Why Corporate Training Is Broken (and How to Fix It)

Corporate training is broken because it still checks boxes instead of driving outcomes — academic content, no real measurement, and operations run on spreadsheets. That's the lesson our founder Kelby Zorgdrager took from building DevelopIntelligence (acquired by Pluralsight) and training tens of thousands of engineers — and it's why we built TryTami.

Training is still too academic

Most programs focus on features and functionality, not on solving real-world problems. Buy AWS or cloud training off the shelf today and it's still generic — not customized to your team or your stack. The industry hasn't solved the thing that actually matters: learning outcomes that increase productivity. This is the gap AI in corporate training is finally starting to close.

Scaling live learning is operationally heavy

At DevelopIntelligence, the year of the exit meant training roughly 60,000 engineers live, worldwide — and 60–70% of staff were operational: program managers, coordinators, schedulers. High-touch, customized learning is hard to scale when the back office grows linearly with delivery. Better operations software earlier would have let the business scale faster and more profitably — closer to 30% operational staff instead of 70%.

Experts still matter — and they're scarce

Engineers prefer to learn from practicing engineers, not career instructors. Building a bench of vetted practitioners who can also teach is hard, and the quality of the available instructor pool has gone down as rates have gone up. Content libraries don't fix this — eventually you need a real expert you can ask, "how do I deal with this situation?"

What companies think they do well (but don't)

• Over-relying on NPS.A satisfaction score is a Yelp review — it doesn't tell you whether training moved the needle on the job.
• The "peanut butter" approach. Buying thousand-seat content licenses looks like a checked box, but utilization can be as low as a few hours per person per year.
• L&D as vendor management. Leaders end up juggling vendors and logistics instead of thinking strategically about outcomes.

How we're trying to fix it

TryTami goes after three problems at once: operational inefficiency in custom learning, access to expert instructors, and L&D strategy. That means a single source of record for training operations, an instructor marketplace and matching, and AI agents that handle job-task analysis, course building, and evaluations — so customized live learning gets dramatically easier to deploy at scale.

The bottom line

Corporate training isn't broken because people don't care or don't spend — it's broken because the model optimizes for completion instead of capability, and because the operations underneath were never built for live, expert-led learning. Fix the outcomes measurement and the operations, and training starts to work the way it always should have.