r/AIgovernance

I have been playing with the local-LLM side of things, once Qwen3.8-27B dropped yesterday... Ofc i spent the initial hours bawling over the benchmark numbers 😅

But ofc while all the running the model is good... For someone like me (grad student), what happens after you've got the model running becomes less obvious...

By now the argument for "harness engineering" is really strong... Establishing that the durable engineering advantage may increasingly sit around the model, and that a better harness improves agent performance far more than simply swapping one good model for another.

Qwen3. 8-27B feels like a good example of why that matters.

Currently stacks like:

Model -> harness -> tools -> state/context -> permission -> eval -> deploy

I know I just wrote basic stuff😭

Me can figure out this stuff for 1 agent... But for people who actually get work done by locally running models or for companies that have 20,50,more agents:

How do u manage and version them?

How do u give each one scooped tool access?

How evaluate, and actually observe their actual actions after deployment?

How do u keep the whole thing manageable across machines/clouds?

I'm curious as to what ppl here are actually using for this parts.... Is the ans basically DIY stack around llama.cop+ Langgraph/OpenCode + own tooling or are the different llatforms for agent-infrastructure and control plane doing good?

I saw NVIDIA is going more runtime direction with NemoClaw and OpenHands has something on control plane, on ln I came across Lyzr and their no code control plane .... How much of those are branding and how much actual work?

Would like to know ur views

What kind of future job market will we have for AI governance roles? (Including feeder roles in privacy, risk, compliance, trust & safety etc). Hype, news, YouTubers, & growth statistics tell one story, but I wonder how it will actually play out.

Assuming AI capabilities increase 10x & then 100x, and we have fully agentic versions of systems like MS Foundry and Purview, how will there be enough AI governance jobs for everyone interested in it?
Yes, I know that as long as humans are control, there will always be governance roles somewhere.
But my question is more about supply and demand.
Will we see a job pipeline collapse like we saw with entry & mid-level cybersecurity roles?

Will this always be a scarce and niche job role dominated by those with legal and ML experience?
How do you think things will change?

Hi everyone,
I am looking to get certified in the **ISO/IEC 42001 Artificial Intelligence Management System (AIMS)**framework and am trying to decide between PECB and BSI Training Academy.
I’ve done some initial research, but I would love to hear from anyone who has taken courses through either academy, especially for this specific AI standard.
Here is my current dilemma:
PECB seems highly attractive because they issue official Credly badges, which would make it incredibly easy to share and verify my certification on LinkedIn and my digital resume. They also offer great self-paced eLearning flexibility.
BSI obviously carries massive legacy prestige as a National Standards Body and global registrar, which corporate employers highly respect. However, they don't seem to use the Credly ecosystem, relying instead on traditional PDF certificates and internal verification.
For those in the industry:
Does having the easily verifiable Credly badge from PECB give a noticeable edge in modern tech/AI job markets?
Or does the traditional corporate weight of BSI still trump digital badge convenience when it comes to hiring managers?
If you've taken the ISO 42001 track with either, how was the quality of the training material?
Appreciate any insights or personal experiences you can share!