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Reveneau vs offshore and nearshore development

Offshore and nearshore delivery solve the cost problem by lowering the price of an engineer-hour, usually by hiring in a different labour market. An AI-native build solves it differently, by reducing how many engineer-hours the work takes at all. Those are genuinely different mechanisms, they combine badly with different kinds of risk, and which one suits you depends less on budget than on how stable your specification is and how much coordination your organisation can handle.

Facts about offshore delivery last checked 2026-08-21

  • Offshore lowers cost per hour. AI-native lowers hours required. Different methods.
  • Offshore economics work best on large, stable, well-specified scopes.
  • The hidden cost of distributed delivery is coordination, and it grows with ambiguity, not with headcount.
  • For a genuinely large programme with a fixed spec, offshore capacity is hard to match on price.
  • Neither model fixes an undecided scope.

Where offshore delivery is the right answer

Written first, and deliberately. If we could not fill this section honestly, the page would not be worth publishing.

What offshore delivery is good at

  • A materially lower cost per engineer-hour than most onshore options
  • Capacity at scale: teams of dozens can be assembled quickly
  • Established firms in this space have long track records and mature process
  • Time-zone overlap is a solved problem for nearshore, and manageable for offshore
  • Well suited to long-running maintenance and support that needs steady, predictable staffing

Choose them over us when

  • The scope is large, well understood, and unlikely to change much
  • You need sustained capacity over years rather than a defined outcome
  • You have strong internal engineering management to direct a distributed team
  • Ongoing maintenance of an existing system is the main job
  • Your budget model is headcount-based and unlikely to change

Side by side

Every cell about offshore delivery is labelled with where it came from. Nothing here is inferred, and a blank is left blank.

 ReveneauOffshore delivery
How cost is loweredFewer hours needed per buildLower cost per engineer-hourVerified
What you manageA scope and an acceptance standardA team, or a vendor managing oneVerified
Coordination overheadOne small team, one specificationGrows with team size and with ambiguityVerified
Best suited toA defined build with an endSustained capacity over timeVerified
What proves it worksAn eval suite written from the specification, blocking the mergeTheir internal QA and your acceptance testingTheir claim
Typical ratesScoped per build, quoted before work startsNot establishedNot established
Track recordNone yet. Reveneau is newEstablished firms have years of itVerified

This comparison is usually framed as quality versus price, which is both insulting to a lot of very good engineers and not the actual difference. The real difference is arithmetic.

Two different ways to lower the same number

The cost of a build is roughly the number of engineer-hours multiplied by the price of an hour.

Offshore and nearshore delivery reduce the second term. Hire in a labour market where an experienced engineer costs less, and the same work costs less. That works, it has worked for decades, and at large scale it is hard to match on price.

An AI-native build reduces the first term. If the implementation is generated, a build needs fewer engineer-hours, and the hours that remain are concentrated in specification and verification.

Both are real. They are not in opposition, and the interesting question is which term is larger in your particular project.

Where each method works best

The offshore method works better as size and stability increase. A large, well-specified programme running for two years, with clear requirements and a client who can manage a distributed team, is close to the ideal case. The per-hour saving adds up over thousands of hours and the coordination overhead is spread across a long engagement.

The AI-native method works best where the total hours are modest but the correctness standard is high, and where scope is defined enough to write checks against. Reducing hours matters less on a two-year programme than on a three-month build, and specification-led verification matters more when a defect is expensive.

The cost nobody puts in the proposal

Coordination. And the thing worth knowing is that it does not scale with headcount, it scales with ambiguity.

A perfectly specified task can be executed by a team anywhere in the world with almost no overhead. An ambiguous one generates a question, and every question needs an answer. Across time zones one question and its answer can take a day, and an ambiguous requirement can generate dozens of them.

That is why distributed delivery works so well on well-understood work and struggles on exploratory work, and it has nothing to do with the skill of the people involved. It is a property of the communication path.

It is also why "write the specification properly" is not a slogan on this site. It is the thing that determines whether either model works.

What we are not going to claim

We will not tell you offshore engineers are worse. The claim is false as a generalisation, we have no measurement, and this site does not publish claims it cannot show the calculation for.

We will not tell you we are cheaper. Reveneau is new and has no completed engagements to average, so any figure would be invented.

What we will say is that the two models fail in different places, and that the failure mode of distributed delivery is coordination cost on ambiguous work, while ours is a specification that was agreed and turned out to be wrong.

If you already have an offshore team

The most common real situation is not a choice between the two. It is that you already have a distributed team and you are wondering whether AI-native practice applies to them. It does, and the sequence matters more than the tooling. How to move an existing engineering team to AI-native development is written for exactly that case.

Where we fit

Reveneau suits this when

  • The scope can be specified precisely enough to verify automatically
  • You would rather not run a distributed team yourself
  • The work is a defined build with an end, not indefinite capacity
  • Correctness matters enough that the verification is the point

Common questions

Is offshore development cheaper than an AI-native build?
They lower cost by different mechanisms, so the answer depends on the type of work. Offshore lowers the price of an engineer-hour, which adds up on large, long, stable programmes. An AI-native build lowers how many hours are needed, which matters more on a defined build with a high correctness standard.
Are offshore engineers lower quality?
No, and we are not going to imply it. That claim is false as a generalisation and we have no measurement that would support it. The genuine difficulty with distributed delivery is coordination cost on ambiguous work, which is a property of the communication path rather than of anyone's skill.
What is the hidden cost of offshore development?
Coordination, and the important detail is that it scales with ambiguity rather than with headcount. A precisely specified task executes anywhere with almost no overhead, while an ambiguous one generates questions, and each question needs an answer that can take a full day across time zones.
When is offshore clearly the better choice?
Offshore delivery is the better choice for a large, well-understood scope running over a long period, especially ongoing maintenance with strong internal engineering management to direct the team. It also suits a headcount-based budget model and time-zone overlap that is already a solved problem for nearshore work. The per-hour saving adds up across thousands of hours and the coordination overhead is spread across a long engagement.
Can I use both?
Yes, and combining offshore delivery with an AI-native build is common. The usual setup is an AI-native build for the new, correctness-critical product area, priced as a defined outcome, with a distributed offshore or nearshore team doing ongoing maintenance and support of the wider system where steady, predictable staffing matters more than reducing hours per build.
We already have an offshore team. Should we replace them?
Usually not. The more useful question is whether AI-native practice, writing a specification and blocking changes until they pass an eval suite, can be adopted by the offshore team you already have, which is mostly a sequencing problem rather than a staffing one. Get blocking automated checks in place before raising the volume of generated code, not after, so quality does not fall while speed increases.
How does pricing compare between offshore delivery and an AI-native build?
Reveneau prices work per scoped build, quoted before it starts, rather than a per-hour rate. Offshore and nearshore delivery are typically priced as an hourly or day rate, which is the correct comparison only when the total hours are the main variable. Reveneau's rates are not published here because they are scoped to each build rather than fixed to a published price list.
How do I decide which model actually fits my project?
Ask which method actually matters for your build: lowering the price of an hour, or lowering the number of hours needed. A large, stable, well-specified programme favours offshore. A defined build with a high correctness standard favours fewer hours through generation and automated verification. Also ask what proves the work is correct, since that answer separates a supplier's process from its marketing.

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