Shoelace

Operational context

Shoelace originally launched as a SaaS product in the performance marketing space. When Vishaal joined, the company had just raised a seed round and was doing four figures in revenue.
Vishaal was the first employee overall and the first engineering hire, operating as a generalist with a mandate to solve the operational problems that were getting in the way of delivery.
Over time, the company evolved into a tech-enabled agency, which made the quality of the underlying service-delivery systems much more important.

Where work was breaking

At the time:

• • the SaaS model was struggling to gain traction
• • revenue was low and margins were thin
• • client onboarding and account management were almost entirely manual
• • Facebook Ads was evolving rapidly, with frequent API changes and instability

The operating problem was clear: if onboarding and campaign work stayed mostly manual, service delivery would be hard to run consistently and hard to scale.

System built

Role: first engineering hire / operations systems.

Partners: three founders. Scope: cross-functional work focused on identifying the biggest operational bottlenecks and removing them through systems and automation, even when the underlying data and APIs were messy.

• • automatic Facebook Pixel installation on Shopify stores
• • continuous syncing of Shopify product catalogs
• • one-click ad launching for account managers
• • integrations with supporting systems (reviews, email lists, etc.)
• • retry logic and alerting to handle Facebook API failures

These systems absorbed a large share of the repeated coordination work that account managers would otherwise have handled manually.

Constraints and edge cases

The strategy was to automate the highest-leverage bottlenecks first, even though the environment stayed messy:

• • Facebook introduced new ad formats constantly
• • core APIs were unreliable and failure-prone
• • client requirements varied widely

The systems had to be robust, retry-safe, observable, and overrideable when needed. Automation was paired with manual fallbacks so the workflow stayed reliable even when external systems changed or failed.

Operational outcome

• • account managers scaled from 10–15 accounts to 100+ accounts each
• • launching an ad went from a 15-minute manual process to ~1 minute
• • customer success and account teams experienced the largest productivity gains
• • service delivery became much more repeatable without matching headcount growth

As the business grew, these systems were extended to support additional ad formats, automated client reporting, and new workflow variations.

What this proves

Shoelace is not a field-service business, but it is a strong example of the same systems pattern. When service delivery is high-touch and failure-prone, the leverage comes from building the operating system behind the work so handoffs, launches, and follow-through do not all depend on manual effort.

Transferable lesson: when service delivery depends on repeated manual handoffs, the highest-leverage fix is often the operating system behind the work.