Pro-Tips to Master AI

DROdio

Master AI within the enterprise by learning how DROdio, the CEO of Storytell.ai, uses Storytell day-to-day. drodio.substack.com

Episodes

  1. 3 MAR

    How Nate B. Jones Advises Our Product Roadmap at 4 AM Every Morning (While We're Both Asleep)

    I'm writing my first Storytell "Action" take have Nate B. Jones' latest AI thinking and apply it to Storytell's product roadmap This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    5 min

  2. 18 FEB

    Writing In Your Voice, On Demand: Using Storytell's New "Persona Skill" Feature

    I have a terrible habit of having my best thoughts in the worst places. Driving to pick up the kids. Mid-workout. Halfway through making coffee. The thought is vivid and clear, and then — almost immediately — it starts to fade at the edges. I’ve lost more genuinely interesting ideas to the friction of “I’ll write that up later” than I care to admit. So when I realized I could literally speak a blog post into existence — record a few minutes of rambling audio, hand it to Storytell, and use Storytell’s new Persona Skills feature to get back a fully structured Substack post that sounds exactly like me, I became a little obsessed. This post is the companion guide to the video above I made to walk you through this process. If you watched want a step-by-step written reference to follow along, you’re in the right place. Let’s go. Why This Works The core idea is simple: your thoughts are more fluid when you speak than when you type. So instead of staring at a blank page, you talk — to others in meetings, to yourself, to nobody in particular. Then you let Storytell do two things: * Learn your voice — your patterns, frameworks, tone, the way you build an argument * Turn your video, audio., transcripts or notes into written output — structured, in your style, ready to edit and publish The Skills feature is the mechanism that ties this together. Think of it as a pre-loaded, reusable set of instructions that knows exactly how you work, or speak, and can apply that understanding to your raw unstructured material. Pro-tip: Having Storytell write in your voice is just one small example of teaching Storytell a skill that it can then re-use at scale. You might also have Storytell learn how to speak like your CEO, your sales engineer, your data analyst. Skills aren’t limited to speaking “in the voice of,” either. You might give Storytell specialized knowledge about how your company likes to respond to customers and invoke that skill when doing churn analysis or customer success work. Phase 1: Build Your “Voice Foundation” This is the one-time setup. Do this right, and everything you have Storytell write in your voice becomes tuned to the way you write. Using the “Skill Creator” The Skill Creator is an easy way to have Storytell build a new skill, like “writing in my voice.” Invoke it by typing the @ symbol and then start typing “Skill Creator” — you’ll see it in a pop up menu. Then type a prompt like the one below to create a “Voice of” persona-based skill that will output a detailed brand voice and messaging guideline — things like your communication style, your values, how you frame problems, your recurring themes. Storytell will craft a “Voice of” Skill based on your instructions, which you can then save for future use. You’ll get back output that feels almost uncomfortably accurate. Mine had things like “vulnerable over polished” and “problem-focused over solution-obsessed.” That’s the goal — a document that captures you, not a generic professional persona. Save the Skill to Your Project and Put It To Work Once Storytell generates your “Voice of” persona skill, you can start to use it like I did in the video above to create this Substack post. Here’s a screenshot of the output from Storytell that formed the basis of that post: Storytell offers many pre-built skills, and you can add as many of your own as you’d like. But Wait, There’s More Storytell also just launched a Prompt Library that lets you save and re-use your favorite prompts. If you switch to “advanced user mode,” you can even put field variables into your saved prompts. This lets you create a saved prompt that uses one of your skills, like this: The next time you want to run that prompt, you just select it from the Prompt Library and it’s ready to go: The Real Math Here Before I built this workflow, the barrier between “having a thought” and “publishing a post” was high enough that most thoughts never made it. The friction — the blank page, the organizing, the writing, the editing — added up to hours I often didn’t have. Now it looks like this: * 5 minutes of audio → captured thought * 1 click → structured draft in my voice * Edit to taste → polished post, ready to publish I’ve built the project once. The “Voice of” skill is ready. The labels are set. Every time I want to publish now, I start with a system that knows my voice. The whole system compounds. That’s the part I couldn’t have predicted when I started experimenting with this: how much easier the tenth post becomes compared to the first. The project just keeps getting richer, more context-aware, more me. I hope you can experience the same result! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    4 min

  3. 17 FEB

    From Zoom call to shipped code: My workflow for PRDs

    Most brilliant engineering conversations evaporate into Slack history. I spent 20 years watching velocity die in that gap. Here’s my exact workflow for turning a 15-minute call with an engineer into shipped code using Storytell + Cursor to bridge human conversation and AI execution. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    19 min

  4. 10 FEB

    Turning a 12 minute conversation between CEO + Engineer into investor updates, technical and help documentation

    As CEO, I need to understand what my engineering team is building—but I also can’t spend hours diving into each technical improvement. When my team shipped powerful new functionality around multi-fleet agents and tools at Storytell, I needed a deep understanding fast. Here’s exactly how I used our own product to turn a quick phone call and some engineering tickets into a comprehensive understanding I could use for investor updates, technical capabilities documentation and user help docs. CSVs and transcripts don’t usually play nice together. But with Storytell.ai, you can combine unstructured data (like audio transcripts) with structured data (like Linear tickets) to create polished, production-ready documentation. This isn’t just about saving time, it’s about scaling knowledge across your organization and specifically across teams. In this case, I used: * A conversation transcript about new functionality we’d shipped (I used a 12-minute phone call with my engineer, Alex) * Structured data related to that topic (I exported recent engineering tickets from Linear) * Existing documentation we wanted to update (we have a tech stack page and help documentation) What I did, Step-by-Step I spent 12 minutes on the phone with Alex, having him walk me through how our new tools, agents, and skills work. Pro tip: Storytell has the ability to directly record audio right in the project, which can be very useful to capture conversations like this. The result: A raw, conversational transcript that contains the knowledge I needed. I exported from Linear all the engineering tickets and issues that had activity in the last week. This gave me detailed technical context on what was actually being built and shipped. Now I had two distinct data sources: * Unstructured: The conversation transcript * Structured: CSV data from Linear I already had this tech stack page that needed updating. Here’s what I asked Storytell to do: * Consume the existing URL (the old tech stack page) * Using the resources above (the transcript + Linear tickets), write an executive summary about how all the technology works * Write up detailed documentation * Rewrite the entire page I wrote this prompt and Storytell got to work—reasoning, doing web searches, doing knowledge base searches on my internal data. Phenomenal. I also had this existing help documentation that needed refreshing. I asked Storytell to: * Consume the existing webpage (I copied it as markdown) * Run the prompt to update our help pages I used a diff checker to see the differences between the old version and the new version. The results were clear: There was a whole new section on the Storytell tools ecosystem that came directly from my 12-minute conversation with Alex. Storytell pulled insights from the conversation, cross-referenced with the Linear tickets, and integrated everything into cohesive documentation. I now had three updated assets: * Human-readable documentation with information about specialized agents, tools, skills, etc. * LLM-optimized version — this is what we send to large language models so they can learn how Storytell works (meant to be read by machines, not humans) * Help page updates — specific user-facing documentation about how to use these features I sent the help page updates to our customer success team to publish. This entire workflow—from phone call to published documentation—took less than an hour and was based on time I’d already spent on a call anyway. The magic is in combining different data types that traditionally don’t work together: * Conversational, unstructured knowledge (transcript) * Structured, technical detail (Linear CSV exports) * Existing documentation (web pages) That’s how you make use of time you’re already spending to scale knowledge across departments. Hope it’s useful! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    3 min

  5. 9 FEB

    How To Create Pre-Filled 1-Click Prompts in Storytell

    We just shipped our Prompt Launchpad with 1,659 curated, pre-filled prompts that users can easily submit with just one click. You can find them all right here. If you’ve visited Storytell.ai recently, you’ve seen them on the homepage—featured prompts like “Churn Risk Analysis” or “Find Anyone’s Work Email Address” where you can literally upload one file, hit go, and get high-quality output immediately. Here’s how you can also create these pre-filled 1-click prompts to share with others. Step 1: Enable Advanced Mode First, you need to have Advanced Mode turned on. This isn’t enabled by default, but it’s available to all users: * Go to your user settings in Storytell * Switch on “Advanced Mode” Once you do this, you’ll see extra icons and options that let you create template variables, share draft prompts, and build the sophisticated prompts I’m about to show you. Step 2: Write Your 1-Click Prompt Using Template Variables To create a pre-filled prompt, you just use the # hashtag when writing a prompt, like this: You’ll be able to add one of four types of variables, and to choose whether they should be optional or required: Here’s what it looks like after you add the variable: Once you’ve put the fields in that you want your user to fill in, just choose Share this draft prompt from the share menu at the top right of the prompt box. That’s it! You can now paste this shareable URL anywhere (into an email, a Slack or Teams message, etc) or you can bookmark it for later use. Here’s the 1-click prompt I just created in the screenshots above for you to try: https://storytell.ai/?chat=Analyze+our+customer+accounts+using+%23%7Bfile%3ASales+Data%7D Going Way Deeper: Giving Storytell Specialized Knowledge In the video above, I do a deeper dive showing how I did way more than just create a 1-click prompt: I gave Storytell specialized knowledge to use when answering this “Help Me Resolve Conflict” prompt. If you want to learn how to do that, too, read on! Helping Humans Navigate Conflict (with one click) Most of our featured prompts are work-focused, but I wanted to tackle something different in the last spot I had available for the top six featured prompts on the Storytell.ai home page: Helping humans with conflict resolution. Why? Because conflict is fundamentally unstructured data—messy emotions, unclear needs, communication breakdowns. This is an area where Storytell excels. Using the process outlined below, I was able to build a prompt that uses the Clean Communication Framework developed by Erika Anderson combined with Stan Tatkin’s PACT framework without fine-tuning or training a custom LLM for this expertise. Step 1: Gathering Source Materials As I said above, everything from here on is optional. You don’t need to do any of this to make a pre-filled 1-click prompt. I first needed to assemble the raw “knowledge” Storytell would need to expertly answer the prompt query. This step is optional — out of the box Storytell is trained on the world’s knowledge, so if you’re not working with a bespoke framework like I was, you can skip this work. I created a project in Storytell called “Clean Communication” and uploaded multiple assets: * The Clean Communication Framework PDF (we literally use this at Storytell internally when we need to work through challenging conversations) * Active listening frameworks * Various other related materials Think of this step as loading the knowledge base that Storytell will synthesize its prompt expertise from. Step 2: Have Storytell Synthesize the Training Document Here’s where it gets powerful. Instead of manually compiling all the knowledge I’d need to have Storytell respond expertly, I just asked Storytell to do the synthesis work: My prompt to Storytell: Synthesize all the data in this project and create a comprehensive framework document for an LLM to consume about clean communication. Storytell went to work. You can actually watch it process in the video above —searching through the knowledge base, pulling relevant sections, organizing the material. What it created was a detailed training guide that included: * The different levels of communication (logic, emotions, vulnerability) * Tables of feelings associated with met and unmet needs * Tools like “observations vs. judgments” (e.g., “You’re always late to meetings” vs. “I’ve noticed you arrive 10 minutes after the hour for our last five meetings”) * Guidance on translating emotions into unmet needs This is the key insight: humans get stuck at level two (emotions). “I’m angry you didn’t show up to the meeting we scheduled.” But there’s no resolution at the level of emotions. The work happens at level three—vulnerability and unmet needs. “I felt angry and disappointed. I have an unmet need for consideration and partnership. I need to know that our time together matters to both of us.” The training document I had Storytell create teaches the LLM how to guide humans down to level three. Step 3: Store the Training Document in GitHub Gist Once Storytell generated the comprehensive training document (about 1,300 lines of markdown), I needed to make it accessible to the prompt. Here’s my process: * Download the document as markdown (the native language of LLMs) * Create a new GitHub Gist * Paste the markdown content into the gist * Grab the raw URL from the gist I went one step further: I created a subdomain at https://framework.cleancommunication.com that redirects to the raw gist URL. This makes the prompt more readable and maintainable. Step 4: Build the Predefined Prompt Now comes the actual prompt construction — like above, but with a twist. In Advanced Mode, you can use template variables to make your prompts dynamic: * Type your prompt in the prompt bar * Use # to insert template variables (text input, file upload, dropdown, or checkbox) * Mark variables as required or optional * But this time, I included the instruction to consume my training document: Go learn about the Clean Communication Framework by consuming it at https://framework.cleancommunication.com Try Using the Prompt! You can try this Help Me Resolve Conflict prompt by going to the home page of Storytell.ai — you’ll see it in the Prompt Launcher’s “Featured Prompts” section. You can also try it by clicking right here on this shareable URL. Why Do This? Traditional approaches would require fine-tuning a model, maintaining custom infrastructure, or using limited prompt space to create this level of specialized expertise for an anser. This approach is different: * The LLM expertise training document lives externally (GitHub gist) * Any foundational model can consume it on-demand * Updates to the framework just require updating the gist * The prompt stays clean and focused You can use this for any domain where you need an LLM to quickly ramp up on a specific skill set. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    9 min

  6. 24 JAN

    How I Used 141 Documents + Web Research to Revise a White Paper About Why 90% of Enterprise Data Is Dark

    Quick tutorial on how to rewrite and update your white papers using Storytell.ai. In this video, I walk through:• Updating content with new product capabilities pulled from Linear engineering tickets• Creating new documents from old ones efficiently Perfect for marketing teams, sales teams, product teams, and customer success teams who need to keep content current by leveraging internal knowledge sources like Linear or Jira. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    11 min

  7. 24 JAN

    Dogfooding at Its Finest: Using Storytell to Re-Position Storytell

    Watch me use Storytell to sharpen... Storytell's positioning. It's the ultimate meta-moment in building: using my own AI knowledge platform to refine how I articulate what that platform actually does. In this unscripted screen recording, I walk through my actual workflow—uploading podcast episodes about storytelling and category creation into Storytell, then leveraging those insights in real-time to refine how I'm positioning "predictive intelligence" as a new category. You'll see the practical mechanics of dogfooding in action: I'm copying podcast-derived insights between projects, enhancing product descriptions with frameworks pulled from my knowledge sources, and building positioning strategy not through guesswork, but through intelligent knowledge integration. This is what it looks like when I use the tool I'm building to solve the problems I actually face. As CEO, one of my core challenges is articulating what Storytell does and why it matters. By feeding the platform podcast content about storytelling principles and category creation, then querying that knowledge when I need it, I'm both solving a real problem and validating that the product works for knowledge-intensive work. The recording shows the real workflow—screens, clicks, copy-paste actions, and my thought process behind it all. It's unpolished, unscripted, and exactly the kind of behind-the-scenes content that shows how products get built and positioned in practice. This is building in public. This is dogfooding. This is using AI not to replace strategic thinking, but to amplify it with the right knowledge at the right moment. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    6 min

  8. 20 JAN

    Using Storytell to create LLM system instructions for Storytell to learn about itself

    As the CEO of Storytell.ai, I’m constantly thinking about how Storytell.ai can transform the way teams work – not just in theory, but in practice. In the video above, I walk through the exact process I use to export engineering ticket data, review use cases, and create LLM system instructions to help Storytell be more effective in understanding itself, so we can then apply it to specific sales and marketing use cases. I’m writing this to share what I’m actually doing, because I keep getting asked by other CEOs and executives: “How do you actually implement this stuff day-to-day?” Here’s the honest answer: It’s a combination of tactical engineering work, strategic analysis, and cross-functional collaboration. And it’s messy, iterative, and absolutely worth it. Why I Care About This Before I dive into the how-to, let me give you some context on why this matters to me. At Storytell, we’re obsessed with making data-driven analysis and storytelling as great as possible for users – whether that’s in education, entertainment, or enterprise applications. This isn’t just CEO-level strategy work. This is how I actually spend my time, working alongside our engineering team, sales and marketing teams, and other executives to make sure we’re building the right thing, fast, instead of the wrong thing, right. Step 1: Train Storytell to understand itself, using Linear engineering tickets and JOBS data. To make Storytell as effective as possible, I first want our infrastructure to understand itself. And we use Storytell to do that. We’ve created this public Gist in GitHub that we provide to our LLM infrastructure so it is aware of what it can do, and how users use it. Here’s how we made it: I wrote this prompt asking Storytell to understand itself. In the prompt, I referenced a label called Linear Data. That label contains several assets that I’ve added to the project — CSV exports from Linear of our completed engineering tickets, and use case examples around ways users use Storytell: I got a good initial result, but I wanted more depth, so I also used our Google Drive integration to load all of Storytell’s documentation into the project. These files are all automatically labeled with the Google Drive folder name, which I was able to easily reference in my prompt: Here’s the output I got from Storytell, which I loaded into the GitHub Gist file. Putting it to use Our engineering team will use this Gist file to update Storytell’s system instructions, so it instinctively knows more about itself and its capabilities. But I can also use that Gist file in prompts. For example, in the video above, I improve my “SWOT++” prompt to do a better job of understanding how Storytell can help a company — like Netflix, in this example— solve some of its toughest problems. Here’s a screenshot of me using the Gist file (which I shortened to “http://go.Storytell.ai/capabilities” using our link shortener) in my Netflix prompt: Below is a bit of Storytell’s output, and here the full SWOT++ analysis produced by Storytell — more on this in a future post! This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    10 min

  9. 10 JAN

    How I Use Storytell to Identify, Research & Target Enterprise Customers

    Selling isn’t about pitching products—it’s about telling stories that resonate with real problems. In the video above, I share how I use Storytell.ai to remix external web information about an enterprise prospect with internal data about our platform and my bio, background and interests to compose personalized outreach to an enterprise prospect. The “STORY” Sales Method Sellers know BANT or MEDDIC — in this age of Agentic AI I’d like to introduce the “STORY” sales method, which stands for: * Search: Have AI continuously search company intelligence across the open web, including news, social, SEC filings, LinkedIn, blogs, websites and more to understand what a prospect’s realtime objectives and challenges are * Triangulate: Have AI match those objectives and challenges to the capabilities your solution offers and find the best personas — or even better, the exact right people — for you to reach out to * Opportunity: Have AI create an in-depth dossier on each specific opportunity for you to add value, tailored to the prospect you’ll be engaging with. * Remix: AI combines the external intelligence it’s gathered with the personalized solution dossier to create targeted messaging that will resonate with your prospect * Yield: All this means you are positioned to have high-value conversations equipped with deep intelligence, aligned capabilities, and messaging that speaks directly to what your prospect cares about right now The STORY Sales Method is a strategic approach to sales outreach that leverages curated knowledge and personal narratives to identify and engage prospects based on actual problems they face. Instead of generic cold outreach, you create a “knowledge fence” around your expertise and use storytelling to connect authentically. Before You Begin: Build Your Foundation Before you can effectively use the STORY method, you need to prepare three critical components that will fuel you use of Storytell for AI-powered outreach. Curate Your Knowledge Create a project in Storytell that’s all about you. In my case, I called it “DROdioGPT.” Put anything in there that is representative of you — your resume, blog posts, expertise, and interests I even put a FounderCulture podcast episode and my parenting blog into it. What to focus on adding: * Identify your core areas of expertise and experience and put as much content in as you’ve got that showcase those items * Determine what knowledge is most relevant to your target audience * Create Labels or Collections to organize different types of knowledge — this helps establish clear criteria for what stays in and what gets excluded from various sales narratives Gather and Organize Your Company Assets and Capabilities In a separate project (we cal ours Storytell Sales), collect all the materials that support your story and demonstrate your expertise. I wrote a full how-to blog post on how we created this GitHub Gist file that outlines the capabilities of Storytell, along with over 150 use cases around how different personas can get value from Storytell. Then copy the data about you from your personal collection over to this sales project and give it all al label like “About Me” (or just preserve the existing labels) Assets to include: * Techn`ical White papers * Case studies and success stories * Industry research and insights * Personal experiences and lessons learned * Client testimonials or results * Relevant data and statistics How to organize: * Label each asset with appropriate labels to taste — for example, based on the problems they address. You can do as much or as little of this as you wish * Ensure easy access when AI needs to remix this information Optional: Mine Your Personal Information for Story Gold Your personal experiences are the secret weapon in creating authentic connections. What to extract: * Challenges you’ve personally overcome * Mistakes you’ve made and lessons learned * Breakthrough moments or insights * Industry observations from your unique perspective * Client interactions that revealed deeper problems A great way to get this data is to load Otter, Granola, Zoom or other transcripts into Storytell and have it extract all of these gold nuggets into a dossier that you then “Add to Project Knowledge” to incorporate Storytell’s summarized output into your knowledge corpus. How it helps: These personal stories become the foundation that AI will use to craft authentic narratives that demonstrate understanding rather than just selling. The STORY Method in Action Now that your foundation is built, here’s how to apply the STORY framework to turn prospects into conversations. Step 1: SEARCH Company Intelligence What’s happening: Have Storytell search the open web to gather real-time intelligence about your prospect’s world. Here’s a sample prompt from the video above: Storytell can: * Scan news articles, press releases, and industry publications * Search social media posts from company leaders and employees * Analyze SEC filings, earnings reports, and investor presentations * Review LinkedIn profiles, company pages, and job postings * Examine company blogs, podcasts, and public content * Track recent company initiatives, product launches, or pivots What you’re looking for: * Current business objectives and strategic priorities * Challenges or pain points mentioned in public forums * Recent changes (leadership, strategy, market position) * Industry pressures or competitive dynamics * Growth initiatives or transformation projects Why it matters: You’re building a picture of what your prospect actually cares about right now—not what you assume they need. Step 2: TRIANGULATE Problems with Capabilities What’s happening: Have Storytell match the intelligence gathered in Search to your specific capabilities and finds the exact right people to contact. Here’s the part of the prompt where I used Storytell to do this in the video: Storytell will: * Analyze the prospect’s challenges against your curated knowledge base * Identify where your expertise, stories, and solutions align with their problems * Map specific capabilities from your assets to their stated needs * Find personas or individuals most likely to own these problems * Prioritize opportunities based on problem-capability fit Key questions Storytell will answer for you: * Which of their challenges do we solve best? * What stories from our experience mirror their situation? * Who in their organization owns this problem? * Which of our capabilities are most relevant right now? Why it matters: This isn’t spray-and-pray prospecting—you’re identifying genuine alignment between what they need and what you offer. Step 3: Create OPPORTUNITY Dossiers What’s happening: Storytell will create an in-depth, tailored dossier for each specific opportunity to add value. What’s included: * Summary of the prospect’s specific challenge or objective * Relevant personal stories from your experience that mirror their situation * Specific capabilities or insights from your knowledge base that apply * Context about why this matters to their business right now * Suggested value-creation angles for conversation The dossier answers: * What problem does this prospect have that we can address? * Why does this problem matter to them specifically? * What unique perspective can we bring based on our experience? * How can we create immediate value in the first conversation? Why it matters: You’re not just identifying an opportunity—you’re building a complete narrative framework for meaningful engagement. Here’s a screenshot from this example dossier Storytell compiled on Netflix Step 4: REMIX Into Personalized Outreach What’s happening: Storytell combines external intelligence, your curated assets, and your personal bio and stories into targeted messaging that resonates. The remix process: * Takes the opportunity dossier from Step 3 * Weaves in relevant personal stories that demonstrate understanding * Incorporates specific insights from your knowledge base * References the prospect’s actual situation from Search intelligence * Crafts messaging that invites conversation rather than pushing a sale Here are some Netflix examples from the video above: Storytell will also compose tailored outreach based on this remix of data: Storytell will structure your message to: * Open with relevant context that shows you understand their specific situation * Share a personal story that mirrors their challenge * Offer immediate value through insights from your experience * Invite dialogue focused on problem-solving, not selling Step 5: YIELD Value-Creation Conversations What’s happening: You’re now positioned to have high-quality conversations equipped with everything you need to add value. Importantly, you can spend your time in this step, not in steps 1-4 like you would otherwise need to. The outcome: Conversations shift from “selling” to “solving”—prospects engage because you’ve demonstrated understanding and offered real value from the very first touchpoint. Why it matters: You’ve stacked the deck in your favor by doing the deep work upfront. These aren’t cold calls—they’re warm conversations with prospects who recognize you understand their world. The Bottom Line Storytelling for sales isn’t manipulation—it’s about using the STORY method to transform authentic experiences and curated expertise into conversations that matter. By letting Storytell handle the heavy lifting of Search, Triangulate, Opportunity creation and Remixing, providing the personal stories and knowledge that make Remix authentic, you position yourself to Yield value-creation partnerships instead of transactional pitches. Start small: use the STORY method with one prospect, let AI gather the intelligence and match it to your capabilities, craft one personalized message, and see how the conversation shifts from “selling” to “solving.”

    6 min

  10. 9 JAN

    How to Use Storytell for Product Marketing

    DROdio describes how Storytell is used for product marketing, focusing on a task management system designed for storytelling projects. Key Features: Storytelling Advanced Web Search Tool: A specialized tool that enables social media searching within specific categories Custom Labeling: Users can create and assign new labels for project organization Documentation Integration: Incorporates storytelling documentation to support workflows @Mention Functionality: Provides collaboration features through at-mentions Purpose: The system aims to improve workflow efficiency and optimize for different types of use cases across teams including CEOs, engineering, and marketing departments. Deliverables: The project involves creating: A comprehensive blog post A condensed LinkedIn post for social media sharing The content emphasizes researching and creating new views of projects within a structured storytelling framework, with connections to platforms like GitHub and cross-functional marketing teams. This is a public episode. If you would like to discuss this with other subscribers or get access to bonus episodes, visit drodio.substack.com

    15 min
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Master AI within the enterprise by learning how DROdio, the CEO of Storytell.ai, uses Storytell day-to-day. drodio.substack.com

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