AI Software Development Costs in 2026: What CRED's 90% AI Code Shift Means
CRED's founder revealed that AI now writes 90% of the company's code. Here's what falling AI software development costs mean for non-technical founders in 2026.
In September 2026, CRED founder Kunal Shah dropped a reality check every non-technical founder should hear: artificial intelligence now writes roughly 90% of the fintech unicorn's code. This isn't a future projection — it's happening right now inside one of India's most valuable startups.
If AI is carrying that much of the workload for a $4.5 billion enterprise, ask yourself a direct question: why are your AI software development costs still anchored to 2023-era billable hours?
The baseline for software engineering has shifted for good. Paying armies of junior developers to hand-type boilerplate is no longer necessary — yet many traditional agencies quietly use AI to speed up their own workflows while still billing clients for weeks of manual labor.
This guide breaks down how AI is reshaping the economics of building a product, why the Build-Operate-Transfer model is the most transparent way forward, and how you can use these shifts to demand better outcomes from your technology partner.
The CRED Revelation: AI Code Generation Tools Are Rewriting the Baseline
Speaking on a recent podcast, Shah revealed that CRED's reliance on AI for code generation jumped to 90% — up from just 5% a year earlier. The more telling part of his observation wasn't the volume of code, but the human impact: roughly 10% of tech employees, he said, are becoming a "completely different species" in terms of productivity.
That 10x productivity gap is splitting software engineering into two tiers:
- The Orchestrators — senior architects and product-focused engineers who use AI to generate, test, and deploy code rapidly, while focusing on system design, security, and business logic.
- The Typists — traditional developers who still treat their job as writing syntax line by line.
For a non-technical founder, this is the market dynamic to understand. If your software partner staffs your project with "typists" and bills by the hour, your capital is going toward outdated workflows.
The Truth About AI Software Development Costs in 2026
To see how far costs and timelines should be dropping, look at enterprise-level data. McKinsey & Company reports that organizations successfully running "agentic" AI workflows in product development are seeing striking results — in one case involving a major global bank, overnight AI agent teams delivered updates and tested failure paths "10 times the speed at half the cost."
McKinsey's 2026 data also shows the top 20% of software engineers experiencing AI-driven productivity growth averaging 55%.
In practice, a feature set that once took a five-person team three months to build can now be architected and delivered by a two-person team of senior orchestrators in three weeks. If your agency isn't passing these efficiencies down to you, they're capturing the margin. The real cost of building custom software is falling fast — but only for founders who structure their vendor engagements correctly.
How to Reduce Software Agency Costs Without Compromising Quality
The key is genuine software outsourcing efficiency: moving away from "Time and Materials" contracts that reward slow, manual coding, toward value-based, outcome-driven engagements.
Here's how a traditional outsourcing model compares to a modern, AI-native partnership:
| Metric | Traditional Software Agency | AI-Native Partner (BOT Model) |
|---|---|---|
| Billing Structure | Hourly/Monthly per developer head | Milestone/Value-based delivery |
| Tooling Transparency | Opaque (Agencies hide AI use to protect billable hours) | Transparent (AI is leveraged openly to accelerate delivery) |
| Team Composition | Heavy on junior/mid-level coders | Heavy on senior architects, product managers, and AI agents |
| Time to Market | 6 to 9 months for an MVP | 2 to 3 months for a mature V1 |
| End Goal | Perpetual retainer dependency | Transfer of IP, codebase, and operational knowledge to your in-house team |
To genuinely reduce software agency costs, incentives have to align. That's why Ganakys runs on a Build-Operate-Transfer (BOT) model: we act as your temporary, elite in-house engineering team, using top AI code generation tools to build your product quickly, operate it to stability and market fit, and then transfer the entire operation to your permanent team. There's no incentive to string you along with inflated billable hours.
Architecture vs. Typing: Why the "Who" Still Matters
It's tempting to read Shah's 90% figure as proof that engineers are becoming obsolete. That's a trap.
AI code generation tools — GitHub Copilot, Cursor, and emerging enterprise agents — are excellent at writing isolated functions, generating boilerplate, and translating between languages. Gartner projects that 90% of enterprise software engineers will use AI code assistants by 2028.
But AI doesn't understand your business model:
- It doesn't know why an onboarding flow converts better for a rural Indian demographic than a global B2B client.
- It can't weigh the trade-offs between cloud hosting costs and latency requirements.
- It can't design a secure, RBI-compliant data architecture without rigorous human direction.
As writing code becomes commoditized, system architecture, product judgment, and security validation become more valuable, not less. The human role has shifted from construction worker to urban planner — you need a concentrated pod of domain experts and senior architects, not a large team of coders. See how we structure these pods in our engagement models.
The New Economics of Custom Software Pricing India
India has long been the global hub for software outsourcing, driven mainly by labor arbitrage — the wage gap between the West and the subcontinent. AI is changing that math for custom software pricing India.
When code is generated instantly, the wage gap of a junior developer matters far less. The new arbitrage is intelligence and operational execution.
A 2026 NASSCOM report projects global AI spending in the software development life cycle (SDLC) will nearly triple to $630 billion by 2028, transforming every phase of delivery — from requirements and design to automated testing and self-healing deployments.
For global founders and Indian SMEs, this means India stays the top destination for software development — not because you can hire ten people cheaply, but because top Indian engineering teams are among the fastest adopters of agentic AI workflows globally. Partnering with an India-first, AI-native technical team gets you world-class architectural talent at a fraction of Silicon Valley cost, supercharged by AI efficiency.
Demand More From Your Software Partner
As a non-technical founder with a domain-expert vision, you have more leverage today than ever. Audit your current or prospective tech partner with these questions:
- "What's your policy on AI code generation tools?" If they say they don't use them, they're either protecting billable hours or technologically behind. Either way, that's a red flag.
- "How are AI-driven efficiencies reflected in your pricing?" If timelines and costs look identical to a 2023 proposal, you're overpaying. Push for milestone-based pricing that reflects modern development speed.
- "Who's architecting the system?" Make sure you're paying for senior oversight and product strategy, not just bodies in seats.
- "What's the path to independence?" Agencies profit from lock-in — ask how they plan to hand the keys back to you. (See how we handle this in our case studies.)
Stop Paying for Keystrokes. Start Paying for Outcomes.
CRED writing 90% of its code with AI isn't a quirk of one well-funded unicorn — it's becoming the standard for modern software development. Your capital should go toward acquiring users, refining your business model, and scaling operations, not subsidizing manual typing.
If you have a product idea or a legacy system and lack an in-house team to capitalize on this shift, don't settle for traditional outsourcing. Request a BOT engagement with Ganakys, and build your product at the speed of 2026.
Frequently Asked Questions
How do AI code generation tools affect the final cost of an app?
By automating repetitive coding, testing, and deployment, AI tools can cut build time by 40–50%. A transparent partner passes those savings directly to you, lowering the capital required to launch an MVP or enterprise product.
Is AI-generated code secure enough for fintech or healthcare?
AI models generate code from patterns, which can sometimes include outdated or insecure snippets — exactly why senior human architects matter more than ever. AI should generate the code; a senior engineer should validate, secure, and deploy it. Properly overseen, AI-assisted code is highly secure and compliant.
Will I still need a technical co-founder if AI writes the code?
AI writes code; it doesn't build businesses. You still need technical leadership for decisions on cloud infrastructure, data privacy, third-party integrations, and scaling architecture. Without a technical co-founder, a Build-Operate-Transfer partner can fill this role until you're ready to hire an in-house CTO.
What is the Build-Operate-Transfer (BOT) model for software?
A specialized partner builds your product with an elite team, operates it in the live market to ensure stability and traction, then transfers the IP, codebase, and operational knowledge to your in-house team when you're ready. It removes the permanence and lock-in of traditional outsourcing.