[OPS-AREA]Re: [nmrg] Re: [NMOP] Re: [OPSAREA @IETF126] IRTF/IETF OPS Transfer: Status & Exploring Coll aboration Opportunities

"Joe Clarke \(jclarke\)" <[email protected]> Thu, 25 Jun 2026 18:27:26 +0000
Newsgroups gmane.ietf.ops,gmane.ietf.opsawg
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Chongfeng, I mostly agree with everything you said.  That is, I have a simi=
lar understanding.  I do have a few comments, though, based on my implement=
ation experience.


Q1. Which AI agents capabilities are suitable for network management?
   A:   AI agents have the following common capabilities,

    - Perception: Processes multi-modal inputs (text, images, audio) and tr=
acks context and state over time.

[JMC] This depends on model.  Not all models can handle all types of input.=
  And the model capabilities will influence overall cost.

    - Planning & Reasoning: Breaks high-level goals into actionable sub-tas=
ks, dynamically re-plans when obstacles arise, and evaluates trade-offs bef=
ore acting.

    - Tool Use & Execution: Autonomously calls external tools=97search engi=
nes, APIs, calendars, code interpreters, and databases=97to take real actio=
n in the digital world (e.g., send emails, book flights, query data).

[JMC] More specifically, with network management, tools can access devices =
to get data and adjust configuration.  In the former, what the agent can th=
en do with the data it retrieves heavily depends on the model and its train=
ing data.  For example, many frontier models generally do well with basic n=
etwork operational data.  Adding on to tool use, RAG or purpose-trained or =
tuned models, and you can get even better results from such tools calls.

    - Learning & Self-Correction: Detects errors, reflects on outcomes, ite=
rates on solutions, and utilizes both short-term and long-term memory to im=
prove over time.

[JMC] This is where Digital Twin comes into place.  You don=92t necessarily=
 want a model to =93learn=94 as it=92s going through your production networ=
k.  Testing its =93reasoning=94 in a twin environment makes it safer for do=
ing that self-correction and iteration.

All the capabilities above are useful for network management. With the unde=
rground support of LLM models, the following functionalities can be realize=
d by AI agents in the context of network management,

   - Intent-based auto-assignment: Automatically routes NOC tickets based o=
n detected intent.

   - Intelligent root-cause analysis: Pinpoints fault origins with precisio=
n.

[JMC] Eh, maybe.  See above.  I=92ve had models go off the rails on hyper-s=
pecific problems where it didn=92t have a lot of relevant training data.

   - Actionable troubleshooting guidance:  Generates step-by-step plans and=
 recommended resolutions.

   - AI-driven orchestration:  Enables expert-human collaboration and autom=
ated execution of task reassignments/suspensions.

   - Continuous network optimization:  Delivers ongoing tuning recommendati=
ons for wireless, core, and cloud-network resources across diverse scenario=
s.

   - Automated recovery verification:  Validates fault resolution by queryi=
ng network and perceptual metrics via LLM-orchestrated API calls.

Q2. What is the impact of an AI network management process to YANG informat=
ion, service, network and data modelling?
    A:   AI and legcay network management models belong to different domain=
s,  the specific manangement modelling is aganostic to the AI network manan=
gent process. In other words, AI system can process any YANG information, s=
ervice, network and data modelling.

[JMC] This has exactly been my experience.  I=92ve had good luck with a YAN=
G-centric skill.  Where things can get problematic is the token consumption=
 XML and JSON produce when using open weight models with tighter context wi=
ndows.

Q3.  Is MCP (https://en.wikipedia.org/wiki/Model_Context_Protocol) a suitab=
le protocol between AI agents and IETF network management data sources and =
system components?
     A:  Yes, as an open standard that connects AI models to external data =
and tools, MCP enables AI assistants to securely read files, query database=
s, and execute actions across different applications.  The likelihood of MC=
P being used between between AI agents and IETF network management data sou=
rces and system components is very high.
In addition, other approaches can be used, such as APIs exposed by network =
controller, in this case, AI agents can call the APIs directly for network =
device configuration or data collection.

[JMC] Agree completely.  This does work well.  And MCP has considerable fra=
mework backing.

Q4, How does an AI agent interact with Network Digital Twin, Intent-Based N=
etworking, SIMAP, Knowledge Graphs and YANG data in Message Brokers?
  A:   It depends on the specific situation, there should be no one-size-fi=
ts-all solution.

[JMC] See above on a thought on digital twin.  And, yeah, I don=92t think w=
e=92ll have a one-size fits all model.

Joe

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rif; font-size: 12pt; color: rgb(0, 0, 0);">
Chongfeng, I mostly agree with everything you said. &nbsp;That is, I have a=
 similar understanding. &nbsp;I do have a few comments, though, based on my=
 implementation experience.</div>
<div style=3D"direction: ltr; font-family: Aptos, Arial, Helvetica, sans-se=
rif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
</div>
<div id=3D"mail-editor-reference-message-container">
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
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 black;">
<br>
</div>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">Q1. Which A=
I agents capabilities are suitable for network management?&nbsp; &nbsp;</di=
v>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;A:&nbsp; &nbsp;AI agents have the following common capabilities,&nbsp;</d=
iv>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; - Perception: Processes multi-modal inputs (text, images, audio) and tra=
cks context and state over time.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] This depends on model. &nbsp;Not all models can handle all types of i=
nput. &nbsp;And the model capabilities will influence overall cost.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; - Planning &amp; Reasoning: Breaks high-level goals into actionable sub-=
tasks, dynamically re-plans when obstacles arise, and evaluates trade-offs =
before acting.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; - Tool Use &amp; Execution: Autonomously calls external tools=97search e=
ngines, APIs, calendars, code interpreters, and databases=97to take real ac=
tion in the digital world (e.g., send emails, book flights,
 query data).</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] More specifically, with network management, tools can access devices =
to get data and adjust configuration. &nbsp;In the former, what the agent c=
an then do with the data it retrieves heavily depends on the model and its =
training data. &nbsp;For example, many frontier
 models generally do well with basic network operational data. &nbsp;Adding=
 on to tool use, RAG or purpose-trained or tuned models, and you can get ev=
en better results from such tools calls.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; - Learning &amp; Self-Correction: Detects errors, reflects on outcomes, =
iterates on solutions, and utilizes both short-term and long-term memory to=
 improve over time.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] This is where Digital Twin comes into place. &nbsp;You don=92t necess=
arily want a model to =93learn=94 as it=92s going through your production n=
etwork. &nbsp;Testing its =93reasoning=94 in a twin environment makes it sa=
fer for doing that self-correction and iteration.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">All the cap=
abilities above are useful for network management. With the underground sup=
port of LLM models, the following functionalities can be realized by AI age=
nts in the context of network management,</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; &nbsp;&nbsp;</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;- Intent-based auto-assignment: Automatically routes NOC tickets based on=
 detected intent.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;- Intelligent root-cause analysis: Pinpoints fault origins with precision=
.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] Eh, <i>maybe</i>. &nbsp;See above. &nbsp;I=92ve had models go off the=
 rails on hyper-specific problems where it didn=92t have a lot of relevant =
training data.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;- Actionable troubleshooting guidance:&nbsp; Generates step-by-step plans=
 and recommended resolutions.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;- AI-driven orchestration:&nbsp; Enables expert-human collaboration and a=
utomated execution of task reassignments/suspensions.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;- Continuous network optimization:&nbsp; Delivers ongoing tuning recommen=
dations for wireless, core, and cloud-network resources across diverse scen=
arios.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;- Automated recovery verification:&nbsp; Validates fault resolution by qu=
erying network and perceptual metrics via LLM-orchestrated API calls.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p;&nbsp;</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">Q2. What is=
 the impact of an AI network management process to YANG information, servic=
e, network and data modelling?</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; A:&nbsp; &nbsp;AI and legcay network management models belong to differe=
nt domains,&nbsp; the specific manangement modelling is aganostic to the AI=
 network manangent process. In other words, AI system can process
 any YANG information, service, network and data modelling.&nbsp;&nbsp;</di=
v>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] This has exactly been my experience. &nbsp;I=92ve had good luck with =
a YANG-centric skill. &nbsp;Where things can get problematic is the token c=
onsumption XML and JSON produce when using open weight models with tighter =
context windows.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">Q3.&nbsp; I=
s MCP (https://en.wikipedia.org/wiki/Model_Context_Protocol) a suitable pro=
tocol between AI agents and IETF network management data sources and system=
 components?</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; &nbs=
p; &nbsp;A:&nbsp; Yes, as an open standard that connects AI models to exter=
nal data and tools, MCP enables AI assistants to securely read files, query=
 databases, and execute actions across different applications.&nbsp;
 The likelihood of MCP being used between between AI agents and IETF networ=
k management data sources and system components is very high.&nbsp;</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">In addition=
, other approaches can be used, such as APIs exposed by network controller,=
 in this case, AI agents can call the APIs directly for network device conf=
iguration or data collection.&nbsp;</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] Agree completely. &nbsp;This does work well. &nbsp;And MCP has consid=
erable framework backing.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">Q4, How doe=
s an AI agent interact with Network Digital Twin, Intent-Based Networking, =
SIMAP, Knowledge Graphs and YANG data in Message Brokers?</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing">&nbsp; A:&n=
bsp; &nbsp;It depends on the specific situation, there should be no one-siz=
e-fits-all solution.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr;">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
[JMC] See above on a thought on digital twin. &nbsp;And, yeah, I don=92t th=
ink we=92ll have a one-size fits all model.</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
<br>
</div>
<div class=3D"ms-outlook-mobile-reference-message skipProofing" style=3D"di=
rection: ltr; font-family: &quot;&amp;quot;Aptos&amp;quot;&quot;, Arial, He=
lvetica, sans-serif; font-size: 12pt; color: rgb(0, 0, 0);">
Joe</div>
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