AI can finish your work without proving you understand it. Nivela maps your goal against what you can explain and apply, finds the gaps that matter, and gives you one clear next action.
Free first report. Private by default. No credit card. You approve what Nivela keeps.
How people used AI mattered. Participants who asked conceptual questions or generated code and then worked to understand it showed stronger mastery than people who delegated the task completely.
Three writers named the same failure mode from different angles:
All three describe the same failure mode: code exists, the engineer responsible cannot explain it. As Hall writes, the handover is gradual enough that you only notice it later — you still feel like you're writing code, but your role has shifted from driving to supervising.
Not a generic skills checklist. Real job postings, real requirements. Nivela shows which of your claims would hold under probing, and which would collapse in the interview.
Career Deep Check is the first Nivela workflow. It is a real asynchronous report, not a generic resume score.
Share your CV and the role you want. The target determines which claims and gaps matter now. A generic "backend engineer" produces a different report than "AI Backend Engineer at a Series B using NestJS."
Nivela classifies each important claim as supported, empirical but unverified, missing evidence, too broad, or unsupported. Ambiguity stays visible instead of being rewritten into confidence.
Recall, mechanism, reasoning, boundaries, transfer, and tradeoffs. The probe list is specific to your claims, not generic interview prep. Delivery is a separate skill — knowing the pattern matters more than having production experience.
Verified claims get a re-evaluation date based on stability and difficulty. Unverified claims get queued for study. The schedule adapts as you learn and re-probe.
One prioritized next step to improve your readiness. Not a list of twenty things to study. One action that changes your position.
Nivela is in validation. The first Deep Checks are reviewed manually and delivered asynchronously. Share your target and contact, and you will be notified when your slot opens. Nothing is stored beyond your explicit approval.
Nivela connects the parts that usually live in separate tools: your goal, current knowledge, trusted sources, learning process, verification evidence, and next action.
Most systems use a binary knows / does-not-know label. That hides the most common and dangerous state: has used it, cannot explain it. Nivela tracks a probability that decays over time, separated by how you encountered the concept. Seven states across a progression from claim to mastery to decay.
Mastery decays if not re-tested. Nivela schedules re-verification based on stability and difficulty, before retrievability drops to 90%. A verified concept that is due for re-evaluation is flagged at session start, not silently treated as still mastered.
Nivela does not ask "do you know X?" It probes six dimensions. Levels 1-2 mean empirical use. Levels 3-5 mean verified — these are the questions interviewers ask to separate real understanding from buzzwords. Level 6 is the interview-readiness layer: whether you can articulate it out loud under pressure. Behavioral answers are preparable: the system tracks which stories you can defend and which ones still have gaps.
Verification is not a quiz. It is a structured process with gates, fading, and metacognitive tracking.
Separate claimed, exposed, empirical use, needs-verify, verified, stale, and missing. Do not call a skill mastered because it appears on a CV or course certificate.
Turn selected books, articles, videos, courses, and work evidence into source-grounded explanations built around your existing knowledge and current goal.
Use recall, reasoning, tradeoff questions, and transfer challenges. Recheck knowledge over time instead of treating one correct answer as permanent mastery.
Connect the evidence to the goal and receive one prioritized action: study a prerequisite, defend a project claim, revisit a stale concept, or prepare for the next interview requirement.
Uploading a source does not mean you learned it. Nivela turns trusted material into a traceable learning and verification loop. Same engine as Career Deep Check, different entry point.
See what happens when you share an article to learn.
Nivela runs the same loop: ingest, extract, learn, verify, schedule. Click through the stages.
Availability is the proportion of time your system is operational. If your API is up 99.9% of the year, that is 8.76 hours of downtime.
Each additional "nine" is a 10x improvement. 99.99% = 52 minutes downtime. 99.999% = 5 minutes.
The strategies you just read about (redundancy, failover, replication) all serve one goal: reduce downtime when components fail.
Nivela does not grade with a single score. It tracks two models over time:
The goal is to identify the smallest action that changes your readiness.
Prioritize the missing capability that blocks the current goal instead of following every new roadmap or job-posting keyword.
Reading a clear explanation feels like understanding. It isn't. Researchers call this the fluency illusion — exposure to a well-written answer inflates perceived comprehension without building retrievable knowledge. Nivela tests retrieval, not recognition.
A polished claim is a liability when the reasoning behind it is missing. Narrow it, prove it, or remove it.
Every study session, verification result, correction, and source changes the next recommendation.
Your goals, approved facts, demonstrated knowledge, recurring gaps, preferred learning style, and next actions should belong to you, not to one conversation or model.
Nivela is designed to become a portable context layer that supported AI agents can read with permission. The same approved state can eventually guide learning, research, career decisions, and other capability packs.
A useful personal system needs sensitive information. Nivela must earn that access through control and evidence.
Nothing becomes canonical personal context without confirmation. Nivela may suggest, but you decide what stays.
Important claims keep their source and status so you can inspect why Nivela believes them. Every concept page carries verbatim quotes from the original source, not paraphrases. A claim without a source is a hypothesis, not a fact.
If the evidence is incomplete, Nivela says unverified. It does not turn a guess into a confident profile fact. You always know what is proven and what is not.
The planned product requires full export and deletion. Customer data must not be used for model training without explicit opt-in consent. Your data is yours, including the right to remove it.
Nivela comes from a personal knowledge system I have been building and testing for months. It tracks 304 concepts across system design, databases, JavaScript, and backend engineering. Each one has a probability of mastery that decays over time. Each one has a scheduled re-evaluation date. Most of them are not verified yet. That is the honest starting point.
Topics that were hard to talk about are now easy. Not because I read more, but because the system evaluated me: it asked for recall, mechanism, reasoning, boundaries, transfer, and tradeoffs. When I could not produce the answer, it recorded the gap. When I could, it scheduled when I needed to defend it again.
The system behind Nivela is complete, large, and hard. Source extraction from books, courses, articles, and videos into concept pages with verbatim citations. BKT probability tracking. FSRS spaced repetition. Prerequisite chain checking. Metacognitive calibration. It works because it is rigorous, not because it is simple.
Making it accessible to everyone as a sole engineer is the challenge I chose. The landing page you are reading is the first step: I want to know if this resonates before I build more. There is no product yet. There is a working system that proved the methodology, and a question: does this matter to anyone else?
Your free Career Deep Check includes:
Initial reports are delivered asynchronously during validation. Pricing for continued access is still being tested.
Choose the role you want. See which claims hold, which gaps matter, and what to do next.