For years, tech hiring was built on an implicit consensus: if a person knew how to write code, they probably knew how to think problems through. Languages, frameworks, years of experience were reasonable indicators. AI turned exactly that into a commodity. What used to distinguish a good engineer from a mediocre one, speed and technical fluency, now comes from a tool. The indicator broke.

The consequence is uncomfortable: hiring badly today is easier than ever, and it costs more than ever. Easier because AI helps the candidate produce output that looks good in an interview and in the first three months. More expensive because by the time problems appear, six months later, technical debt and architectural decisions are already in place. The DORA 2025 report says it with a phrase worth quoting: artificial intelligence acts as a mirror and a multiplier. It amplifies the strengths of cohesive teams and the weaknesses of fragmented ones. It fixes nothing. It accelerates.

If the skills model stopped working, something else has to be evaluated. The paper proposes what: the candidate's cognitive mode. How they decide under ambiguity, how they read someone else's code, how they translate between technical and business, how they connect pieces that already exist. This doesn't replace technical skills evaluation. It complements it with a layer nobody is evaluating in a structured way today.

Six cognitive modes

The method works with six modes: not personality types, but structured ways of approaching technical work. Four are core (evaluated in every process) and two are optional (activated depending on the role). Every person has a dominant mode and a range, meaning the capacity to activate other modes when the situation calls for it.

  1. 01
    Decision Architect Structures the reasoning that precedes the system. Identifies alternatives, evaluates trade-offs, argues what they rule out and why.
  2. 02
    Connector Combines pieces that already exist. Knows the ecosystem and chooses by fit with the problem, not by familiarity.
  3. 03
    Technical Editor Reads someone else's code and improves it without breaking what works. The most critical mode of the moment, because AI writes a lot and reviews little.
  4. 04
    Translator Converts between business and technical. Brings a business problem down to an actionable spec, and explains a technical limitation without losing rigor.
  5. 05
    Operator Optional Executes with autonomy inside a defined framework. Evaluated in juniors or when the specific role requires execution capacity under supervision.
  6. 06
    Guardian Optional Thinks about what can go wrong. Security, edge cases, observability. Doesn't slow the team down: prepares what the team builds to survive contact with reality.

Application and limits

The method runs in 45-minute interviews, calibrable between evaluators and designed to produce a diagnosis defensible to the client. It doesn't replace the technical skills test: a brilliant Decision Architect who doesn't know Kubernetes is still inadequate for a role that asks for Kubernetes. It doesn't replace cultural fit: cognitive mode says how a person thinks, not how they're going to behave in a specific culture. And it works better with seniors than with juniors, where the professional history available to discuss is more limited.

The full paper develops each mode in detail, the pathologies associated with each dominant mode when it operates without range, the interview protocol, the scoring criteria, the honest limitations of the method, and the bibliography that supports it.

Sources: Stack Overflow Developer Survey 2025; DORA 2025 (Accelerate State of DevOps Report); Bondy Group internal placement data and method development (2008–present).