Fusion Consulting
- Role
- Sole editorial lead and content strategist. Product decisions on the content surface, including killing the scorecard
- Client
- Fusion Consulting (Auston, Founder + Lead Consultant)
- Year
- 2026
- Status
- Live at consulting.tryfusion.ai
The live site at consulting.tryfusion.ai.
Result
I built the Fusion Consulting brand's thought-leadership portfolio from scratch, 12 source-verified articles on the mid-market AI adoption gap, plus the ICP that defined the consulting buyer. Every factual claim traces to a public source, because a consultancy that gets caught fabricating one statistic loses the argument for all of them.
Problem
Fusion Consulting is an AI consulting practice for mid-market firms ($10M to $500M revenue). The gap it addresses is real. Big consultancies are too expensive, off-the-shelf tools are insufficient, and most mid-market companies lack the in-house AI expertise to bridge that themselves.
The constraint. Publishing into a regulated-industry-adjacent space requires source-verifiable claims, because a single misattribution is fatal to consultancy credibility. Twelve articles is a large surface to hold to that standard, and the verification had to catch errors introduced during editing, not just by the original author.
My Role
Authored the 12-article insight portfolio as the sole editorial voice, covering the mid-market AI gap, why AI projects fail, build versus buy, hire versus outsource, ROI and cost, governance, shadow AI risk, and AI in 30 days.
Designed and built the insights page, the public entry point to the portfolio.
Designed and then killed the scorecard lead-magnet, an interactive 12-question assessment with a scoring engine and email gate. On revisiting it after the build, I called it out as not backed by data and as scope creep, and killed the feature rather than ship something that would not hold up.
Authored the ICP, the ideal customer profile, defining the mid-market AI-consulting buyer, mapping industries by consulting fit, and identifying PE portfolio companies as the high-value segment. I wrote the enterprise platform's ICP too, which is how the two stayed distinct.
Ran the citation audit across all 12 articles, tracking 71 issues and catching 2 errors that editing had introduced. Authored the per-claim audit trail mapping every passage to a verifiable source URL.
Editorial review across the site's case-study pages, where I caught and removed fabricated client information.
Solution and Process
The editorial approach was twofold, marketing copy carrying the product offer and thought leadership carrying the expertise behind it. Both were published on the same site and promoted through the same channels, so a buyer could find the thinking without hunting for it.
Verification was a post-write audit rather than a simultaneous one, which is the gap I would close next time. What did work was checking published claims against the source documents independently instead of trusting the writer's recall. That is what caught a Shadow AI statistic where both the unit and the frequency had drifted from the original.
Alternative considered and rejected. The scorecard lead-magnet. Interactive assessments are a standard consulting lead-gen pattern, but nothing empirical justified this one's scoring logic. Killing it was the correct call under the same standard that governed the articles.
Impact and Metrics
Live brand at consulting.tryfusion.ai with 12 source-verified articles as the content surface. Every claim traces to a verifiable source, drawing on primary publications from RSM, BCG, McKinsey, RAND, MIT, Deloitte, IDC, the U.S. Chamber, SBA, Vistage, Microsoft, and Intuit.
The audit caught two errors that would otherwise have shipped.
The ICP separated the consulting buyer (CEO, CTO, or VP at a $10M to $200M company with a failed AI pilot and board pressure) from the enterprise platform buyer, which stopped the two practices from blurring their messaging.
Reflection
I would move citation verification earlier in the production cycle instead of treating it as a post-write audit. Independent checking worked, but running it as a pre-publish gate would have caught the same errors before they propagated into related articles, which is what ate part of the production runway.
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