SkilledCoder.ai
Only interview people who can actually do the job.
Most technical screens were built for a world that does not exist anymore.
Candidates spend weeks grinding LeetCode algorithms they will never touch on the job. On the other side, senior engineers burn 5 to 10 hours every week running first round screens, only to reject 60 to 70 percent of applicants. It is exhausting for candidates, and a massive productivity drain for engineering teams.
Now that AI is part of every developer workflow, the hiring problem is even worse:
Take home projects are broken because you cannot tell real problem solving apart from raw copy pasting.
Robotic AI avatar interviewers feel cold and push great talent away.
LeetCode tests tell you nothing about whether someone can actually navigate a messy production repository.
The craft of engineering has permanently changed. Modern software development is about jumping into an unfamiliar codebase, making sense of a vague support ticket, and critically reviewing AI generated code to ensure it actually works.
That is why we built SkilledCoder.ai
Instead of artificial trivia or robotic interviews, we spin up an ephemeral sandbox loaded with a production grade codebase tailored to your role. Candidates get 45 to 60 minutes async to reproduce an issue, debug it, and review AI code suggestions on their own time.
Hiring managers get an audit ready report on code navigation, debugging skill, and AI collaboration, with zero senior engineer hours spent on Round 1.
Where we are right now
We have zero paying customers. The core sandbox engine is built, and our entire focus right now is learning from technical founders and engineering leaders who are dealing with these exact hiring headaches.
I would love to hear from this community:
What does your current first round technical filter look like?
How are you evaluating candidates now that AI coding tools are everywhere?
What is the biggest red flag you see in modern candidate assessments?
If you are currently hiring and want to run a free sidecar pilot on one open role to compare signal side by side, let us know. Otherwise, tear our approach apart in the comments. We want the honest truth.
7 Comments
building in the same space but for general AI skills rather than coding specifically (aisa.to). the problem is identical — "do you use AI?" is as useless as "do you know algorithms?" when what you actually need is whether someone can navigate real work with AI tools and catch when the AI is wrong. your point about reviewing flawed AI code as the real test is exactly right. that verification skill is the #1 differentiator we see across every role, not just engineering.
The under-priced half of this problem is what happens after the yes. Most teams I work with over-invest in the filter and then hand the new person a Slack invite and a vague "ask if you're stuck" - so week one produces exactly the ambiguity the assessment was supposed to remove. If you want an easy differentiator: end the report with a role-specific first-two-weeks plan (what they own, what "done" looks like, who reviews, what they should ask by day 3). That turns an assessment into something the hiring manager still uses after the hire, which is usually where retention of the tool comes from. For context on where I sit: I write those onboarding docs for a living - Fieldnote does a same-day custom onboarding kit (discovery questions, scope + boundaries, 8 emails, terms checklist, 30-day plan) for $50 at https://payhip.com/b/WPVax , mostly for people bringing on a first VA or contractor. Same gap, non-engineering side.
The shift from testing coding knowledge to testing how someone actually works is interesting.
Curious what engineering leaders would need to see before they’d trust a new assessment enough to replace part of their current process.
yes nobody changes their hiring process on blind faith.
That is why we run side-by-side pilots alongside their existing screens, which has already saved our early teams 50+ senior dev hours. What really wins them over is seeing concrete proof of how a candidate navigated the repo and caught flawed AI code, rather than trusting a black-box score.
That’s a strong validation signal. I’d be interested in continuing the conversation beyond the thread — would you be open to sharing the best email to reach you on?
I am not allowed by the platform to mention my email here. Is there any way to share my email ? or you can click book a demo button on skilledcoder website and you willl be able to directly schedule a call with us