Express YourSelf !

Reference https://www.meetup.com/collabnix/events/316301263/

1. Contain, Forecast, Adjudicate: Three Agent Controls No Protocol Gives You

https://www.nasiko.com/

2. Securing Your Agentic Stack (Workshop) 

https://agentic.dockerworkshop.com/

https://agentic.dockerworkshop.com/#/labs/securing-the-agentic-stack-slides

https://agentic.dockerworkshop.com/#/labs/securing-the-agentic-stack

1. What it contains? What is software Artifact

SBOM

docker scout sbom --format spdx --output baseline.spdx.json catalog-service:baseline

2. From where it comes from?

Provenience

3. CI pipeline. Who approve image with vulnerabilities? Can I. verify attestation source

https://docs.docker.com/scout/deep-dive/advisory-db-sources/

match with SBOM

Now AIBOM term is emerging. https://www.ajeetraina.com/ai-bom-explained-why-your-sbom-stops-where-your-ai-system-starts

VEX: Vulnerability Exploitability eXchange 

In Docker Desktop, we can filter vulnerabilities based on fixable or not

SLSA

Level 1 to 3

FIPS 140 For US

4. Can it be restricted? Sandbox  

We need base image with near zero vulnerabilities.

All images shall be signed

Allow coding agent only what it needs.

"/rc" in Claude. Remote control. You will keep getting notifications in your mobile. 

AI Agent

local sandbox and cloud sandbox. SBX is running on microVM. Agent can change kernel also. So SBX runs on microVM instead of container.

Inside mircoVM also we run Docker engine and docker daemon 

Docker Hub have MCP policy, AI policy

Now we have SBX compose file with policy

MCP Toolkit

Hardened MCP servers

https://agentic.dockerworkshop.com/#/labs/securing-the-agentic-stack-slides/workshop-75

Docker hub

DHI Docker Hardening Images

Images and AI models also on 

3. Docker sbx kits: you explorations to contain AI Agents begins here

AI Agent

https://docs.docker.com/ai/sandboxes/customize/

https://docs.docker.com/ai/sandboxes/customize/kits/

https://hub.docker.com/search?type=sbx_kit

Tools

1. MIXIN kit

It has enhanced capabilities

build agent from scratch

2. Sandbox Kit

-------

Kit has spec.yaml file

Files are payload. it can have docker compose file. certificate file etc. Some will go to sandbox and other files remain on laptop

start from Mixin kit, as Sandbox kit has many definition

Now let's have customize AI agent. 

https://floci.io/ is like localstack. Cloud emulators 

floci CLI is inside sandbox

1. create shell sendbox

2. run docker compose

same can be done with spec.yaml file

We have DHI for langchain also. It can be inside sandbox

4. Beyond the Agent: Building AI Systems You Can Trust

If it hallucinate then workflow has problem or model has problem? 

5. The New Primitives of AI: YAML, OCI, and Agent Infrastructure

you write agent in your Jupiter Notebook

"It works on my notebook"

"docker agent"

oci artifacts

I did not attend this event in-person. I gone through YouTube Playlist https://www.youtube.com/playlist?list=PLcWDDGrTp5AU It has 41 videos

In part 1, let me cover few of them

-------------------

1. Made in India. the founders behind API tools

• specmatic
• Beeceptor
• keploy.io
• postman
• bruno
• karate labs

------------------------

2. Restoring Trust in AI-Native development

Earlier we used to have Pre-commit hook before agent started coding. 

Now, SDD = spec driven development

Vibe coding was based on prompt

now spec is new source code

Harness engineering

1. Guides gives feedback to agent

2. Sensors for self-correcting loop

3. Executable intent

4. Executable architecture

5. Continuous Governance

------------------------

3. Death of API Management

The speaker is founder of "bunny and cloud" a collaborative development tool for humans and AI

https://bunnyandcloud.com/

He explain reasons. 

1. A New practices is emerging: Context engineering

A right context at right time for agent, so it can reason and act reliably. 

2. Agents are taking all management attention

AI GWs and context contracts extend API Management into agent governance. 

3. API Management does not get intent

But agent needs intent

We need to hard code and orchestrate the agents for different workflows. Agent does not think about workflow. 

4. APIs are relegated to the execution layer

Reasoning layer by LLM (Probabilistic) 

context layer by MCP and RAG

Execution layer (deterministic) 

5. The GW shift

Kong is decoupling API GW and AI GW

Portkey AI GW pioneer is acquired by Palo Alto Networks

AI GW enforce policy to every call to LLM, MCP, RAG

6. The tokenomics is replacing APInomics

7. Context Management includes managing APIs

Microcontext. Not DB dump. Agent shall receive smallest truthful slice of bounded context. 

8. From API endpoint Management to capabilities management

Agent Registries

Instead of DX, now we need AX (Agent eXperience) 

Context Management is new API Management

pillar 1: Identity and intent context

pillar 2: Business and domain context

pillar 3: Knowledge and evidence context (RAG) 

pillar 4: Execution and feedback context (MCP)

AI GW examples

1 Portkey AI GW

2 Kong

3 Truefoundry (someone added from the audience) 

The attack surface is different for AI GW. 

36. Skills and MCP

https://www.skills.sh/

API related classes / certifications

https://apimasters.io/