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In Santiago this week, walking around the city - bumped into one of our local billboards (the billboard refresh rate didn’t make it for a too great…
In Santiago this week, walking around the city - bumped into one of our local billboards (the billboard refresh rate didn’t make it for a too great…
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It's been a pleasure to work with Davis Filippell and the TeamWork Online team on this! They have big ideas, are super collaborative and move fast…
It's been a pleasure to work with Davis Filippell and the TeamWork Online team on this! They have big ideas, are super collaborative and move fast…
Shared by Jonathan Perichon
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So proud of the team behind this! Molly Higgins Blaine R. Joe Duchnowski Lu Yang Daniel Gallagher Ethan A., and many others who have helped!
So proud of the team behind this! Molly Higgins Blaine R. Joe Duchnowski Lu Yang Daniel Gallagher Ethan A., and many others who have helped!
Shared by Jonathan Perichon
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Checkr
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Checkr, Inc.
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Douglas Newingham
I have a hot take about how the rapid introduction of AI has impacted engineering teams. This comes from what I see every day inside my teams at Deel. The Software Development Life Cycle has always rested on three pillars: 1) Planning 2) Code Writing 3) Testing/Verification While the "Claudes" of the world have revolutionized Step 2, the impact on Steps 1 and 3 has been minimal. For experienced devs, AI removed the painful typing bottleneck. But for everyone else, it’s created a "velocity illusion." Most sensational AI demos focus on greenfield prototypes with minimal (or zero) legacy baggage. But in a complex ecosystem like Deel, the "magic" hits a wall of reality: 𝐄𝐱𝐩𝐞𝐫𝐭 𝐋𝐨𝐜𝐤-𝐢𝐧: Crucial domain knowledge and compliance logic are sometimes spread across docs, code comments, and the heads of senior engineers. 𝐓𝐡𝐞 𝐑𝐞𝐣𝐞𝐜𝐭𝐢𝐨𝐧 𝐋𝐨𝐨𝐩: AI can churn out code fast, but without the context of Step 1 (Planning), that code often lacks the nuance required for a global HR + payroll platform. It ends up being rejected by other teams because it missed a hidden dependency or a compliance edge case. The result? Step 3 (Testing) is now the ultimate bottleneck. Just because the code was generated in seconds doesn't mean the "Engineering Cost" has disappeared. Setting up stable test environments, seeding proper data, and verifying logic still requires human expertise. We are seeing a world where Step 2 is a tiny sliver of the timeline, but Steps 1 and 3 have stayed the same size. If we don’t start using AI to solve for context and verification, we’re just accelerating our way into a traffic jam. At Deel, we're releasing tools for any product-minded tinkerer to become experts in 𝒂𝒍𝒍 the SDLC steps. Are you seeing Steps 1 or 3 become your team's biggest hurdles? How are you bringing AI into the "Planning" and "Testing" phases? #AI #SDLC #SoftwareArchitecture
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