No PM. No BA.
Your developer runs the show.

Every outsourcing company will tell you they use AI. Most of them mean their developers have GitHub Copilot installed. That's not what we mean.

AI has changed what a single developer can do. It hasn't just made coding faster — it has made it possible for one person to understand business context, define priorities, write user stories, manage scope, and still ship working software. The roles that used to sit between the client and the developer — project managers, business analysts, QA leads, product owners — existed because no one person could hold all of that. AI changed that equation.

We took that seriously. We restructured how we work around it.

Your developer is your product owner

In a traditional setup, you explain your business to a project manager. The PM translates it for a business analyst. The BA writes requirements for a developer. The developer writes code. Then a QA team checks if it matches the requirements they never wrote.

Every handoff loses context. Every layer adds cost. And at the end, the person who wrote the code often has no idea why they built what they built.

We don't work that way. At Core70, your developer talks to you directly. They understand your business — not just the ticket. They define what to build, in what order, and why. They challenge priorities when something doesn't make sense. They protect your budget by saying "this isn't worth building right now" — and meaning it.

This is what we mean by "product owner." Not a separate role. A core capability of every developer on our platform. They maintain your backlog, prioritise by business value (not technical difficulty), evaluate ROI with AI tools, and ensure every sprint delivers something your business actually needs.

Can every developer do this? No. That's why we're selective. The developers who thrive in our model are the ones who were already doing this work — understanding the business, pushing back on bad requirements, thinking beyond the code — they just happened to also be writing code. AI freed up enough of their time to do both properly.

The roles we removed — and why

This isn't about cutting costs by removing roles. It's about building developers who think end to end — from understanding the problem to delivering the solution — with nothing lost in translation.

AI is not a feature. It's the engine.

Every outsourcing company says "we use AI." Most of them mean their developers have GitHub Copilot installed. That's a tool. What we've built is a fundamentally different process — AI doesn't assist our workflow, it powers every stage of it.

Here's what that looks like in practice:

Requirements & discovery: When you describe your business problem, AI captures and structures the conversation in real time — extracting key requirements, identifying missing pieces, and generating a structured brief. What used to take three meetings and a week of documentation happens in one session.

Rapid prototyping: Before writing production code, we use AI prototyping tools to generate clickable, interactive prototypes from your business description. You can see and test your idea within days — not weeks. This means you validate direction before committing budget, and we can iterate on design in hours rather than sprint cycles.

Architecture & planning: AI analyses your requirements against technical options, generates architecture proposals, decomposes work into tasks, and estimates complexity. Your developer reviews, challenges, and makes the final calls — but the analytical heavy lifting is done.

Development: AI coding agents (Claude Code, Cursor, Copilot) generate routine code, handle boilerplate, and implement standard patterns. Your developer focuses where humans are irreplaceable: complex business logic, system architecture decisions, and integration challenges. The result is 2–3x faster delivery on standard features.

Testing & quality: AI automatically generates test cases covering core flows and edge cases, runs security scans, and reviews code for vulnerabilities. Test coverage that would take days to write manually is generated in minutes.

Documentation: API docs, user guides, and technical documentation are generated automatically and stay in sync with the codebase — they never go stale.

Change impact analysis: When requirements change (and they will), AI analyses the ripple effects across the codebase in hours, not days. You get an accurate assessment of cost and timeline impact almost immediately.

Beyond day-to-day use, we apply two structured AI-driven development modes:

Plan-Build: AI helps architect the solution, decompose tasks, and plan the implementation path before a single line of code is written. Then the developer executes with precision.

AI Agent Teams: Multiple specialised AI agents work in coordination — handling requirements analysis, architecture design, coding, testing, and review as a collaborative workflow. The developer orchestrates, validates, and makes the final calls.

This is why one Core70 developer can do what traditionally required a team of five. And it's why our pricing works — AI compresses the total hours needed, so even at competitive hourly rates, your total project cost is dramatically lower than traditional agencies.

The developer's irreplaceable value concentrates in two areas: architecture decisions — how the system is structured, what technical trade-offs to make, where the security boundaries sit — and business understanding — judging whether what was built actually solves the business problem. These require deep knowledge of both the technology and your business. AI can't do either well. Your developer can.

Your developer protects your budget

This is the part most outsourcing companies won't tell you: the traditional model has a built-in incentive to build more, not less. More features mean more billable hours. More complexity means more people needed. Nobody in the chain is rewarded for saying "don't build this."

Our model inverts that. Because your developer understands the business context — not just the technical requirements — they evaluate every request against actual business value. "Is this worth the investment?" is a question they ask before every sprint, not after.

"Not now" is a frequent and correct answer. Your developer must have the courage to tell you "this isn't worth building" — because they're thinking about your budget, not their utilisation rate.

What about security?

Every AI tool we use meets security compliance requirements. None of them use your code, requirements, or business data for model retraining. If a client has specific restrictions on AI usage, we comply without exception.

All team members sign NDAs before accessing any client information. Client data stays in the client's environment wherever possible. When development requires client data, we use anonymised or synthetic data. When the engagement ends, all client data, credentials, and code are deleted from our systems — confirmed and signed off by the Account Owner.

Confidentiality obligations are permanent. Your business information, technical architecture, and product plans are treated as confidential — during and after the engagement, without exception.