How to build thought leadership that compounds
The editorial system behind content that gets cited, shared, and remembered
I spent the first half of my career as a practitioner, designing data warehouses, building predictive models, and deploying BI systems at IBM. The second half has been on the dark side of product marketing at SAS, Dell, TIBCO, Alteryx, and Alation, where I’ve tried to explain those same technologies to prospective buyers. Since then, I’ve had the opportunity to apply my trade as a full-time PMM consultant and advisor to startups and behemoths alike.
Both sides taught me the same lesson. The best content teams produce less.
That sounds backwards because every marketing leader I know is under pressure to publish more blogs, more social posts, and more thought leadership. AI has made it easy to crank out content at scale. Unfortunately, most of it is garbage.
I wrote about this a couple of years ago in a piece called “AI Entropy: The Vicious Circle of AI-Generated Content.” The problem has gotten worse since then. We’re drowning in content that says nothing, written by systems trained on other content that also said nothing. When you train something on nothing, what do you get? The whole industry is racing toward the semantic middle, like a tradeshow buffet full of rubbery chicken that technically counts as food.
Diagnosing this problem is easier than fixing it, and this post is about the fix.
The decision problem
Most B2B content teams have the skills to execute. What they lack is a decision-making process.
They publish before they’ve decided what they believe. They run a trend report, see something interesting, and rush to get a piece out the door. Two weeks later, they’ve moved on, and the piece sits there orphaned like a faded memory, generating nothing.
The teams that build real credibility follow a different pattern. Their content gets cited, shared, and remembered because they move through a specific sequence before publishing.
Discover → Decide → Commit → Validate → Amplify
Most teams skip from discover straight to amplify and then wonder why nothing compounds, why every quarter feels like starting over, and why their thought leadership sounds like everyone else’s. They never decided what they believed. They just published what they found.
A system that forces the hard thinking first
Over the past year, I’ve been building a library of prompt workflows for B2B marketers. There are hundreds of them now, covering everything from persona development to competitive battlecards to analyst briefings. If you’ve read The PMM’s Prompt Playbook, you’ve seen some of this work.
But individual prompts aren’t enough. What most teams need is a system that connects market understanding to published POV to distribution.
Phase 1: Understand the market
Before you can have a point of view, you need to understand what’s happening in your market. Two workflows handle this monthly.
Trend discovery scans for signals like new tools, behavioral shifts, and emerging patterns without jumping to conclusions about what they mean.
Competitive landscape mapping analyzes what competitors are doing and saying, so you understand the landscape before figuring out where to stand.
Both workflows are strictly about gathering raw material for later synthesis.
Phase 2: Decide what matters
Most teams collect signals but never force themselves to prioritize. I watched this happen at Alteryx when we were tracking the analytics automation space. We had dashboards full of competitor moves, analyst reports, and customer feedback. What we didn’t have was a clear answer to the question: what do we actually believe about where this market is headed?
Monthly market signal synthesis takes outputs from trend discovery and competitive mapping and compresses them into one or two clear market narratives. The workflow answers a single question: given everything we know, what should we care about right now?
This step is the upstream governor of the entire system. Getting it wrong means everything downstream becomes noise.
Phase 3: Commit to a point of view
Once you’ve identified a narrative worth pursuing, you need to decide what you believe about it with enough conviction to publish.
Insight to thought leadership takes one market narrative and forces clarity on your POV, your argument, and your boundaries. There’s no writing at this stage, just decision-making about what you’re willing to defend.
Strategic POV validation pressure-tests the POV before you invest in creating the asset. Is this differentiated? Is it defensible? Is it useful to your audience? The workflow ends with a real decision to advance, revise, or kill the idea.
Nothing serious should skip this step. I’ve watched teams spend weeks on whitepapers that should have been killed in the first hour.
Phase 4: Amplify without flattening
Once you’ve created something worth reading, you need to get it in front of people without turning it into sludge.
Thought leadership to social distribution translates a validated piece into platform-native content, expressing one idea in many ways while keeping the same spine throughout.
Content calendar and editorial planning orchestrates cadence, channels, and capacity so content planning stops being reactive.
How this runs in practice
Monthly, you run trend discovery and competitive mapping, then market signal synthesis, and then select one or two narratives. Picking only one or two narratives per month is the constraint that makes everything else work.
For each thought leadership asset, you run the insight-to-thought-leadership workflow, then POV validation. Only after validation do you create the piece itself.
After publication, you run social distribution and let one idea work across channels.
This approach eliminates the scrambling that most teams experience. There’s no more “what should we post this week?” panic, and no more orphaned content sitting on your blog with no amplification plan.
Why this approach works
The system does two things that most content operations fail to do. First, it forces you to make decisions before you start writing. You can’t skip ahead because each workflow requires outputs from the previous one. Second, it treats judgment and execution as separate skills that happen at different times with different inputs. Most teams blur these together, which is how you end up with beautifully written pieces that have nothing to say.
The result is leverage. One validated POV validated across channels will outperform ten mediocre posts. I’ve seen small teams consistently outperform much larger ones by following this principle: their smaller volume of content carried real conviction, and their audience could tell the difference.
The bottom line
You don’t need more content. You need fewer ideas, stronger conviction, and better sequencing.
That’s what this system is for.
The workflows referenced above are available on TinyTechGuides. If you’re building a content operation and want to talk through implementation, find me on LinkedIn.
About David Sweenor
Books: Artificial Intelligence | Generative AI Business Applications | The Generative AI Practitioner’s Guide | The CIO’s Guide to Adopting Generative AI | Modern B2B Marketing | The PMM’s Prompt Playbook
Founder of TinyTechGuides, David Sweenor is a top 25 analytics and AI thought leader and influencer, international speaker, consultant and advisor, and acclaimed author with several patents. He is a product marketing leader, analytics practitioner, and specialist in the business application of AI, ML, data science, IoT, and business intelligence.
With over 25 years of hands-on business analytics experience, Sweenor has supported organizations including Alation, Alteryx, TIBCO, SAS, IBM, Dell, and Quest, in advanced analytic roles.
Follow David on Twitter @DavidSweenor and connect with him on LinkedIn https://www.linkedin.com/in/davidsweenor/.
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