diff --git a/contributions/executable-tutorial/hanzhizh-bingjiez/README.md b/contributions/executable-tutorial/hanzhizh-bingjiez/README.md
deleted file mode 100644
index db6d7c308..000000000
--- a/contributions/executable-tutorial/hanzhizh-bingjiez/README.md
+++ /dev/null
@@ -1,49 +0,0 @@
-# Assignment Proposal
-
-## Title
-
-Observability with eBPF and FlameGraphs: Profiling Containerized Applications
-
-## Names and KTH ID
-
-- Hanzhi Zhang (hanzhizh@kth.se)  
-- Bingjie Zhao (bingjiez@kth.se)
-
-## Deadline
-
-- Task 3  
-
-## Category
-
-- Executable tutorial  
-
-## Description
-
-This executable tutorial demonstrates how to use **eBPF** for observability and performance profiling of containerized applications, combined with **FlameGraph visualization** to identify bottlenecks. Unlike traditional monitoring tools, eBPF allows dynamic tracing at the kernel level with minimal overhead, giving developers deep insights into system and application behavior.  
-
-The tutorial will guide users through the following scenario:
-
-1. **Baseline setup**: Run a simple containerized Python/Flask application and perform a stress test to generate system load.  
-
-2. **Traditional monitoring**: Use `top` and `strace` to show the limitations of conventional tools for observability.  
-
-3. **eBPF tracing**:  
-   - Use `bpftrace` and `bcc-tools` to trace syscalls (`execve`, `open`), file I/O, and TCP traffic of the containerized app.  
-   - Use `profile` sampling to capture CPU stack traces during load testing.  
-
-4. **FlameGraph visualization**:  
-   - Collect profiling data with `perf` or `bpftrace`.  
-   - Convert stack traces into folded format and generate an interactive `flamegraph.svg` using Brendan Gregg’s FlameGraph toolkit.  
-   - Observe which functions and code paths consume the most CPU time.  
-
-5. **Before vs After comparison**:  
-   - Show how traditional monitoring only reveals high-level metrics.  
-   - Demonstrate how eBPF + FlameGraph provides deep, actionable insights into performance bottlenecks.  
-
-The tutorial will be delivered on [KillerKoda](https://killercoda.com), using Linux playgrounds that support Docker, bpftrace, and perf tools.  
-
-**Relevance**
-
-Observability and performance profiling are critical aspects of DevOps and Site Reliability Engineering (SRE). This tutorial introduces students to modern, cutting-edge techniques using **eBPF**, which is increasingly adopted in production environments for performance debugging, security, and monitoring.  
-
-By combining eBPF with **FlameGraph visualization**, learners can bridge the gap between raw system-level tracing and intuitive performance insights, aligning with DevOps principles of continuous improvement and operational excellence.
diff --git a/contributions/feedback/hanzhizh-bingjiez/README.md b/contributions/feedback/hanzhizh-bingjiez/README.md
new file mode 100644
index 000000000..12ecdf0a1
--- /dev/null
+++ b/contributions/feedback/hanzhizh-bingjiez/README.md
@@ -0,0 +1,22 @@
+# Assignment Proposal
+
+## Title
+
+Feedback on executable tutorial:"Zero-Trust Data Pipelines: A Practical DevOps Security Tutorial"
+
+## Names and KTH ID
+
+- Hanzhi Zhang (hanzhizh@kth.se)  
+- Bingjie Zhao (bingjiez@kth.se)
+
+## Deadline
+
+- Task 3  
+
+## Category
+
+- Feedback
+
+## Description
+
+Link to the feedback [Zero-Trust Data Pipelines: A Practical DevOps Security Tutorial comment](https://github.com/KTH/devops-course/pull/2882#issuecomment-3380911246)
\ No newline at end of file