Community Challenge: AI in Action Challenge

One of my favorite AI actions is to create playbooks. I’m currently sketching out implementing a MEDDICC playbook within new hire onboarding. Here’s a recent prompt I gave to Gemini:

tell me how a sales manager could use meddicc in a pipeline review, next week, in a very light touch high impact way

What I like about this prompt is that it emphasizes feasibility and impact. 

And low and behold, after some further prompting, I wound up with a rather useful MEDDICC coaching playbook. Look forward to pressure testing this with some sales leaders in the upcoming weeks!

My go-to AI prompt is for generating search optimized Keywords/Exact Matches/Keyword Matches from a document by combining the document’s actual content with what a client would realistically type into a search bar.

Prompt:

Review this document and generate a list of keywords, phrases, and search-friendly language based on both the content itself and the kinds of words or questions a client would typically use when trying to find this information. Include synonyms, plain-English alternatives, industry terminology, and likely client search phrases. Group the results by theme and prioritize the terms most likely to improve search relevance in our portal.

**If I’m using the ‘Keyword Matches’ field - this field is limited to 4 words, so I ensure to include this rule into my prompt if that is the field I’m using**

What I Use It For + What Tool I Use:

I use my firm’s internal AI system where I’ve built out my agents and built institutional knowledge so that it can analyze document content and help generate structured language outputs. This is key when I want to make sure our content is tagged and described in a way that reflects both internal terminology and client behavior.

Output It Produces + How We Use It:

It produces a refined list of:

• Keywords pulled from the document
• Client Friendly search phrases
• Synonyms and related phrases
• Plain language alternatives
• Grouped themes or categories for indexing/tagging

As we received feedback that the search functionality can get a bit overwhelming due to the volume and content we work with in our tenant, my team and I use the output provided by AI to improve how content is labeled, tagged, and surfaced in our portal. It helps us align document metadata more closely to what clients are actually looking for, which drives more efficient and intuitive searches, improves discoverability and reduces the time spent trying different search terms to find the right content. 

Challenge 1

We built a Claude plugin that contains all of our brand assets and standards (voice, style, visual identity), so anything the team produces — content, comms, training materials — comes out consistent with our brand identity by default. It took a few weeks to build and roll out company-wide, but it's paid off: no more manual brand-compliance checks on every deliverable.

Challenge 1- 

One of our biggest AI wins has been using AI to accelerate content creation and improve how sellers find and use content.

We're using AI to draft first versions of product pages, sales playbooks, launch communications, training materials, and Digital Sales Room content. Instead of starting from a blank page, our team can focus on refining messaging, ensuring accuracy, and tailoring content for specific audiences.

Time to value: Just a few days. Once we established a few reusable prompts and workflows, AI became part of our everyday content creation process.

Biggest surprise: The time savings were obvious, but the biggest benefit has been consistency. AI helps us create more standardized content while freeing up time for higher-value work like strategy, stakeholder reviews, and improving the seller experience.

Challenge 2- 

One prompt I use often is for building or refreshing product pages and Digital Sales Room content.

Prompt:

"Act as a sales enablement manager. Using the information below, create a customer-focused product page for sellers. Include a concise value proposition, key differentiators, ideal customer profile, discovery questions, business challenges solved, customer outcomes, objection-handling tips, and recommended supporting assets. Keep the language easy to scan and sales-ready."

Output: A strong first draft that can be quickly reviewed by product marketing before being published in Seismic or added to a Digital Sales Room.

Before AI: Building a new product page or customer-facing content often meant pulling information from multiple documents and spending several hours organizing and rewriting everything.

After AI: AI creates a structured first draft in minutes, allowing us to spend our time validating messaging, collaborating with stakeholders, and delivering polished content much faster.

Challenge 2

My most-used AI prompt:

“Smart Brevity this copy for a very busy sales force.”

Smart Brevity is a communication framework developed by the founders of Axios. The goal is simple: lead with what matters, make it easy to scan, and clarify what the reader needs to do.

I use this AI prompt for playbook copy, seller announcements, emails, lesson copy, and Seismic communications.

Before AI: Too much time spent cutting repetition and reorganizing copy.

After AI: A clear, concise first draft in minutes, giving me more time to focus on accuracy, relevance, and the seller experience.

My biggest takeaway: shorter isn’t always clearer. AI works best when it knows the audience, why the message matters, and what they should do next.

A few of our favorite AI prompts are for summarizing account information, reviewing call recordings, and even looking at strategic reporting. We are also fans of MEDDICC along with a few others in our community which is exciting! For example:

• Act as a strategic account executive. Analyze this account information. Identify likely business priorities, key stakeholders, buying signals, potential objections, competitive risks, and recommend a 30-day engagement strategy.
• Evaluate this call using MEDDICC. What information is missing? What risks exist? What should I ask next?
• Summarize the top 10 highest-fit prospects this month based on employee growth, funding events, and lack of internal HR  infrastructure, formatted as a briefing for the sales team.

Challenge 2:
My go-to prompt: I set up a scheduled task in Claude Cowork that runs daily: "Look at how I've used you over the past day — the prompts I ran, what worked, what didn't. Give me one tip to help me use you better: a capability I'm underusing, a sharper way to phrase something I keep asking for, or a shortcut I'm missing. A few sentences, specific to what I actually did — not generic advice."

What it's for / tool: Self-directed enablement — having Claude coach me on using Claude, based on my own usage patterns. Runs in Claude Cowork's scheduled tasks.

Output & how I use it: A short, personalized tip each morning tied to real gaps in how I'm prompting. When one's especially useful, I pass it along to the team in Slack so we're all leveling up on AI fluency together, not just me.

Before/after: Didn't exist before — there was no structured way to build our own AI skills; it was trial and error. Now it's a standing habit that costs me zero setup time after the first prompt.

Challenge 1:

My favorite AI win has been using AI to refine Seismic pages (aka playbooks) from boring, factual, overview-centered text to real guidance for our users - action-oriented language that improves how sellers interact with our pages. 

I keep working with my AI to adapt to my style - making sure that existing copy is refined to fit my standards - short, action-oriented, seller-focused, and clearly able to communicate the business outcome rather than read like product marketing copy. It knows to tell users what they’ll accomplish by using the page and will guide users in how to talk to their customers.

Time to value: The value for me was visible in just a day - the pages are easier to read, follow a familiar structure for the sellers, and save the seller time by providing the right context and guidance. We are still trying to determine how to quantify the value. 

Biggest surprise: The time savings were definitely expected, but I was pleasantly surprised at the consistency provided from page to page and topic to topic. The AI ‘remembered’ my style, which is making each of the pages I’ve touched in this way feel familiar to the seller. AI helps me provide that consistency so I can spend more time focusing in other areas where AI can’t necessarily help me. 

Challenge 2

My go-to prompt (leveraged from a coworker and refined for me): 

Act as my weekly productivity coach. Review available information from my notes, meetings, calendar, emails, chats, documents, action items, and recent work activity from the last 7 days. Identify tasks, commitments, deliverables, follow-ups, reviews, requests, project actions, meeting outcomes, and pending decisions that appear to require my attention. For each item: Give a short task title. Explain why you believe it is an active task. Estimate urgency (High / Medium / Low). Estimate importance (High / Medium / Low). Note any known due dates, deadlines, meetings, or dependencies. Flag items suitable for delegation. Flag items that appear stalled or waiting on others. Then organize everything: Urgent + Important (Do first); Important + Not Urgent (Schedule); Urgent + Less Important (Delegate); Neither Urgent nor Important (Minimize, postpone, or ignore). Next: Identify the top 5 priorities for this week. Suggest a realistic day-by-day focus plan for the remainder of the week. Highlight risks, deadline collisions, overloaded days, and missing follow-ups. Point out where I may be spending time on low-value work. If information is incomplete or ambiguous, ask concise follow-up questions before finalizing recommendations. Be pragmatic. Do not simply list everything. Help me focus on the few activities that create the most value. Use proper rich text formatting — headings, tables, and lists, not raw markup.

What I use it for and what tool I run it in: I run this in Microsoft Cowork and have it scheduled to run every Monday and delivered to my email inbox first thing in the morning. It use it to keep me grounded in value-driven activities.

The output it produces and how I use it: This is a personal prompt that helps make me aware of areas where I may be spending too much time that could be delegated to others or redirected in some way. It is an unbiased view of how I can work more efficiently and productively.

Before/After: Before, I felt like I had to be everything to everyone, but I am learning with this guidance where to better prioritize my time and put my efforts. 

My go-to AI prompt:

Act as a Sales Enablement Manager. Create a realistic seller role-play scenario for a sales professional selling [product] to an engineer at a manufacturing company. Include customer background, business challenges, competitive landscape, objections, desired outcomes, and seller objectives.

What I use it for and what tool I run it in:

I use this prompt in Microsoft Copilot to quickly develop realistic Seismic Role Play scenarios for product training and sales skill development.

The output and how I use it:

The output provides a complete customer scenario with relevant challenges, objections, and selling opportunities. I use it as a starting point for Seismic Role Plays, then customize it with product-specific details before assigning it to sellers. This helps reps practice customer conversations in a realistic environment and build confidence before engaging with customers.

Challenge 1 
 

Our team has adopted AI as a daily working partner, especially for building our sales applications and enablement content. It helps us turn complex product and application information into clear, visual, interactive experiences much faster, solving a major challenge for our growing global organization: creating useful, consistent content at scale.

We started seeing value almost immediately. Within one afternoon, we could develop a strong working concept, and within a few weeks, turn it into a live resource.

The biggest surprise has been how much AI contributes beyond speed. It helps us think through ideas, identify opportunities, and bring initiatives to life. The important lesson has been that human review is still essential, especially for technical accuracy, brand consistency, and real-world application details.

I have now got an AI playbook built which manages every Seismic initiative we have got underway.  It is my digital AI product manager and project manager all in one.  

I created the playbook by outlining what I wanted to achieve - track ideas, initiatives, set prioritization, capture dependencies etc and build that into a live product roadmap.  It means I no longer need to update lots of individual JIRA boards and maintain stakeholder presentations - I just chat to my agent and we update all of the content in real time.  

The bonus part of this is that it gives me really great HTML outputs that I can share with stakeholders.  

In addition, I have now expanded it to also run and check the usage on content and flag where we have any issues that could cause Sales problems - such as duplicate or unused content creating clutter.  That involves manually downloading our content library and uploading to my playbook but we are actively looking to connect with Seismic’s MPC to make this fully automated.

All of this is now saving hours every week / month and shows where AI and humans can work seamlessly together.

Challenge 1: 
Our team uses AI to transcribe our weekly team meeting, and that transcript feeds the agenda for the following week. Before this, the loose ends from one meeting (open questions, things we said we'd follow up on) lived in people's memory or scattered notes, so we'd start the next meeting reconstructing where we left off.

Value came almost immediately. The person on our team who builds the agenda used to spend hours every Friday tracking down loose ends. Now the transcript captures them as they happen, so that time mostly disappears. There wasn't much to set up, just turning it on and getting into the habit of reviewing the transcript afterward.

The surprise was how much it tightened up the rest of the work. Our meeting notes are a lot more streamlined now, and the weekly conversation itself is clearer because we're not spending the first stretch of each meeting piecing together where we left off.

Challenge 2:

Mine is built on a Know/Do/Say/Share structure. I give the AI my raw inputs for a playbook (the campaign details, the talk tracks, the assets) and ask it to organize everything into four sections: What to Know, What to Do, What to Say and What to Share. Then I have it return the whole thing as clean HTML snippets built to render well as a Seismic content block.

I use it for field playbooks that live in Seismic. I bring the content and the AI handles the structure and the formatting, so I skip the two things that used to eat the most time: figuring out how to organize it clearly and hand-building the layout that displays right in the platform.

Before AI, a playbook meant taking my notes and inputs, working out the structure myself, then formatting it by hand to look right in Seismic. That was a few hours per campaign. Now I hand over the raw material, get back organized HTML in minutes, and spend my time on the content itself instead of the packaging.

Challenge 1

Day to day, my team leans on AI across everything we do, from drafting training curriculum, to planning large-scale events, to turning complex projects into scalable, actionable steps. It's not replacing our expertise; it's amplifying it, letting us move faster and take on more ambitious work.

Challenge 2

Prompt: “Take these [source materials — call notes, product docs, existing decks, SME input] and turn them into a training curriculum outline. Structure it into modules with clear learning objectives for each, suggest a mix of formats (e.g., video, role-play, quiz, job aid), flag where reps are most likely to need practice vs. just information, and note any gaps in the source material I'll need to fill before building it out."

What I use it for / tool: I run this in Claude anytime I'm starting a new training program from scratch: new product launch, new process, onboarding refresh, etc.

Output & how I use it: It gives me a structured module-by-module outline with objectives, suggested formats, and gaps flagged, which becomes my working skeleton. I share it with SMEs to validate content, then build the actual materials (decks, job aids, assessments) on top of it. What used to take days of staring at raw notes and manually structuring a curriculum from scratch now takes about 15-20 minutes to get a solid first draft.

Before/after: Before AI, building a curriculum outline meant hours of sifting through scattered notes and docs, trying to figure out logical sequencing and where reps needed hands-on practice vs. just info. Now that structuring work happens almost instantly, and my time goes into refining content and getting SME sign-off instead of building the skeleton.