[OPSAWG]Re: [nmrg] Re: [NMOP] Re: [OPSAREA@I ETF126] IRTF/IETF OPS Transfer: Status & Exploring Collabor ation Opportunities
<Thomas.Graf-Zc0CTiu5wcBWk0Htik3J/[email protected]> Thu, 9 Jul 2026 06:46:31 +0000
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--===============3567560108038137250== Content-Type: multipart/signed; protocol="application/pkcs7-signature"; micalg=sha-256; boundary="----=_Part_217833_96794165.1783579595390" Content-Language: en-US ------=_Part_217833_96794165.1783579595390 Content-Type: multipart/alternative; boundary="_000_ZR1P278MB11705083FFE0BF2061C9EE1B89FE2ZR1P278MB1170CHEP_" Content-Language: en-US --_000_ZR1P278MB11705083FFE0BF2061C9EE1B89FE2ZR1P278MB1170CHEP_ Content-Type: text/plain; charset="us-ascii" Content-Transfer-Encoding: quoted-printable Dear Joe and Chongfeng, Catching up on this conversation and thanks for sharing your thoughts and c= ommenting. What you are describing making very much sense to me. Regarding: 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't think we'= ll have a one-size fits all model. [TG] My biased view is that a Network Digital Twin is helpful in context of= Planning & Reasoning where Intent-Based Networking, SIMAP and Knowledge Gr= aphs in context of Learning & Self-Correction. I see the YANG schema and se= mantics in the YANG schema registry (https://datatracker.ietf.org/doc/html/= draft-ietf-nmop-yang-message-broker-integration-13#section-4.4) and in the = Streaming Catalog (https://datatracker.ietf.org/doc/html/draft-ietf-nmop-ya= ng-message-broker-integration-13#section-4.5) in Message Brokers as a sourc= e of information for the RAG (Retrieval-Augmented Generation) and identifyi= ng from which Message Broker topics which YANG data should be consumed from= , which Chonfeng lists under Tool Use & Execution. What are your thoughts? Does that make sense? Best wishes Thomas From: Joe Clarke (jclarke) <[email protected]> Sent: Thursday, June 25, 2026 8:27 PM To: Chongfeng Xie <[email protected]>; Graf Thomas, SCS-INI-NET-VNC-E2= E <Thomas.Graf-Zc0CTiu5wcBWk0Htik3J/[email protected]>; ops-area <[email protected]>; opsawg <opsawg@= ietf.org>; nmop <[email protected]>; [email protected] Cc: [email protected] Subject: Re: [nmrg] Re: [NMOP] Re: [OPSAREA@IETF126] IRTF/IETF OPS Transfer= : Status & Exploring Collaboration Opportunities Be aware: This is an external email. 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-search engine= s, APIs, calendars, code interpreters, and databases-to take real action 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't necessarily w= ant a model to "learn" as it's going through your production network. Test= ing its "reasoning" in a twin environment makes it safer for doing that sel= f-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've had models go off the rails on hyper-spe= cific problems where it didn't 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've had good luck with a YANG-= centric skill. Where things can get problematic is the token consumption X= ML and JSON produce when using open weight models with tighter context wind= ows. 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't think we'= ll have a one-size fits all model. Joe --_000_ZR1P278MB11705083FFE0BF2061C9EE1B89FE2ZR1P278MB1170CHEP_ Content-Type: text/html; charset="us-ascii" Content-Transfer-Encoding: quoted-printable <html xmlns:o=3D"urn:schemas-microsoft-com:office:office" xmlns:w=3D"urn:sc= hemas-microsoft-com:office:word" xmlns:m=3D"http://schemas.microsoft.com/of= fice/2004/12/omml" xmlns=3D"http://www.w3.org/TR/REC-html40"> <head> <meta http-equiv=3D"Content-Type" content=3D"text/html; charset=3Dus-ascii"= > <meta name=3D"Generator" content=3D"Microsoft Word 15 (filtered medium)"> <style><!-- /* Font Definitions */ @font-face {font-family:"Cambria Math"; panose-1:2 4 5 3 5 4 6 3 2 4;} @font-face {font-family:Calibri; panose-1:2 15 5 2 2 2 4 3 2 4;} @font-face {font-family:Aptos;} @font-face {font-family:"Trebuchet MS"; panose-1:2 11 6 3 2 2 2 2 2 4;} /* Style Definitions */ p.MsoNormal, li.MsoNormal, div.MsoNormal {margin:0in; font-size:12.0pt; font-family:"Aptos",sans-serif;} a:link, span.MsoHyperlink {mso-style-priority:99; color:#467886; text-decoration:underline;} span.EmailStyle19 {mso-style-type:personal-reply; font-family:"Trebuchet MS",sans-serif; color:#0E2841; font-weight:normal; font-style:normal;} .MsoChpDefault {mso-style-type:export-only; font-size:10.0pt; mso-ligatures:none;} @page WordSection1 {size:8.5in 11.0in; margin:70.85pt 70.85pt 56.7pt 70.85pt;} div.WordSection1 {page:WordSection1;} --></style> </head> <body lang=3D"DE-CH" link=3D"#467886" vlink=3D"#96607D" style=3D"word-wrap:= break-word"> <div class=3D"WordSection1"> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US">Dear = Joe and Chongfeng,<o:p></o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US"><o:p>= </o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US">Catching up on this conversation and thanks for sharing your thou= ghts and commenting. What you are describing making very much sense to me. Regarding: <o:p></o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US"><o:p> </o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US">Q4, H= ow does an AI agent interact with Network Digital Twin, Intent-Based Networ= king, SIMAP, Knowledge Graphs and YANG data in Message Brokers?<o:p></o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US"> = ; A: It depends on the specific situation, there should be no o= ne-size-fits-all solution.<o:p></o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US"><o:p>= </o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US">[JMC]= See above on a thought on digital twin. And, yeah, I don’t thi= nk we’ll have a one-size fits all model.<o:p></o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US"><o:p>= </o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US">[TG] My biased view is that a Network Digital Twin is helpful in = context of Planning & Reasoning where Intent-Based Networking, SIMAP and Knowledge Graphs in context of Learning & Self-C= orrection. I see the YANG schema and semantics in the YANG schema registry = (<a href=3D"https://datatracker.ietf.org/doc/html/draft-ietf-nmop-yang-mess= age-broker-integration-13#section-4.4">https://datatracker.ietf.org/doc/htm= l/draft-ietf-nmop-yang-message-broker-integration-13#section-4.4</a>) and in the Streaming Catalog (<a href=3D"https://datatracker.ietf.org/doc/= html/draft-ietf-nmop-yang-message-broker-integration-13#section-4.5">https:= //datatracker.ietf.org/doc/html/draft-ietf-nmop-yang-message-broker-integra= tion-13#section-4.5</a>) in Message Brokers as a source of information for the RAG (Retrieval-Augmented Genera= tion) and identifying from which Message Broker topics which YANG data shou= ld be consumed from, which Chonfeng lists under Tool Use & Execution.<o= :p></o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US"><o:p> </o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US">What are your thoughts? Does that make sense?<o:p></o:p></span></= p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US"><o:p> </o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US">Best wishes<o:p></o:p></span></p> <p class=3D"MsoNormal"><span lang=3D"EN-US" style=3D"font-size:10.0pt;font-= family:"Trebuchet MS",sans-serif;color:#0E2841;mso-fareast-langua= ge:EN-US">Thomas</span><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:gray"><o:p></o:p></span></p> <p class=3D"MsoNormal"><span style=3D"font-size:10.0pt;font-family:"Tr= ebuchet MS",sans-serif;color:#0E2841;mso-fareast-language:EN-US"><o:p>= </o:p></span></p> <div> <div style=3D"border:none;border-top:solid #E1E1E1 1.0pt;padding:3.0pt 0in = 0in 0in"> <p class=3D"MsoNormal"><b><span lang=3D"EN-US" style=3D"font-size:11.0pt;fo= nt-family:"Calibri",sans-serif">From:</span></b><span lang=3D"EN-= US" style=3D"font-size:11.0pt;font-family:"Calibri",sans-serif"> = Joe Clarke (jclarke) <[email protected]> <br> <b>Sent:</b> Thursday, June 25, 2026 8:27 PM<br> <b>To:</b> Chongfeng Xie <[email protected]>; Graf Thomas, SCS-I= NI-NET-VNC-E2E <Thomas.Graf-Zc0CTiu5wcBWk0Htik3J/[email protected]>; ops-area <ops-area@ietf= .org>; opsawg <[email protected]>; nmop <[email protected]>; nmrg@= irtf.org<br> <b>Cc:</b> [email protected]<br> <b>Subject:</b> Re: [nmrg] Re: [NMOP] Re: [OPSAREA@IETF126] IRTF/IETF OPS T= ransfer: Status & Exploring Collaboration Opportunities<o:p></o:p></spa= n></p> </div> </div> <p class=3D"MsoNormal"><o:p> </o:p></p> <table class=3D"MsoNormalTable" border=3D"0" cellspacing=3D"0" cellpadding= =3D"0" align=3D"left" width=3D"100%" style=3D"width:100.0%"> <tbody> <tr> <td style=3D"background:#CF4A0C;padding:5.0pt 2.0pt 5.0pt 2.0pt"></td> <td width=3D"100%" style=3D"width:100.0%;background:#FFF8E5;padding:5.0pt 4= .0pt 5.0pt 12.0pt"> <div> <p class=3D"MsoNormal" style=3D"mso-element:frame;mso-element-frame-hspace:= 2.25pt;mso-element-wrap:around;mso-element-anchor-vertical:paragraph;mso-el= ement-anchor-horizontal:column;mso-height-rule:exactly"> <b><span style=3D"color:#222222">Be aware:</span></b><span style=3D"color:#= 222222"> This is an external email.<o:p></o:p></span></p> </div> </td> </tr> </tbody> </table> <p class=3D"MsoNormal"><o:p> </o:p></p> <div> <div> <p class=3D"MsoNormal"><span style=3D"color:black">Chongfeng, I mostly agre= e with everything you said. That is, I have a similar understanding. = I do have a few comments, though, based on my implementation experien= ce.<o:p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"color:black"><o:p> </o:p></span>= </p> </div> <div id=3D"mail-editor-reference-message-container"> <div style=3D"border:none;border-top:solid windowtext 1.0pt;padding:3.0pt 0= in 0in 0in;border-color:currentcolor currentcolor"> <p class=3D"MsoNormal"><span style=3D"color:black"><o:p> </o:p></span>= </p> </div> <div> <p class=3D"MsoNormal">Q1. Which AI agents capabilities are suitable for ne= twork management? <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"> A: AI agents have the follo= wing common capabilities, <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Perception: Processes multi-modal in= puts (text, images, audio) and tracks context and state over time.<o:p></o:= p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] This depends on model. Not all models can hand= le all types of input. And the model capabilities will influence over= all cost.<o:p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Planning & Reasoning: Breaks hig= h-level goals into actionable sub-tasks, dynamically re-plans when obstacle= s arise, and evaluates trade-offs before acting.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Tool Use & Execution: Autonomous= ly calls external tools—search engines, APIs, calendars, code interpr= eters, and databases—to take real action in the digital world (e.g., = send emails, book flights, query data).<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] More specifically, with network management, tools ca= n access devices to get data and adjust configuration. In the former,= what the agent can then do with the data it retrieves heavily depends on the model and its training data. For example, man= y frontier models generally do well with basic network operational data. &n= bsp;Adding on to tool use, RAG or purpose-trained or tuned models, and you = can get even better results from such tools calls.<o:p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Learning & Self-Correction: Dete= cts errors, reflects on outcomes, iterates on solutions, and utilizes both = short-term and long-term memory to improve over time.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] This is where Digital Twin comes into place. Y= ou don’t necessarily want a model to “learn” as it’= s going through your production network. Testing its “reasoning= ” in a twin environment makes it safer for doing that self-correction and iteration.<o= :p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal">All the capabilities above are useful for network ma= nagement. With the underground support of LLM models, the following functio= nalities can be realized by AI agents in the context of network management,= <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"> <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"> - Intent-based auto-assignment: Automat= ically routes NOC tickets based on detected intent.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Intelligent root-cause analysis: Pinp= oints fault origins with precision.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] Eh, <i>maybe</i>. See above. I’ve had models go off the rails= on hyper-specific problems where it didn’t have a lot of relevant tr= aining data.<o:p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Actionable troubleshooting guidance:&= nbsp; Generates step-by-step plans and recommended resolutions.<o:p></o:p><= /p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - AI-driven orchestration: Enable= s expert-human collaboration and automated execution of task reassignments/= suspensions.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Continuous network optimization: = ; Delivers ongoing tuning recommendations for wireless, core, and cloud-net= work resources across diverse scenarios.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"> - Automated recovery verification: = ; Validates fault resolution by querying network and perceptual metrics via= LLM-orchestrated API calls.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"> <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal">Q2. What is the impact of an AI network management p= rocess to YANG information, service, network and data modelling?<o:p></o:p>= </p> </div> <div> <p class=3D"MsoNormal"> A: AI and legcay network m= anagement models belong to different domains, the specific manangemen= t modelling is aganostic to the AI network manangent process. In other word= s, AI system can process any YANG information, service, network and data modelling. <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] This has exactly been my experience. I’v= e had good luck with a YANG-centric skill. Where things can get probl= ematic is the token consumption XML and JSON produce when using open weight models with tighter context windows.<o:p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal">Q3. Is MCP (<a href=3D"https://en.wikipedia.or= g/wiki/Model_Context_Protocol">https://en.wikipedia.org/wiki/Model_Context_= Protocol</a>) a suitable protocol between AI agents and IETF network manage= ment data sources and system components?<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"> A: Yes, as an open standar= d that connects AI models to external data and tools, MCP enables AI assist= ants to securely read files, query databases, and execute actions across di= fferent applications. The likelihood of MCP being used between between AI agents and IETF network management data sources and sys= tem components is very high. <o:p></o:p></p> </div> <div> <p class=3D"MsoNormal">In addition, other approaches can be used, such as A= PIs exposed by network controller, in this case, AI agents can call the API= s directly for network device configuration or data collection. <o:p><= /o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] Agree completely. This does work well. A= nd MCP has considerable framework backing.<o:p></o:p></span></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal">Q4, How does an AI agent interact with Network Digit= al Twin, Intent-Based Networking, SIMAP, Knowledge Graphs and YANG data in = Message Brokers?<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"> A: It depends on the specific sit= uation, there should be no one-size-fits-all solution.<o:p></o:p></p> </div> <div> <p class=3D"MsoNormal"><o:p> </o:p></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">[JMC] See above on a thought on digital twin. And, y= eah, I don’t think we’ll have a one-size fits all model.<o:p></= o:p></span></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black"><o:p> </o:p></span></p> </div> <div> <p class=3D"MsoNormal"><span style=3D"font-family:"Arial",sans-se= rif;color:black">Joe<o:p></o:p></span></p> </div> </div> </div> </div> </body> </html> --_000_ZR1P278MB11705083FFE0BF2061C9EE1B89FE2ZR1P278MB1170CHEP_-- ------=_Part_217833_96794165.1783579595390 Content-Type: application/pkcs7-signature; name=smime.p7s; smime-type=signed-data Content-Transfer-Encoding: base64 Content-Disposition: attachment; filename="smime.p7s" Content-Description: S/MIME Cryptographic Signature MIAGCSqGSIb3DQEHAqCAMIACAQExDzANBglghkgBZQMEAgEFADCABgkqhkiG9w0BBwEAAKCAMIIG ODCCBCCgAwIBAgIUSsUJVqoGHtAgGVpYDZmJSjsiHI0wDQYJKoZIhvcNAQELBQAwUjELMAkGA1UE BhMCQ0gxFTATBgNVBAoTDFN3aXNzU2lnbiBBRzEsMCoGA1UEAwwjU3dpc3NTaWduIFJTQSBTTUlN 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