AI Minority

Agentic-engineering consulting

Make the consequential system trustworthy.

Narrow, technical consulting for companies facing an agentic implementation or reliability problem where “try another prompt” is no longer an adequate answer.

This path is separate from the AI Minority publication. Daniel reviews fit case by case and accepts only work where a focused investigation can be useful.

Useful starting points

Problems worth investigating.

The work starts with the actual system, its operating environment, and the authority it has—not a generic AI transformation program.

  1. 01

    Coding agents can modify consequential systems, but review and verification do not scale with them.

  2. 02

    An agentic workflow works in a demo but fails under production context, permissions, or organizational boundaries.

  3. 03

    The team cannot tell whether failures come from the model, tooling, context, constraints, or evaluation.

  4. 04

    A company needs an informed technical investigation before committing to an implementation path.

Describe the operating reality

Start with the problem.

Share enough context to assess whether Daniel can help investigate. Do not include credentials, secrets, proprietary source code, or regulated personal data.

01 Consequential implementation

02 Reliability under constraints

03 Evidence before prescription

What is happening now, where does reliability break down, and why is the work consequential?

What would a useful investigation or change make possible?

Is there a decision, launch, incident pattern, or deadline shaping the work?

Optional: stack, security, compliance, team boundaries, permissions, or evaluation limits.

Daniel reviews each inquiry. Submitting does not create an engagement.

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