Routine server-scale range
Operating behavior of a cross-region system Gevorg created.
M01 Media + speaking
Engineering systems have to survive contact with organizations.
Gevorg A. Galstyan is an engineering and data leader who shows technology executives how ownership, architecture, and incentives make complex systems expensive to change.
Built for conversations with
CTOtechnology executives
ENGengineering leaders
DATAdata and platform leaders
FOUNtechnical founders
M02 Practitioner evidence
An operating point of view, with the boundaries attached.
These records establish relevant experience. They are not presented as results from Gevorg's new advisory offer.
Peak request rate
The system remained functional during an AWS regional outage.
Remote-care platform
A platform result. Gevorg created the core system and later led the full development team.
M03 Signature topics
Start with a tension your audience already recognizes.
Each topic can stand alone or become part of a broader conversation about architecture, platforms, data, and engineering leadership.
Decision architecture
Decision Altitude
How to find the organizational layer where a consequential decision belongs, and why a technically sound choice can become expensive when ownership sits too high or too low.
Platform products
Stop Selling Kafka
Why shared infrastructure does not become a platform until teams can adopt a durable capability without inheriting the machinery behind it.
Data enablement
Data Enablement Is a Product
Why available data is not the same as usable data, how to treat internal consumers as customers, and which signals reveal adoption before lagging business metrics arrive.
Systems economics
Reversibility Before Standardization
How blast radius, switching cost, and the value of optionality should change architecture and platform decisions before an organization makes them difficult to reverse.
AI operating models
The AI-Native Off-Switch Test
A practical test for whether AI changes the product, operating model, ownership, and learning loop, or merely adds another feature and another dependency.
M04 Host-ready copy
Use the length that fits the format.
These bios are evidence-safe and ready for episode notes, event listings, introductions, and guest pages.
01Short introductionSpeaker intro · event listing
Gevorg A. Galstyan is an engineering and data leader who shows technology executives how ownership, architecture, and incentives make complex systems expensive to change.
02Standard bioPodcast notes · guest page
Gevorg A. Galstyan is an engineering and data leader working at the intersection of architecture, platforms, data, and organizational design. At Life360, he leads data enablement work and created a cross-region system that routinely scales from 10–20 servers to more than 2,000 and serves millions of requests per second at peak. Earlier, he created the core system for a remote-care platform and later led the full development team as the platform reached 5,000 daily active patients. Through Systems That Scale, he develops practical ways to diagnose ownership, capability boundaries, incentives, and the total cost of change.
03Full bioConference program · editorial profile
Gevorg A. Galstyan is an engineering and data leader focused on the decisions that make complex technical systems durable or expensive to change. At Life360, he leads data enablement work and created a cross-region system that routinely scales from 10–20 servers to more than 2,000, serves millions of requests per second at peak, and remained functional during an AWS regional outage. Earlier, he created the core system for a remote-care platform and later led the full development team as the platform reached 5,000 daily active patients. He has also co-founded a software engineering company and taught industrial economics to more than 200 students. Through Systems That Scale, Gevorg examines architecture through ownership, incentives, product value, reversibility, and economics. He is based in Canada, and his opinions are his own.
M05 Interview guide
Questions that lead to useful operating detail.
Choose a focused path or combine adjacent questions into a broader systems conversation.
- 01
What is decision altitude, and how can leaders recognize an altitude error?
- 02
When should repeated product code become a platform capability?
- 03
Why do technically sound systems become expensive before they visibly break?
- 04
Why do platform teams confuse availability with adoption?
- 05
Which signals show that a data capability is becoming useful and trusted?
- 06
What is the difference between an AI-enabled feature and an AI-native operating model?
- 07
How do incentives, constraints, and local optimization change the way you evaluate architecture?
- 08
What does a regional cloud failure reveal about architecture and operating ownership?
- 09
How can leaders reduce complexity without creating a central platform bottleneck?
M06 Host assets
The material needed to brief the conversation.
The kit uses a non-photographic Systems That Scale identity card. It does not present a graphic as Gevorg's portrait.
- Identity
- Systems That Scale brand card; no headshot supplied
- Bios
- Short, standard, and full
- Topics
- Five host-ready conversations
- One-sheet
- Download PDF ↓
- Location
- Canada
- Website
- galstyan.am ↗
- Selected work
- Evidence ledger ↗
- YouTube
- @GevorgGalstyan ↗
STS Systems That Scale
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