About
Who is building this
newc0 is built by Rajiv Saxena. Twenty-five years in enterprise software: engineering large-scale systems, then product at the company that created the CRM category, then founding, selling and running software at scale. The product is shaped by that, and the site says which parts.
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Twenty-five years in enterprise software: engineering, then product, then founding and selling companies. Most of it spent on the systems sales and marketing teams actually run on.
| Role | Where | What it was | Bearing on newc0 |
|---|---|---|---|
| Engineering | Large-scale systems | Started in engineering, building large-scale systems. | Why newc0 generates from tested scaffolds and verifies every build rather than trusting output that looks right. |
| MBA | The Wharton School | Business degree, after the engineering years rather than instead of them. | Why the product is organized around company functions rather than around features. |
| Product Manager | Siebel Systems | Product management at the company that created the CRM software category. | Where the shape of a sales organization — pipeline, stages, forecasting, the data model underneath — became familiar. |
| Founder | ettache.com | Account aggregation, founded during the dot-com era. Acquired. | The first time the whole arc: build it, sell it, hand it over. |
| Product leadership | WebEx, acquired by Cisco | Eight years. Led product management for the line-of-business applications, a line at $180M annual recurring revenue. | What running software at real scale demands, and which decisions in a business genuinely cannot be delegated. |
| Founder | OnePgr | Go-to-market systems for sales and marketing teams. Building those, the team built the AI systems underneath them. | The work newc0 is made of. |
Why is newc0 built the way it is?
Because the failure modes are familiar ones. Software that demos well and does not hold together is an engineering problem, which is why every build here passes typecheck, tests, a production build and a smoke test before a founder sees it. Software that runs a business without asking anyone is a product problem, which is why the approval gate exists.
Twenty-five years of enterprise software mostly teaches you which decisions cannot be delegated. Pricing, positioning, anything binding, anything irreversible: those were the decisions that stayed with people at Siebel and at WebEx, and they are the ones newc0 queues for the founder rather than making on their behalf.
The rest of it — scoring leads, answering the same question for the hundredth time, reconciling invoices — is work that scale makes miserable for a person and trivial for software. That split is the whole product.
Where did newc0 come from?
It was internal tooling. The team was building its own products, and to do that at any speed with a small group it built an AI development system to write the code. The checks and balances came with it, because generated code that nobody verifies is a liability rather than an asset — and the team was shipping its own software on the output.
That is where the constraints in this product came from, and why they are structural rather than advisory. Generation starts from pre-built, tested scaffolds. The model proposes structured file edits and a deterministic executor applies them, so the model never touches a filesystem directly. Every build passes typecheck, tests, a production build and a smoke test before anyone sees it. None of that was designed to reassure a customer. It was designed because the team had to trust the output itself.
Using it long enough made the second half obvious. Once an application can be generated and verified reliably, the hard part is no longer building the software — it is running the company around it. That is where the agents and the trained models came in: the go-to-market work the team had already been doing for sales and marketing teams, pointed at the company the software had just produced.
newc0 is that system, brought to market. A founder gets what the team built for itself: software it was willing to run its own business on, and the workforce to operate it.
Why trained models rather than only language agents?
Because the go-to-market work required prediction, not just generation. Knowing which lead is worth a call, and what the pipeline is actually going to close, is not something a language model produces — it produces a confident sentence about it instead.
Two model domains are confirmed and named on the model library page, and no model count appears anywhere on this site, because a count with nothing browsable behind it is unverifiable.
What is this page not telling you?
Team size, funding, customer numbers, the legal entity and the founding date. None of them are confirmed on this site, so none of them appear on it. What is held back, and why, is listed in full on the claim sheet.
A career is context for why a product is built a particular way. It is not evidence that it works, and this page is not offered as any. The evidence is the verification chain, the named models, and the fifteen minutes a morning — a typical morning, not a guarantee — stated before you sign up rather than after.
Questions about the team
Who builds newc0?
- Rajiv Saxena, who has spent twenty-five years in enterprise software — engineering large-scale systems, an MBA from Wharton, product management at Siebel Systems, founding and selling a company during the dot-com era, and eight years leading product for a $180M ARR line of business at WebEx before it was acquired by Cisco.
Why should a founder trust a platform this early?
- On the evidence, not the biography. This site publishes what it can verify, states the scope of every number, and lists what it is deliberately not claiming. A career is context for why the product is built the way it is. It is not a substitute for the product working.
How big is the team?
- Not published. newc0 does not publish a team size, a funding figure, a customer count or a founding date, because none of them are confirmed on this site yet. They appear on the claim sheet the day they are, and not before.