What's the best way to train our engineering team on assigning evidence?

I'm a security lead at a fintech of about 200 people. We run Tugboat Logic and Drata side-by-side for different compliance frameworks, so I've lived with the engineer-evidence problem every quarter for two years.

The "best way" isn't a training course. It's to stop making it a separate process. Here's my breakdown on turning evidence collection from a chore into a byproduct.

* **Integration Depth vs. Manual Tickets:** If your evidence lives in Jira tickets, you've already lost. The winning move is pulling evidence automatically from systems engineers already use. Tugboat Logic can integrate with GitHub, GitLab, Jira, and AWS Config. The key is the automated "proof sessions." At my last shop, we configured it to scan specific repos for merged PRs with certain labels and pull commit histories for designated infrastructure-as-code paths. This covered ~70% of evidence needs without a single manual assignment. Manual tickets guarantee friction.
* **Engineer Workflow Tax:** Measure the time between "engineer gets ticket" and "evidence is accepted." Our manual ticket process took engineers a median of 48 minutes of context-switching and digging. Automating PR and cloud config evidence brought that to under 5 minutes for review. The "training" needed is showing them the automated report and teaching them how to tag PRs or deployments - a 15-minute session, max.
* **Auditor Acceptance:** Auditors don't want screenshots. They want immutable, timestamped logs with clear ownership. A PR link with merge approval chain is gold. A screenshot in a Jira ticket is suspect. The real limitation of any tool is evidence that *can't* be automated, like process walkthroughs. For that, we use Loom recordings embedded directly in Tugboat, which is still easier for engineers than writing paragraphs.
* **Real Cost:** Tugboat's pricing starts around $12k/year for the base platform. The hidden cost is engineering time spent on manual evidence gathering, which can easily double the TCO. If your tool can't reduce that, you're burning money.

My pick is to bypass "training" and instead invest a sprint in configuring Tugboat's automated evidence collectors for your top 3-4 evidence sources (e.g., GitHub, your CI/CD tool, your cloud provider). Use it for one compliance cycle, then refine. The specific use case for this is teams already using modern devtools. If you're in a heavily legacy or custom-tool environment, tell us, because then the equation changes to building custom integrations versus mandating process compliance.

You've hit on a real core issue. The moment it's a separate Jira ticket after the fact, it becomes an administrative burden and falls off the radar.

I agree that automation is the ultimate goal, but getting there requires some cultural groundwork first. Teams need to understand *why* evidence matters before the automation makes sense.

What worked for us was pairing the "why" with very specific examples. Instead of generic training, we ran short, 30-minute workshops for each squad where we walked through two controls they directly owned. We showed a "bad" evidence submission - a screenshot with no context, a PR link without a comment explaining its relevance - and a "good" one. The "good" example wasn't just the artifact, but it included a single sentence in the ticket or pull request description explicitly stating which control requirement it satisfied.

This gave them a concrete model and made the purpose click. It turned the abstract "assign evidence" into a simple, repeatable task: "link the thing and say why it fits." That basic understanding made the eventual shift to automated proof sessions much smoother, because engineers could validate what the tool was collecting.

You're right that it's a process problem, not a tool problem. The Jira-ticket-after-the-fact approach creates a separate to-do list that feels like paperwork.

I'd push back slightly on starting with full CI/CD integration. That's a long-term technical fix, but you need an immediate behavioral one. Before you can automate the evidence, you need engineers to consistently produce it. We found success with a simple rule: the evidence description is part of the definition of done for any work that touches a control. The engineer who merges the PR writes the one-sentence explanation of how it satisfies the control, right in the PR description or a linked ticket comment. It becomes part of the peer review. This shifts it from a post-hoc chore to a quality gate.

Thanks for laying out your current process so clearly. What you're describing, with Jira tickets assigned after the fact, is exactly the point where the process becomes a tax on engineering time and starts to break down. I've seen this pattern a lot.

The advice you're getting on automation is spot-on for the long game, but to get there, you need that cultural shift. For an immediate fix, I'd focus on the hand-off. Could you shift the ownership of that ticket *before* the relevant work starts? Make attaching evidence a gate for the ticket moving to "Done," not a separate task they discover later. This way, it's part of their workflow's definition of done, not a surprise assignment.

For training, we had good results with a 15-minute "lunch and learn" format where we dissected one real, anonymized control from their own domain. No generic slides, just walking through a confusing PR link they'd likely create and then showing a clear one with a single-sentence justification in the description. It made the "why" concrete. Have you considered piloting something like that with just one receptive squad first?