Should you hire a team to build your MVP or hand it to Praetorix Foundry? Run the same defined MVP through both models in a month-by-month worksheet that shows the figures each one actually produces. Then use the decision matrix to match your own situation to one of three common scenarios.
Every cost comparison we’ve seen collapses at the same point: someone puts a salary table next to a partner quote and calls that a decision. Salaries aren't outcomes. A quote isn't an outcome either. What you're buying in both cases is a launched product that tells you whether anyone wants it, and a team that can keep working on it afterward.
So fix the outcome first. One scope with one definition of launched, and a date by which you need evidence at the decision point. Then price both paths against that fixed target.
Compare the cash and the calendar against identical outcomes. Everything in this article hangs on that.
Build the worksheet twice, once per model, with months M0 to M6 down the side and four columns across: cash out, internal hours at loaded cost, weeks of delay introduced, and commitments remaining at the decision point. The fourth column is where most comparisons quietly cheat, because a signed employment contract and a finished engagement are not the same obligation. Every cell below is a labelled assumption or a placeholder. Replace each one with your own number and copy the structure.
| Month | Cash out ([your number]) | Internal hours × loaded rate ([your number]) | Weeks of delay introduced ([your number]) | Commitments remaining if you stop here ([your number]) |
|---|---|---|---|---|
| M0 | ||||
| M1 | ||||
| M2 | ||||
| M3 | ||||
| M4 | ||||
| M5 | ||||
| M6 (decision point) | ||||
| Total |
| Line item | In-house: what to enter | Partner: what to enter |
|---|---|---|
| Recruiting and hiring | Cost per hire × roles, in the months searches run | Usually none; note any sourcing fee |
| Engineering | Loaded salary × months × headcount | Scoped engagement fee (from the discovery call) |
| Design | Hire, contractor or “not costed” (flag it) | Included in scope or quoted separately: check |
| QA | In-house role or “not costed” (flag it) | Included in scope or quoted separately: check |
| Product leadership | In-house role or “not costed” (flag it) | Your product owner’s hours at loaded cost |
| Ramp-up on your domain | Months to productivity × loaded cost | Partner’s ramp-up on your domain: ask how it is billed or absorbed |
| Cloud setup | One-off setup effort, not just the monthly bill | One-off setup effort, and who does it |
| Cloud run cost | Monthly cost from your architecture | Same: it stays yours in both models |
| Equipment and software | Laptops, licences, tooling per head | Usually the partner’s: confirm what you license yourself |
| Management overhead | Existing leaders’ hours on hiring and onboarding | Your hours on reviews, questions and approvals |
| Knowledge transfer at handover | Internal documentation hours | Handover effort and documentation quality: check scope |
| Cost of stopping mid-engagement | Notice periods, severance, idle capacity | What you owe under the termination terms |
| Cost of keeping capacity after the decision | Salaries continue while you decide | Extension or continuation terms, if you proceed |
Fill it with your own numbers. Published bands exist to orient you. Praetorix Foundry’s MVP Sprint band of $25k-$80k over 6 to 10 weeks is a starting point that the free discovery call turns into a scoped price, and an internal build has no published band at all until you’ve priced your specific roles.
Three rules keep the worksheet honest:
Record cash in the month it leaves the account
Count internal hours at loaded cost, which includes the product decisions nobody bills for
Put a dollar figure on each week of delay, because waiting has a price even when nothing is spent
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Book a Discovery Call →The MVP scope definition is the shared object both estimate price. Write down the feature list with the platforms and integrations you must have on day one, and set the quality bar for defects and performance along with the acceptance criteria you'll test against. Then write the exclusion list, which matters more than people expect.
Why does the exclusion list carry so much weight? Pendo’s 2019 analysis of 615 Pendo customer subscriptions found that 80 percent of features in the average product were rarely or never used. Every feature you exclude in writing is one you don’t pay to build, test, and maintain.
Assign the product decisions by name. Who approves the scope, and who has the authority to cut a feature in week six. The MVP scope definition is worthless if three people each believe they own it.
Start with what it costs to get the team through the door. SHRM’s benchmarking puts the average cost per hire at nearly $4,700, across all roles. Hiring time varies by role: SmartRecruiters reports a median of 48 days to hire at technology companies, across all roles, which is 26 percent slower than the global median across industries. Check your own searches against that figure rather than assuming it.
Then price the people. The U.S. Bureau of Labor Statistics put the median annual wage for software developers at $135,980 in May 2025. For private industry workers, wages accounted for 70.3 percent of total compensation in March 2025, which puts one median developer near $193,000 loaded before you’ve bought a laptop. Treat that as an approximation: your own benefits quote is the better input. Multiply across product leadership and engineering, and the in-house side gets large fast.
Three line items get left off almost every internal estimate:
Ramp time, since Gallup's experience suggests new employees need around 12 months to reach peak performance
Management overhead, meaning the hours your existing leaders spend hiring and onboarding
Unallocated capacity, meaning the weeks a backend engineer waits on design, which you pay for in full
Design, QA and product leadership are often assumed to be in-house roles and left uncosted. Cloud setup, equipment and software, and the cost of retaining or releasing capacity if the plan changes (notice periods, severance) each get their own row in the worksheet above.
A partner engagement prices differently because the commitment is shorter. Praetorix Foundry’s discovery is a free call that sets scope and price, and the scoping work itself is part of the MVP Sprint. The fee covers the scoped work, and change requests cover what you add once you see the product running. The MVP Sprint covers scope and user flows through design and the frontend and backend build, plus documentation and handover.
What a fee doesn't cover is your side of the work. Your product owner still has to answer questions and make the calls that only you can make. Budget those hours at loaded cost, the same way you did for the internal team, because they're real and they're the most common reason a scoped engagement slips.
Give the partner side the same scrutiny as the internal side. Three costs belong in the worksheet:
The partner’s ramp-up on your domain, which is either billed or absorbed into the scope
Knowledge transfer at handover, including how much of it your own team must do to take over
What you owe if you stop mid-engagement, which depends on the termination terms you sign
Cloud costs stay yours in both models. One rough benchmark for seed-stage products with real users is $300 to $1,500 a month on AWS, from a vendor blog. A better input is to price your own architecture in the AWS Pricing Calculator. Post-launch support is a separate commitment you either buy or staff internally, and pretending otherwise distorts the whole worksheet.
Tell us about your idea. 24-hour response. NDA-friendly.
Book a Discovery Call →The worksheet tracks spending. This section tracks the thing you’re actually buying, which is evidence. Eric Ries calls it validated learning in The Lean Startup: demonstrating empirically that a team has discovered valuable truths about a business’s prospects. That’s the output your decision point depends on.
Now put the two models on the same calendar. If you are hiring every role from zero, the internal path spends its first stretch recruiting, then its next stretch onboarding people who are competent but new to your problem, and no learning begins while the requisition is open. A partner path can start discovery in week one, though it carries its own ramp-up on your domain. If your comparison treats those timelines as equivalent, it’s measuring the wrong thing. If you already have people with the right skills and context, the gap narrows or disappears.
Cheap evidence beats expensive evidence. Where the riskiest question is whether an AI feature works, Praetorix Foundry runs an AI Pilot at $9.5k-$25k for one AI use case over 2 to 4 weeks, and the firm’s own position on a failed pilot is blunt: “Then the pilot did its job, at a fraction of what a full build would have cost to learn the same thing.” CB Insights analyzed 431 VC-backed shutdowns since 2023. Among the 385 where a failure reason could be identified, poor product-market fit accounted for 43 percent, with running out of capital the final cause. Learning late is the expensive failure mode.
Unclear decision rights produce rework in both models, and rework is the cost line nobody forecasts. A feature gets built, and a stakeholder sees it, then the requirement changes and the team rebuilds. That churn is invisible in a salary table and invisible in a quote.
Marty Cagan, founder of Silicon Valley Product Group, argues that product teams should own the solution to a problem rather than just deliver a feature list. Read that as a split of roles: the client owns the problem and the decisions, and the delivery team, whether a partner or an in-house engineering team, needs room to propose the solution. That split has to be written into the MVP scope definition rather than discovered in week five.
There are client commitments no supplier can take over. Access to your customers and your internal data about how the work gets done today, along with a decision-maker who answers within a day and a willingness to cut scope when evidence says so. Where those commitments are weak, both models produce the same outcome of churn and duplicated work as cost factors drift every sprint upward.
Launch is the start of the larger half of the spend, if the product lives. Software maintenance is commonly cited at 60 to 80 percent of total cost over the life of systems that run for years. An MVP that stops never reaches that figure, but one that proceeds will, so price the continuation before you sign the first engagement.
An internal team carries the knowledge forward and absorbs support naturally, which is the honest advantage of hiring. It also carries risk. Mercer’s survey put average U.S. voluntary turnover at 9.9 percent for white collar professionals in 2025 (13.0 percent across all industries). On a four-person MVP team, a single departure still means losing a quarter of everything nobody wrote down.
A partner engagement makes continuity a contract question instead of a retention question. The variables that matter are handover quality and documentation that someone other than the author can follow. Both paths work. Your cost factors after launch depend on which risk you'd rather manage, and the honest answer differs by company.
Run the worksheet three times, because the decision point has three possible answers and they produce different bills.
If the MVP proceeds, the internal team is already hired and ramped and ready to keep building, which is where hiring starts to repay itself. The partner path needs an extension or a continuing arrangement, and you should price that before you sign the first engagement rather than after. For ongoing work, Praetorix’s Product Partner engagement is the option to price.
If the product changes direction, the internal team carries a headcount shaped around the old plan. Retraining or reassigning people can take months, depending on how far the new direction is from their skills. If the scope you wrote at the start is still the shared reference, a partner engagement can be rescoped as a conversation instead of an argument, though change requests have a price.
If the MVP stops, the asymmetry can be sharp. Employment commitments continue past the decision as idle capacity accrues, and winding down costs real money (notice, severance). A finished engagement ends; you keep the code and the evidence, and what you owe depends on the termination terms. If you stop, that gap can be the largest variable in your model, and it only shows up if you model the stop case honestly.
Match your situation to the closest row, then check it against your own worksheet.
| Your situation | Time to first evidence | Cash to the decision | Commitments left if it stops | Continuity after launch | What you must provide |
|---|---|---|---|---|---|
| Complete team available today | Fast: no hiring or ramp-up | Low new cash, but count the work the team sets aside | Low: no new commitments | Strong: knowledge stays in-house | Decide whether that displaced work is worth less than the MVP |
| Hiring every role from zero | Slower: recruiting and onboarding come first | High before any evidence, if you hire first | High: employment commitments and notice | Strong once the team is built | Budget for hiring and ramp-up, and a clear definition of launched |
| Product ownership stays with you, delivery doesn’t | Starts at discovery, plus the partner’s ramp-up on your domain | Scoped fee plus your own hours | Lower: per the termination terms you sign | Depends on handover quality and any continuation | Customer access, internal data, a product owner who decides within a day |
If your team is fully available today, build internally when the work they would put aside is worth less than the MVP. If you are hiring every role from zero, a partner can reach evidence sooner, and hiring later against proof can be cheaper than hiring now against a guess. Build internally from the start if your roadmap is long and certain, since a team you will keep for years amortizes its hiring and ramp-up cost. In the third case, Praetorix Foundry fits because the engagement is built for clients who keep the problem and the decisions while a delivery team builds. You still own the product decisions, customer access, internal data, and the scope sign-off.
Praetorix Foundry’s discovery call is free and sets the scope and price of your MVP Sprint, which includes documentation and handover. Book a discovery call, and we’ll price your MVP development cost against your actual scope.
Tell us about your idea. 24-hour response. NDA-friendly.
Book a Discovery Call →Value internal time at its loaded hourly cost, including salary and benefits, plus the hours spent making product decisions. Record those hours by month rather than treating them as free capacity. This gives the mvp development cost comparison a fair basis against partner invoices and exposes delays caused by unavailable staff.
The client should name one decision-maker before work starts and set a response time for questions. That person approves scope changes and resolves conflicting feedback. They can also remove a feature when evidence is weak. Without this authority, the delivery team waits or rebuilds work, which increases cost in either model.
Yes, but post-launch work should be priced as a separate commitment unless the agreement states otherwise. Ask whether support covers bug fixes, infrastructure monitoring, and new features, then define response times and ownership. This keeps launch pricing separate from the continuing cost of operating and changing the product.
Collect evidence tied to the decision you wrote before development, such as activation or repeat use, then record the sample size and test period. Set an action for each result before reviewing the data. A result without a pre-agreed response leaves the team debating opinions instead of deciding from evidence.
Hire after the evidence supports continued investment and the roles are clear. Use the tested product to define the skills and next milestone, then compare permanent headcount with a partner extension. This avoids building a full team around assumptions while preserving a path to internal ownership.
Tell us about your idea. 24-hour response. NDA-friendly.
