Uploaded March 2026 | Updated September 2026, 4 days ago
WebAssembly is usually framed as an application runtime story, but at AppWorld 2026 in Las Vegas, WebAssembly Unleashed shifts the spotlight to a more urgent frontier: data. As AI architectures get hungrier and more distributed, performance and security constraints are moving closer to the data store itself. In this episode, Joel Moses and co-host Oscar Spencer explore why WebAssembly components could become the connective tissue between data-intensive AI systems and the storage infrastructure that feeds them.
They’re joined by Ugur Tigli, CTO of MinIO, to break down how modern AI workloads stress storage in very different ways, from throughput-heavy training and RAG pipelines to latency-sensitive inference. Ugur explains why keeping GPUs fed is now an economic necessity, how MinIO optimizes for saturating networks, and how techniques like erasure coding and SIMD offload help keep CPU and memory overhead low across diverse hardware targets.
If you’re trying to understand where WebAssembly fits beyond the browser and beyond app logic, this episode offers a practical view of Wasm as a data-adjacent execution layer for real-world AI.
Chapters:
00:00 Welcome to WebAssembly Unleashed
00:44 Why WebAssembly must move “into data”
02:06 MinIO: S3-compatible, anywhere, enterprise-ready, AI data store
04:20 Real-world AI at the edge: GPUs, factories, and tight budgets
06:25 MinIO + WebAssembly packaging: portable storage components
07:19 AI storage workloads: training vs RAG vs inference (latency/throughput)
08:44 Keeping GPUs busy: the cost of idle + “Hadoop déjà vu”
09:59 How MinIO goes fast: erasure coding + SIMD + no metadata DB
13:37 Managing SIMD instruction sets with different architectures
15:40 Data takes the driver seat for application architecture
18:05 Edge-ready security: IAM policies, OIDC/LDAP, and KMS
19:33 Futurist hat: Wasm as on-prem Lambda + NIC/DPU offload
25:15 Agentic AI + component for Markdown
For more from F5's Office of the CTO visit the following sites:
Blogs - f5.com/company/octo
Reports - f5.com/services/resources/reports
Meet Your Hosts:
Joel Moses | linkedin.com/in/joelmoses | community.f5.com/users/joel_moses/398372
Oscar Spencer | twitter.com/oscar_spen | linkedin.com/in/oscarspen
Matthew Yacobucci | linkedin.com/in/matthew-yacobucci-323b4b2
⬇️⬇️⬇️ JOIN THE COMMUNITY! ⬇️⬇️⬇️
DevCentral is an online community of technical peers dedicated to learning, exchanging ideas, and solving problems - together.
Find all our platform links ⬇️ and follow our Community Evangelists! 👋
➡️ DEVCENTRAL: community.f5.com
➡️ YOUTUBE: youtube.com/devcentral
➡️ LINKEDIN: linkedin.com/showcase/f5-devcentral
➡️ TWITTER: twitter.com/devcentral
Your Community Evangelists:
👋 Jason Rahm: linkedin.com/in/jrahm | twitter.com/jasonrahm
👋 Buu Lam: linkedin.com/in/buulam | twitter.com/buulam
👋 Aubrey King: linkedin.com/in/aubreyking | twitter.com/aubreykingf5
👋 Chase Abbott: linkedin.com/in/chaseabbott1
WebAssembly is usually framed as an application runtime story, but at AppWorld 2026 in Las Vegas, WebAssembly Unleashed shifts the spotlight to a more urgent frontier: data. As AI architectures get hungrier and more distributed, performance and security constraints are moving closer to the data store itself. In this episode, Joel Moses and co-host Oscar Spencer explore why WebAssembly components could become the connective tissue between data-intensive AI systems and the storage infrastructure that feeds them.
They’re joined by Ugur Tigli, CTO of MinIO, to break down how modern AI workloads stress storage in very different ways, from throughput-heavy training and RAG pipelines to latency-sensitive inference. Ugur explains why keeping GPUs fed is now an economic necessity, how MinIO optimizes for saturating networks, and how techniques like erasure coding and SIMD offload help keep CPU and memory overhead low across diverse hardware targets.
If you’re trying to understand where WebAssembly fits beyond the browser and beyond app logic, this episode offers a practical view of Wasm as a data-adjacent execution layer for real-world AI.
Chapters:
00:00 Welcome to WebAssembly Unleashed
00:44 Why WebAssembly must move “into data”
02:06 MinIO: S3-compatible, anywhere, enterprise-ready, AI data store
04:20 Real-world AI at the edge: GPUs, factories, and tight budgets
06:25 MinIO + WebAssembly packaging: portable storage components
07:19 AI storage workloads: training vs RAG vs inference (latency/throughput)
08:44 Keeping GPUs busy: the cost of idle + “Hadoop déjà vu”
09:59 How MinIO goes fast: erasure coding + SIMD + no metadata DB
13:37 Managing SIMD instruction sets with different architectures
15:40 Data takes the driver seat for application architecture
18:05 Edge-ready security: IAM policies, OIDC/LDAP, and KMS
19:33 Futurist hat: Wasm as on-prem Lambda + NIC/DPU offload
25:15 Agentic AI + component for Markdown
For more from F5's Office of the CTO visit the following sites:
Blogs - f5.com/company/octo
Reports - f5.com/services/resources/reports
Meet Your Hosts:
Joel Moses | linkedin.com/in/joelmoses | community.f5.com/users/joel_moses/398372
Oscar Spencer | twitter.com/oscar_spen | linkedin.com/in/oscarspen
Matthew Yacobucci | linkedin.com/in/matthew-yacobucci-323b4b2
⬇️⬇️⬇️ JOIN THE COMMUNITY! ⬇️⬇️⬇️
DevCentral is an online community of technical peers dedicated to learning, exchanging ideas, and solving problems - together.
Find all our platform links ⬇️ and follow our Community Evangelists! 👋
➡️ DEVCENTRAL: community.f5.com
➡️ YOUTUBE: youtube.com/devcentral
➡️ LINKEDIN: linkedin.com/showcase/f5-devcentral
➡️ TWITTER: twitter.com/devcentral
Your Community Evangelists:
👋 Jason Rahm: linkedin.com/in/jrahm | twitter.com/jasonrahm
👋 Buu Lam: linkedin.com/in/buulam | twitter.com/buulam
👋 Aubrey King: linkedin.com/in/aubreyking | twitter.com/aubreykingf5
👋 Chase Abbott: linkedin.com/in/chaseabbott1
