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Reveneau vs a traditional software development agency

A traditional development agency sells you a team for a period of time, and the estimate is a headcount multiplied by weeks. An AI-native build sells you a defined outcome, because the implementation is generated rather than typed and the expensive part moves to specifying and proving it. Almost every practical difference between the two, from how a change request is priced to who pays for an underestimate, follows from that one structural difference rather than from anyone being better at engineering.

Facts about a traditional agency last checked 2026-08-21

  • An agency's cost is people multiplied by time, so its incentive is a longer engagement with more people on it.
  • An AI-native build's cost is dominated by specification and verification, not typing.
  • The honest question for either model is what happens when the estimate is wrong.
  • Agencies have depth we do not: established process, references, and a pool of available specialists.
  • Neither model protects you if what to build has not been decided.

Where a traditional agency is the right answer

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

What a traditional agency is good at

  • A track record you can check, with references from named clients
  • Many available specialists: for a niche platform, regulated domain, or legacy stack
  • Established process that has been tested with many clients
  • Scale, so a large programme can be staffed without the firm becoming the step that slows everything
  • Longevity: a firm that has existed for years is likely to be there for the maintenance

Choose them over us when

  • You need a supplier with a long, checkable history, which a new firm cannot offer
  • The work needs a rare specialism that a generalist team cannot learn responsibly
  • The programme is large enough that a pool of dozens of available engineers matters more than speed per change
  • Your procurement requires a vendor with a minimum trading history or turnover
  • You want the reassurance of references from companies like yours

Side by side

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

 ReveneauA traditional agency
What you are buyingA delivered outcome, not a person suppliedA team for a periodVerified
What drives the priceScope and how hard it is to verifyHeadcount multiplied by durationVerified
Who writes the implementationAI writes the implementation, on every engagementEngineers, increasingly with AI assistanceTheir claim
What proves it worksAn eval suite written from the specification, blocking the mergeCode review, QA, and their internal processTheir claim
A change mid-buildRe-scoped against the specification, priced before it startsUsually a change request billed as extra timeTheir claim
Who pays for an underestimateWe do, within the agreed scopeVaries by contract: time and materials puts it on youTheir claim
Track record you can checkNone yet. Reveneau is newUsually years of itVerified
What you get at handoverSpecification, eval suite, decision record, and runbookNot establishedNot established

How each one runs a build

StageReveneauA traditional agency
ScopingA specification precise enough to generate and test againstA statement of work and an estimate in person-weeks
StaffingA small team directing generationEngineers assigned from a pool of available staff
BuildingGenerated against the spec, blocked by evals until it passesWritten by the assigned team
QualityAutomated checks that block a mergeReview and QA, process varies by firm
Change requestsRe-specified, then re-generatedRe-estimated in hours

The comparison people expect here is "agencies are slow and expensive". That is not true as a general claim, it is unprovable, and a new company making it about an established industry deserves to be ignored. Here is the difference that is actually structural.

The unit you are buying

An agency sells time. The proposal is a number of people for a number of weeks, and whether it says so or not, the price is those two numbers multiplied. That model is honest and most of the industry has worked this way for decades. It also means the supplier's revenue grows with the duration and the headcount of the engagement, which is worth understanding rather than being cynical about.

An AI-native build sells a scoped outcome, because the cost structure underneath is different. When the implementation is generated, the labour is concentrated in deciding precisely what is wanted and in proving that what came back is right. Those are the parts we price.

Neither is morally superior. They fail differently, which is the useful part.

How each one fails

The agency model fails when the scope is unclear, because unclear scope becomes more weeks, and more weeks is more money for the supplier at exactly the moment the client is least happy. Good agencies manage this honestly. The incentive still works against the client, and everyone in the industry knows it.

The outcome model fails when the scope was defined badly, because we agreed to a result and the definition of that result turns out to be wrong. Then we are rebuilding at our own cost and under pressure, and the temptation is to argue that the request was out of scope. The protection against that is spending real effort on the specification before anyone builds, which is why this site talks about specification so much.

If what to build has genuinely not been decided yet, neither model protects you, and the right first purchase is a short discovery engagement from whoever you trust most.

What an agency has that we do not

A track record. That is not a small thing and we are not going to avoid it.

A firm that has been operating for a decade can show you work, put you on the phone with a client who had the same problem, and demonstrate that it will still exist when you need a change in eighteen months. Reveneau is new. We have engagement patterns and a published method, and we do not have a decade of references, because inventing them is the one thing that would make everything else on this site untrustworthy.

If a checkable history is what your decision needs, an established agency is a rational choice and you should make it.

They also have many available specialists. If your build needs someone who has spent years in a specific regulated domain or on an unusual platform, a firm with hundreds of engineers can put that person on it. A small team directing generation cannot create that experience, and pretending otherwise would be how a project goes wrong.

What actually changes with generation

Two things, and they are worth being precise about because most of the marketing in this market is not.

The first is that producing a first version became cheaper, for everyone. Agencies are adopting the same tools. Anyone claiming this as a unique advantage is describing the industry, not themselves.

The second is what most teams have not reorganised around: if code arrives faster than anyone can read it, the review step stops being a real control. The answer is to move verification into automated checks written from the specification, so that a change proves itself before a person ever looks at it. That is the actual difference in how we work, and it is why the eval suite rather than the AI is what this company sells. It is set out in full in eval-driven development.

The question to ask both of us

Whoever you are talking to, ask what runs automatically on every change, and what happens to a change that fails it. Then ask what happened the last time something reached a customer that should not have, and what changed in the pipeline afterwards rather than in the code.

The answers separate firms far more usefully than the agency-versus-AI-native framing does.

Where we fit

Reveneau suits this when

  • The scope is definable in enough detail to build and test against
  • The deadline is external and real
  • You would rather pay for a result than for seats
  • Correctness matters enough that automated verification is worth paying for

Common questions

What is the real difference between an AI development company and a software agency?
The unit being sold. An agency prices a team for a period, so the estimate is headcount multiplied by weeks. An AI-native build prices a scoped outcome, because generation moved the cost into specifying the work and proving the result. Most of the practical differences follow from that.
Is an AI-native firm cheaper than an agency?
We cannot tell you that honestly, because Reveneau has no completed engagements to average and any number would be invented. What we can say is that the cost structure differs: less of it is typing, more is specification and verification. Ask both suppliers what happens when the estimate turns out to be wrong, which is the question that actually predicts your final invoice.
Do agencies not use AI too?
Most do now, and anyone presenting that as a unique advantage is describing the industry rather than themselves. The differentiator is not whether AI writes the code, it is whether the verification was reorganised around the fact that code now arrives faster than anyone can read it.
When should I choose an established agency over a new firm?
An established agency wins when a checkable track record is what your decision needs, when procurement requires a minimum trading history or turnover, or when the work needs a rare specialism that only a large pool of specialists can supply. Agencies also offer scale, so a large programme can be staffed without the firm itself becoming the step that slows everything. Those are real reasons, and a new firm like Reveneau cannot answer any of them yet.
How are change requests handled differently?
An agency typically re-estimates the change in hours and bills the additional time. An outcome-priced build re-specifies it and quotes before work starts. The second is more predictable when scope is stable and more contentious when it is not, which is why the specification does most of the work.
What if I do not know exactly what I want built yet?
Then neither model protects you, and pricing either one is a guess presented as a plan. Buy a short discovery engagement first from whichever supplier you trust most, and treat its output, a specification precise enough to build and test against, as the thing you use to get a proper quote. Skipping that step is how both agency estimates and outcome quotes go wrong.
What should I ask both suppliers?
What runs automatically on every change, and what happens to a change that fails it. Then ask what happened the last time something reached a customer that should not have, and what changed in the pipeline afterwards rather than in the code. Those three questions separate serious firms from confident ones far better than asking either side to describe its methodology in the abstract.
How does pricing actually differ between the two models?
An agency prices headcount multiplied by duration: more people and more weeks means more revenue for the supplier. A Reveneau engagement prices a scoped outcome, quoted before work starts, because generation concentrates the cost in specifying the work and proving the result rather than in typing it. Neither structure is inherently cheaper; they price different things and fail in different places.
How is the project timeline set under each model?
A Reveneau engagement is scoped and quoted against a written specification precise enough to generate and test against, so the timeline follows from what was agreed rather than from a headcount estimate. An agency estimates in person-weeks from a statement of work. Both depend entirely on how clearly the scope was defined before pricing started, which is why specification work happens first either way.
Do we keep the code and IP?
Yes. A Reveneau engagement hands over the specification, the eval suite, a decision record, and a runbook alongside the code, so the reasoning behind the build is handed over with it. What an agency hands over at the end of an engagement is not established here and varies by firm, so it is worth asking any agency directly what documentation and rights transfer at handover.
Who is actually doing the work on each side?
A small Reveneau team directs generation: writing the specification, then reviewing what the eval suite reports on every change. An agency staffs engineers from a pool of available staff, increasingly with AI assistance of their own, and reviews their work through code review and internal QA. The difference is not headcount, it is where the verification step happens and what triggers it on each change.

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