Repositioning a learning platform for the AI era

The change

The market for technical learning stopped being about courses. Enterprises moved from "teach our people a tool" to "build a workforce that can actually operate with AI," and buyers, analysts, and press all changed the questions they were asking. A company that had earned authority in data skills now had to be understood as an enterprise AI capability partner — while shipping product, integrating an acquisition, and competing against a crowded field of AI-training entrants with louder budgets. In a category that reprices this fast, the risk isn't bad coverage. It's being described in last year's language by the people enterprise buyers read.

The result

The engagement produced a system rather than a campaign. Instead of a media list that expired the week it was built, Research and media outreach workflows that enabled a small team to punch above its weight class through a combination of skill.md files and no-code automation. The team ended up with a maintained and scored media map, a prioritization model reused for every subsequent announcement, and a thought-leadership cadence that runs without rebuilding the research from scratch each time. The research work that used to consume days of senior time before every push now takes hours — with the judgment calls still made by a human, because those are the part that matters.

What I owned

Working through the company's agency partner, I ran the research-and-earned-media engine: identifying the journalists and outlets that actually shape enterprise AI-learning decisions, building the pitch prioritization behind every outreach push, and turning company data and executive perspective into stories reporters could use.

What I built

  • AI-assisted research and media outreach workflows that compresses the days of manual work behind media targeting into hours — with human judgment and QA at every decision point, not automated pitching.

  • A journalist research and validation system — a maintained, scored media map built on verified recent coverage rather than a stale contact list, so every pitch went to someone actively writing on the beat.

  • A pitch prioritization model that ranks a target list against a specific announcement by degree of fit, so senior effort goes where it converts instead of spreading across a blast.

  • A thought-leadership pipeline connecting proprietary company data to a repeatable cadence of executive commentary, bylines, and podcast placements.