Wildfire Newsletter Complete! (workspace #1)

7d (edited) • 🏆 Wins

I can not stop running my mouth about the benefits of running 1 agent through these dynamic context / folder / markdown / skill trees. I'm ecstatic!!!

What I learned building my first production AI workflow with ICM

[newsletter builder]

Where things broke — and what I learned

Content accuracy doesn't self-police. The AI surfaced outdated content and presented it as current. We added a structured recency guardrail classifying content into three tiers — time-sensitive, forward-looking, and evergreen — each with its own freshness rules.

Factual claims need a dedicated review pass. Vague language around eligibility, requirements, and designations slipped through editing. We added a formal fact-check pass with explicit criteria: verify claims against primary sources and flag anything requiring tight specificity.

The build stage needs the right foundation. The first output was functional but not platform-native. Rebuilding it using our platform's actual template structure unlocked proper responsive behavior — and it deployed cleanly on the first attempt. [Sales Force template generation on the fly!!]

Generated assets need a management workflow. AI-generated images were enormous files causing slow load times. Building a download, optimize, and host workflow into the stage documentation means every future issue handles it consistently. [Connected Higgsfield MCP]

Updated our Sales Force template to the new HML syntax. -- Updating every reference in both the output and the skill documentation means future issues are built correctly from the start.

The takeaway

Every problem we hit became a documented fix that future runs inherit automatically. By the end of one session, the pipeline was producing accurate, platform-ready output with guardrails that didn't exist at the start. If you're building any recurring AI-assisted workflow, the investment in getting the stages right pays off.

0 comments