Skills Tech Network
Articles
Verified technical talent and community: proof-based hiring signals, technical reputation, mentorship, and staffing in the AI era.
Assess mentoring judgment separately from learner outcomes
Use separate records for teaching judgment and learner application, plus a consistent exercise when candidates cannot share past evidence.
Change the interview format, not the evidence standard
Keep engineering work samples rigorous by identifying essential constraints, testing alternative formats, and scoring the same evidence.
Stack gaps should not erase evidence of engineering judgment
Separate demonstrated engineering judgment from unresolved stack requirements, then test only the gaps that could change the hiring decision.
A bigger performance gain is not stronger hiring evidence
Weigh engineering impact claims by measurement quality, metric relevance, and individual attribution before comparing improvement percentages.
Resolve hiring disagreements before averaging scores
Separate factual disputes, evidence gaps, and conflicting role expectations before combining hiring scores or choosing a follow-up.
How to Assess an Engineer’s Code Review Work Samples
Use an anchored rubric to assess code review judgment, with separate evidence ratings and a structured alternative for candidates who cannot share past work.
How to Assess an Engineer’s Contribution to a Team Project
Use a shared-work worksheet and a two-part rubric to assess engineering judgment, verify individual contributions, and record uncertainty without demanding solo ownership.
How to Assess a Failed Engineering Project as a Work Sample
Assess engineering judgment, execution, and accountability with an evidence-based rubric that separates project outcomes from individual contributions.
Engineering Portfolio Under NDA: What Can You Safely Show?
Choose engineering work samples with a permission-and-provenance checklist, label independent demonstrations, and separate verifiable skills from unverified career claims.
How to Present a Canceled Engineering Project in Your Portfolio
Show verifiable contributions, decision-time context, and observed results, using a rubric that separates missing evidence from weak judgment.
Assess Engineering Skill, Not Permission to Publish
Use a confidentiality-safe evidence matrix to assess engineering candidates, distinguish demonstrated reasoning from verified past delivery, and choose consistent follow-ups.
When Open Source Contributions Stop Counting as Hiring Proof
Not all open source work signals the same thing to hiring managers. Learn which contribution types carry weight and which get ignored at senior levels.
What Hiring Managers Actually Discuss in Your Technical Interview Debrief
The real criteria hiring committees use after your interview rarely match the job description. Here is what engineers need to know.
Your Reference Network Decays Faster Than Your Resume Does
The engineers who vouched for you two jobs ago can't describe your current work. Here's why live proof beats a reference call you can't control.
Why Contract-to-Hire Conversions Fail Senior Engineers Who Lack Portable Proof
Contract-to-hire sounds like a safe path to a staff role, but without portable proof of impact, engineers lose leverage at conversion time.
The Peer Feedback Loop Most Senior Engineers Never Build
Why senior engineers who skip structured peer feedback stall promotions and how to build a credible loop that creates portable proof of impact.
The Peer Feedback Gap: Why Most Engineers Never Get Input That Changes Their Trajectory
Most engineering peer feedback is vague or political. Here is how to build the feedback loops that actually sharpen your technical reputation.
The Scope Transfer That Never Gets Documented
When engineers move on, critical ownership quietly shifts to whoever is nearby. Here is why undocumented scope transfer is a career and system risk.
Quiet Attrition: Why Senior Engineers Stop Raising Concerns Before They Quit
Senior engineers disengage long before they resign. Learn to spot the silence that precedes departure and what it costs teams when it goes unaddressed.
What the Artificial Analysis Intelligence Index Gets Right, and What Engineers Should Measure Instead
Benchmark leaderboards rank models, not engineers. Here's how to build hiring signals and career proof that survive model churn.
What a Go Grandmaster Beating KataGo With a Handicap Tells Engineers About Proof-Based Reputation
When human expertise defeats AI under harder conditions, it reframes what verified skill actually looks like, and why engineers need proof, not just credentials.
What Shin Jinseo Beating KataGo Teaches Engineers About the Limits of AI Evaluation
A Go grandmaster just defeated a top AI system. Here's what that signal means for engineers who evaluate, hire, or build on AI-assisted tools.
EU Regulation Is Coming for ChatGPT: What Engineers Building on LLM APIs Must Do Now
EU DSA scrutiny of ChatGPT signals tighter compliance requirements ahead. Here's what engineers shipping LLM-powered products must build into their stack now.
Internal Mobility by Proven Capability, Not Manager Memory
The best person for the project is often already inside, and invisible. Matching engineers to work by demonstrated capability instead of who a manager happens to remember.