The two roles
What’s the difference between a fractional CTO and an interim CTO?
A fractional CTO covers an ongoing need that doesn’t fill a week: 1 to 3 days a week, from a few months to more than a year.
An interim CTO fills an empty seat for a set period: more hours, shorter engagement, a clear goal — steady the team, then onboard a successor.
What about fixed-price projects?
Technology assessment, AI exploration, POC, MVP: a specific question, with deliverable, timeline, and price set up front. A fixed-price project delivers a result, then ends. It doesn’t replace technical leadership: if you need someone to lead the team over time, that’s a CTO role. See fixed-price projects
How is that different from a consultant?
A consultant recommends. A CTO decides, leads the team, and answers for the results. Monolithic Lab takes the role, with the mandate that comes with it.
Or from a freelancer or an agency?
Freelancers and agencies write code. A CTO decides what to build, how, and with whom, and manages the people building it, vendors included. If all you need is development capacity, a freelancer or an agency will cost less.
Does Monolithic Lab write code?
Yes, with AI agents: prototypes, analysis of existing code, internal tools, automation, MVPs. A CTO who can no longer build can no longer judge what the team and its agents produce. The role is leadership; hands-on practice makes it credible.
Who it’s for
What kind of company?
Small and mid-sized companies and scale-ups, typically 10 to 100 people, whose product or operations depend on technology. Led either by a technical founder who’s stretched too thin, or by a non-technical founder who needs a technical counterpart they can trust.
When is it the wrong answer?
- when all you need is development capacity
- when the engineering team is several dozen people and needs a leader there every day
- when leadership isn’t ready to hand over a real mandate: a CTO with no authority to decide is useless
Cadence, length, pricing
How many days a week?
Fractional: 1 to 3 days. Interim: often close to full-time at the start, then tapering off.
How long does an engagement last?
Fractional: from a few months to more than a year. Interim: long enough to hire and onboard the successor, usually a few months. Fixed-price projects: timeline set up front; 2 to 8 weeks for an assessment.
On site or remote?
Both. The first phase works best on site, close to the team. After that, the split depends on your needs.
How much does it cost?
CTO roles are billed on time, based on cadence. Fixed-price projects have a fixed price. Either way, a written proposal with a firm price follows the first conversation. At the same cadence, a fractional CTO costs a fraction of an in-house CTO, with no recruiting fees and no notice period.
Hiring and the team
Can Monolithic Lab hire our future CTO?
Yes, and it’s often how the engagement ends: defining the profile, joining the interviews, then supporting the new CTO’s first weeks.
What if we hire a CTO mid-engagement?
That’s a good outcome. The engagement turns into a handover, then ends.
How does it work with the existing team?
The team stays yours. The CTO leads it, helps it grow, and prepares an internal lead to take on more responsibility where possible.
Confidentiality and independence
Can we sign an NDA?
Yes, from the first conversation if needed.
Does Monolithic Lab take commissions?
No. No partnerships with software vendors, integrators, AI providers, or recruiting firms. Every recommendation serves your company alone.
AI transformation
Is AI only for the engineering team?
No. Developers are changing how they work with coding agents, but the gains are often just as fast elsewhere: customer support, sales, finance, operations, HR. The transformation covers the whole company. AI transformation in detail
What’s a forward deployed engineer, and how does it relate?
An engineer who works inside a client’s teams to turn a loosely defined problem into a system that runs in production. The model comes from Palantir, and both OpenAI and Anthropic use it to deploy AI at their customers. Monolithic Lab takes its cue from it: on site, on your data, judged on real usage. Read the article
Do you have a ready-made method?
No, and that’s deliberate. AI is new, and few companies have deployed it successfully in a real transformation. The adoption plan gets built with your teams, starting from their work: map, prioritize, test on real work, deploy, hand over.
Where to start?
With a fixed-price AI exploration if the question is “where can AI help us?” With a CTO role if the transformation needs to be led over time, along with the rest of technical leadership.