Daniel Covell

Software Engineer

Software Engineer with 4+ years of experience working on production-scale applications. Passionate about building robust and user friendly systems.

Experience

Lindy.ai

October 2024 — Current

AI automation platform. Fullstack typescript.

Oversaw key projects helping contribute to ARR growth from $2M to $8M and user growth from 30k to 400k.
Lead planning and development of a novel agent harness, called Input Tree, which directly lead to a 30x (200 to 6k integrations) expansion of Lindy's integration offering.
Scaled verification suite — including hundreds of unit, integration, and E2E tests and expanded eval tooling — enabling the team to safely ship 300+ new versions of existing actions and triggers.
Led cost reduction initiative that decreased average agent cost 95% ($10 to $0.50/user/day), directly improving unit economics for ~10k active users.
Worked intimately with modern software development tooling including Temporal, Redis, Sentry, DataDog and more.
Helped interview 25+ engineering candidates leading to 2 full-time hires

Groundswell.io

June 2021 — July 2024

First engineering hire. Promoted twice. Lead development on mobile, web, and social offerings.
Helped grow user base from 0 to ~5k users. Helped grow ARR from $0 to $300k
Worked across platforms helping build features and deploying software to end users, frameworks include React Native, React, Next.js, Express, GraphQL, Prisma, and PostgreSQL
Worked closely with CTO, CEO, and R&D leadership to identify and address process and product optimizations

Mushroom.gg

Jan 2021 — Mar 2021

Helped early stage social media start-up build out product features and grow daily active user base
Leveraged React to develop responsive front-end components, implemented GraphQL queries and mutations with Apollo caching, updated AWS hosted PostgreSQL database schema via data migrations
Collaborated closely with product, engineering, and design teams to iterate on system design and product features

Berkeley EECS Department (CS88)

Jan 2020 — Mar 2020

Helped freshman Data Science students learn Python fundamentals including abstraction, data structures, algorithmic thinking, and object oriented programming; other topics included SQL and machine learning