy quotas. I have that awesome sh-t in an email saved. as proof
AI assisted reformatting of a 5yr employee who joined with great expectations to lead and build a new eco system and now considering abandonment
The Dilemma of Institutional Knowledge and Tech Modernization at BNY
Engineers remaining in the legacy core are caught in a frustrating "no-man’s-land" as colleagues of similar seniority steadily abandon ship.
The Root Cause: AI Adoption vs. Domain Knowledge
BNY’s aggressive bet on AI has led to a sweeping reduction in Subject Matter Experts (SMEs). While AI certainly improves efficiency, it has introduced a critical knowledge gap:
The Loyalty and Skill Gap: Newer, younger talent—particularly offshore teams—are often driven by immediate career gains and AI exposure rather than long-term domain mastery. They operate without a deeper context of the underlying system mechanics. Hired g-ns is a loose way to describe them.
The "How" vs. "Why" Divide: Modern AI tools make the "how" easy. Re-engineering code, generating scripts, and optimizing execution speed are straightforward when backed by substantial capital. However, the "why"—the foundational business logic, architectural intent, and legacy decision-making—remains missing.
Knowledge Hoarding for Survival: The few veteran SMEs who retain this institutional knowledge often refuse to share it, viewing their unique context as their sole mechanism for job security. Those who do attempt to explain the system often provide fragmented, incomplete pictures, like blind men describing an elephant.
The Reality of the Legacy Infrastructure
Attempting to remediate systems after years of neglect and underinvestment is proving far more difficult than building a platform from scratch:
Fear of the Unknown: Engineers face massive black-box components. A core pipeline or data stream exists, but no one knows what business service it powers or what would break if it were altered. Consequently, leadership permits capacity scaling, but nobody dares to decommission or truly refactor the underlying code.
Resistance and Pace: While executive leadership has deep pockets and is willing to fund fixes, old-school practitioners cling to familiar paradigms and struggle to keep pace with modern technology. Conversely, the core business moves slowly due to heavy standardization.
Integration Pain and Wove: Migrating hundreds of institutional clients from deeply entrenched legacy systems to newer, nimbler platforms is an excruciatingly slow process. Because the newer systems are often built by teams lacking legacy domain context, they arrive bug-ridden and prove exceptionally painful to integrate. The shortcomings of platform initiatives like Wove can be directly attributed to these structural issues.
Potential Path Forward: A Clean Slate Strategy
Rather than continually patching a fragile environment, a complete rebuild may be the only viable engineering solution:
Raze and Rebuild: Completely demolish the legacy structure and build a nimble, modernized platform from the ground up, migrating clients sequentially.
Virtualization and Isolation: Leverage modern virtualization to present each client with a seemingly dedicated, customized environment, insulating them from shared multi-tenant complexity.
Conclusion
Engineers on the ground face a constant wall of roadblocks: vanishing SME domain knowledge, mounting client demands, and bug-plagued modern platforms. Without decisive intervention from senior management—moving away from high-level slide decks and vaporware toward genuine structural fixes—the easiest path for practitioners remains passive compliance: take the payout and eventually exit.
F/ck this place , when is next layoff
AI is coming for the majority anyways.
I made the original comment below (the first one). They want offshoring and young interns, contractors and folks who will only be here a short time- emphasis on young. India is king now. Even all my reporting is via India now.
@a4 damn, old deadwood is 40 now? I could see 60 or even 50 but 40 is a little wild lol
As a manager, I was literally ordered to “get rid of the old deadwood” (anyone over 40—!)