News · Published 24 July 2026 · Updated 26 July 2026 · 4 min read

People + AI delivery needs one transparent rule

MH – Applied AI combines senior engineering and agentic execution under a visible commercial model instead of treating AI usage as an opaque surcharge.

In one paragraph

People + AI delivery pairs senior engineering judgment with agentic execution in one working model. The first two hours are free for scope setting; billing then starts at USD 2,800 per engineering day, including USD 300 of agentic AI usage. Scope and expected days are agreed before delivery.

AI changes the unit of work

An engineering day no longer has to mean one person moving through a queue of tasks sequentially. Agentic tools can research a codebase, draft alternatives, run tests, prepare migrations, and maintain documentation in parallel.

That capacity creates value only when someone senior frames the problem, supplies the right context, reviews the output, and owns the consequences. Tokens without judgment produce volume, not reliable delivery.

One rate across services

MH – Applied AI uses one commercial rule across its services:

  • the first two hours are free and used to set scope;
  • billing then starts at USD 2,800 per engineering day;
  • each billed day includes USD 300 of agentic AI usage;
  • the expected number of days is agreed before delivery begins.

The included usage makes the combination explicit. Agentic execution is part of the delivery system, not a hidden pass-through cost added after the work.

What remains human

Senior engineers remain responsible for architecture, security boundaries, trade-offs, review, stakeholder decisions, and operational acceptance. They decide when a model helps, when deterministic software is safer, and when additional context creates risk instead of value.

Human ownership also includes saying no: to an unsuitable use case, an unmeasurable promise, unnecessary model complexity, or a deployment that the client cannot operate.

An ambition, not a fabricated average

MH – Applied AI works toward a 3–5× value ambition compared with conventional sequential delivery. That is a design target, not a measured or guaranteed average.

The actual result depends on the mission, constraints, existing systems, quality requirements, and the client team’s ability to make decisions. Evidence belongs to each engagement. The commercial model makes the inputs visible; it does not turn an ambition into a fake metric.

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