8 answers
L
Student
Woodbridge, Virginia
5
Questions
Updated
1776 views
I keep hearing over and over that it is important in one's profession to have "AI skills". I understand how AI is going to change the work force in the future, but what particular AI skills are important to have?
So far I am a SME with AI computer hardware, networking and infrastructure. I have built an agent at home, used few shot tuning on a generic LLM, and did a resume builder and mock interview on it. I have a small prompt library that I keep at work and at home, slowly expanding to making skills and eventually larger tools. Is this enough to say "I have AI skills"? Is this going to become the same thing as saying "I have MS office and internet skills" in the future?
Should I be focused on training, prompting, building, RAG, embeddings, ethics, coding, APIs, genAI, model tuning, agentic workflows, and certifications before I say I have AI skills?
Basically which skills are desired or required in the future?
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8 answers
Kelly Fry, MBA, PMP
Customer Success Executive - Post Sales Strategic Advisor for Technology Platform
8
Answers
Wenatchee, Washington
Updated
Kelly’s Answer
Given your answer here you are already in the top 10% of users who are actively working on AI skills. Great work!
The first step is awareness and understanding. It appears you know this well. On your resume, you should list the specific tools/models that you like to use and that you are familiar with prompting, etc.
Second (and this is where you can differentiate for now) is how are you using the tools to add value -- make money or save money. Even if you are able to streamline workflows, that results into time saved = dollars retained.
Once you are able to use your knowledge to create value from the tools you understand, you will be in the top 5% or 1% of AI users and this will become a key competitive advantage. When discussing this on your resume, be sure to lay out the quantifiable benefit (numbers) to showcase how these tools and skills have definitive value.
The first step is awareness and understanding. It appears you know this well. On your resume, you should list the specific tools/models that you like to use and that you are familiar with prompting, etc.
Second (and this is where you can differentiate for now) is how are you using the tools to add value -- make money or save money. Even if you are able to streamline workflows, that results into time saved = dollars retained.
Once you are able to use your knowledge to create value from the tools you understand, you will be in the top 5% or 1% of AI users and this will become a key competitive advantage. When discussing this on your resume, be sure to lay out the quantifiable benefit (numbers) to showcase how these tools and skills have definitive value.
Thank you! This is a skill I am slowly building, this is the perfect direction to build this skill around!
L
Joseph Neilson
Radiation Detection Physicist
265
Answers
Oxford, England, United Kingdom
Updated
Joseph’s Answer
I think your comparison with "MS Office and internet skills" is quite apt - both are a broad continuum of skills. At the bottom end of the range, a lot of people can claim on a resume or CV to have Office and internet skills, but what they often mean is a very basic "I can work a browser and handle simple documents" - really a default expectation in the modern world, and not skills that are making or breaking careers. However, as you increase through the scale into "'I'm an intermediate/advanced user who can build complex Excel formulae with XLOOKUP and INDIRECT; compose macros and VBA or a master of Power Automate", that's a different level of skills that does mean more.
AI skills are similar. Increasingly, "I have AI skills" is meaning at the bottom end - "I can get ChatGPT to write an email for me" or "I use Gemini for search" - which is increasingly becoming an expectation rather than a skill above the rest. However, what you've described is definitely more of the advanced skill set, certainly around the LLM side of AI. (you didn't list much around traditional ML "AI", but you're allowed to be a specialist in one form of AI and still claim "Advanced AI skills".)
I'd probably recommend you provide clarity in CVs/applications on what you mean by "AI skills" - rather than just "AI skills", say something like "Advanced AI skills including model tuning, agentic workflows and prompt engineering" - from what you've described, I think that's something you can legitimately claim.
AI skills are similar. Increasingly, "I have AI skills" is meaning at the bottom end - "I can get ChatGPT to write an email for me" or "I use Gemini for search" - which is increasingly becoming an expectation rather than a skill above the rest. However, what you've described is definitely more of the advanced skill set, certainly around the LLM side of AI. (you didn't list much around traditional ML "AI", but you're allowed to be a specialist in one form of AI and still claim "Advanced AI skills".)
I'd probably recommend you provide clarity in CVs/applications on what you mean by "AI skills" - rather than just "AI skills", say something like "Advanced AI skills including model tuning, agentic workflows and prompt engineering" - from what you've described, I think that's something you can legitimately claim.
Thank you for this was a very thorough answer! I will consider adding some ML skills to my skill set as well!
L
Audrey Dargan
4
Answers
Dublin, County Dublin
Updated
Audrey’s Answer
Think about how you can utilise AI to optimise your work or personal life. Can you use ChatGPT or other resources to reduce the time you spend in planning i.e. writing a cover letter for a job, prepping for an interview, replying to a friend in a difficult conversation?
The most important thing is how willing you are to adopt AI and incorporating it into your life so that you can display this in an interview for a job. If used correctly you can minimise the time you spend on 'busy-work' and optimise the time spent on high level / priority tasks.
Hope that helps!
The most important thing is how willing you are to adopt AI and incorporating it into your life so that you can display this in an interview for a job. If used correctly you can minimise the time you spend on 'busy-work' and optimise the time spent on high level / priority tasks.
Hope that helps!
I am all about taking boring tasks and automating them with AI! Thank you for your response!
L
Natig Ahmadov
Social media
1
Answer
Baku, Azerbaijan
Updated
Natig’s Answer
The work you are doing now — building an agent, tuning it, and creating a custom prompt library — elevates you from a mere user to an "AI implementer." Yes, these are pretty serious skills for today. But you're right, in the near future, saying "I know AI" will be as commonplace as saying "I can use the Internet" today. What will make the difference is not how, but to what depth you use the tool.
The most sought-after skills in the future will not just be the ability to ask questions, but the ability to build systems. You should pay special attention to RAG (Retrieval-Augmented Generation) technology; because the most important thing for companies is to get AI to work properly with their internal, confidential data. In addition, learning Agent workflows (the coordinated work of several bots) and API integrations will greatly strengthen you from a technical perspective.
As for coding, even if you are not a professional programmer, understanding scripts written in Python and modifying them according to your needs will put you one step ahead of others. Ethics and security are the "responsibility" side of things, which are absolutely required in large projects.
In short, you've already laid the foundation. Now, if you focus on connecting these skills (deployment and workflow), you'll have solidified your place as a future expert. Certifications are great, but real projects you've built and agents working effectively will always speak louder.
The most sought-after skills in the future will not just be the ability to ask questions, but the ability to build systems. You should pay special attention to RAG (Retrieval-Augmented Generation) technology; because the most important thing for companies is to get AI to work properly with their internal, confidential data. In addition, learning Agent workflows (the coordinated work of several bots) and API integrations will greatly strengthen you from a technical perspective.
As for coding, even if you are not a professional programmer, understanding scripts written in Python and modifying them according to your needs will put you one step ahead of others. Ethics and security are the "responsibility" side of things, which are absolutely required in large projects.
In short, you've already laid the foundation. Now, if you focus on connecting these skills (deployment and workflow), you'll have solidified your place as a future expert. Certifications are great, but real projects you've built and agents working effectively will always speak louder.
Thank you! I think I am going to find some more projects to do!
L
Hemant Negi
Software Developer
4
Answers
Delhi, DL
Updated
Hemant’s Answer
Hi,
- Show value, not just knowledge — the real differentiator is "I used AI to save X hours or automate Y task" not just "I know how to prompt"
- Put specific tools on your resume — LangChain, specific LLMs, vector DBs, whatever you've touched — name them explicitly
- Add RAG next — it's the #1 skill companies need right now for working with their own internal data
Learn MCP (Model Context Protocol) — Anthropic's open standard for connecting AI agents to real tools, files, APIs — this is becoming the backbone of agentic systems, learn it now before everyone else does
- Look into ACP (Agent Communication Protocol) — emerging standard for how agents talk to each other in multi-agent systems, very early but very important
- Sandboxes & safe execution — knowing how to run AI-generated code safely (E2B, Docker sandboxes, isolated environments) is a real skill as agentic systems grow
- API + workflow integration — connecting AI to real systems (Slack, databases, internal tools) is where the money is
- Even basic Python — you don't need to be a dev, just enough to read and tweak scripts
- Quantify everything — "reduced X process from 2 hours to 10 minutes using an agent I built" beats any certification
On the MS Office comparison — you're right, it's coming:
- Basic AI use will be table stakes soon
- Building and integrating AI systems will stay rare and valuable for a long time
Your hardware + infrastructure background is a secret weapon — most AI people can't do what you do on the infrastructure side. That combo is genuinely hard to find.
Keep building real projects. Real things you've built will always speak louder than any certification. You're on the right track — just keep going.
- Show value, not just knowledge — the real differentiator is "I used AI to save X hours or automate Y task" not just "I know how to prompt"
- Put specific tools on your resume — LangChain, specific LLMs, vector DBs, whatever you've touched — name them explicitly
- Add RAG next — it's the #1 skill companies need right now for working with their own internal data
Learn MCP (Model Context Protocol) — Anthropic's open standard for connecting AI agents to real tools, files, APIs — this is becoming the backbone of agentic systems, learn it now before everyone else does
- Look into ACP (Agent Communication Protocol) — emerging standard for how agents talk to each other in multi-agent systems, very early but very important
- Sandboxes & safe execution — knowing how to run AI-generated code safely (E2B, Docker sandboxes, isolated environments) is a real skill as agentic systems grow
- API + workflow integration — connecting AI to real systems (Slack, databases, internal tools) is where the money is
- Even basic Python — you don't need to be a dev, just enough to read and tweak scripts
- Quantify everything — "reduced X process from 2 hours to 10 minutes using an agent I built" beats any certification
On the MS Office comparison — you're right, it's coming:
- Basic AI use will be table stakes soon
- Building and integrating AI systems will stay rare and valuable for a long time
Your hardware + infrastructure background is a secret weapon — most AI people can't do what you do on the infrastructure side. That combo is genuinely hard to find.
Keep building real projects. Real things you've built will always speak louder than any certification. You're on the right track — just keep going.
ACP is a new term to me! I'll dig into that one and brush up or learn everything else you listed here! Thank you!
L
Sandeep Khandelwal
Software Engineer
131
Answers
San Ramon, California
Updated
Sandeep’s Answer
Hello,
You already have more AI experience than many people who simply list “AI skills” on a resume. The important part is not just using AI tools, but understanding how to apply them to solve real problems.
In the future, valuable AI skills will likely include:
* Working with APIs and automation
* Prompting and workflow design
* Understanding data and model limitations
* Building AI-assisted applications
You already have more AI experience than many people who simply list “AI skills” on a resume. The important part is not just using AI tools, but understanding how to apply them to solve real problems.
In the future, valuable AI skills will likely include:
* Working with APIs and automation
* Prompting and workflow design
* Understanding data and model limitations
* Building AI-assisted applications
Thank you! I have been looking at MCP for a while so I will definitely be following your advice!
L
Adam Edwards
IT Support Manager
5
Answers
Richmond, Virginia
Updated
Adam’s Answer
I think you are on the right track. Yes, AI skills will be like saying you know how to use the Internet.
However, there is much greater value in saying I have implemented AI to perform this task and this is how I solved this problem with AI tools. You are on the right track with certifications and additional professional development. Never stop learning new things because this will ultimately set you up for success when you become the subject matter expert for a new tool just because you were curious and played around with it.
Continuous improvement in all things you do will open doors and you'll be prepared to seize opportunity when its presented.
However, there is much greater value in saying I have implemented AI to perform this task and this is how I solved this problem with AI tools. You are on the right track with certifications and additional professional development. Never stop learning new things because this will ultimately set you up for success when you become the subject matter expert for a new tool just because you were curious and played around with it.
Continuous improvement in all things you do will open doors and you'll be prepared to seize opportunity when its presented.
Thank you! Never stop learning will continue to be my mantra!
L
Supreeti Sehra
15
Answers
Updated
Supreeti’s Answer
You are definitely ahead in the game. The differentiator will be depth + integration + outcomes. There are many different layers to AI:-
1. Layer 1 : Foundations (you already have most of this) - Prompting (beyond basics), understanding LLM behavior (hallucinations, context limits), basic agent workflows
2. Layer 2: Systems thinking (RAG, database etc)
3. Layer 3: Integration -APIs (must-have), Connecting AI to real tools (Slack, CRM, databases), Automation pipelines, Backend logic
Push yourself and build on what you have already learned and focus on orchestrating workflows based on efficiency and tool usage. Pick a layer and integrate systems that will help you or the organization reduce manual effort while utilizing minimum tokens. In the process you are designing, validating implementing, validating and debugging the system from end to end. Showing impact that will stand you out. If you are interested in security or specialization in a field then add certifications.
1. Layer 1 : Foundations (you already have most of this) - Prompting (beyond basics), understanding LLM behavior (hallucinations, context limits), basic agent workflows
2. Layer 2: Systems thinking (RAG, database etc)
3. Layer 3: Integration -APIs (must-have), Connecting AI to real tools (Slack, CRM, databases), Automation pipelines, Backend logic
Push yourself and build on what you have already learned and focus on orchestrating workflows based on efficiency and tool usage. Pick a layer and integrate systems that will help you or the organization reduce manual effort while utilizing minimum tokens. In the process you are designing, validating implementing, validating and debugging the system from end to end. Showing impact that will stand you out. If you are interested in security or specialization in a field then add certifications.
Thank you so much! Thank you for breaking this question down and responding to its parts as well!!
L