Spec Driven Development
Why Australian Dev Teams Are Moving Beyond Agile in 2026
Software development is undergoing its biggest transformation since Agile. And Australian organisations that don't adapt risk being left behind.
The shift isn't subtle. At OpenAI — one of the companies building the AI tools reshaping our industry — they've discovered something that should concern every CTO and engineering leader:
"The performance difference is like 10x by any way that you measure it — whether lines of code, commits, or business impact. The people who aren't adopting it are now 10 times less productive at performance review time... you panic. You actually go to HR and you go to legal and you're like, what are our options here?"
— Steve Yegge, speaking on the Latent Space podcast. Yegge led Amazon's Developer Infrastructure teams during the company's platform transformation, built Google's internal code intelligence platform (Grok), and managed teams of up to 150 engineers across 19 years at both companies.
This isn't speculation from the sidelines. This is what's happening inside the organisations building these tools.
The Data Behind the Shift
McKinsey's research tells the same story. In late 2025, Martin Harrysson (McKinsey's Global Leader for AI Software Engineering) and Associate Partner Natasha Maniar presented findings from a survey of nearly 300 publicly traded companies.
The headline: individual productivity gains are substantial, yet company-wide improvements average only 5-15%.
Why the gap? Most organisations are bolting AI tools onto existing processes. The top performers are doing something different — they're rebuilding how development works from the ground up.
What top performers look like:
7x more likely to have AI-native workflows across four or more development use cases
6x more likely to operate with smaller, specialised pods instead of traditional teams
5-6x faster time to market with higher quality output
51% increase in code mergers with improved efficiency
The common thread? These organisations have moved from story-driven development to spec driven development — where product managers iterate specifications with AI agents rather than writing lengthy PRDs that developers then interpret.
What Is Spec Driven Development?
Spec Driven Development (SDD) inverts the traditional approach. Instead of developers writing code line by line, teams invest upfront in detailed specifications. AI agents then generate the implementation.
Think of it as a pyramid:
Specification — What you want to build and why
Technical Plan — Architecture, constraints, and approach
Task Breakdown — Actionable instructions for AI agents
Implementation — AI generates code from detailed briefs
At each layer, you add context. By the time instructions reach the AI agent, they're precise enough to produce consistent, high-quality output.
The result: AI builds micro-components with precision. You assemble them into complete solutions.
This isn't theoretical. GitHub released Spec Kit in September 2025 as an open-source framework for exactly this approach. It has quickly become the industry standard.
The End of the 10-Person Sprint Team
McKinsey's research points to a fundamental restructuring of how teams operate.
The old model: 8-10 person teams working in two-week sprints with quarterly planning.
The emerging model: "One-pizza pods" of 3-5 people with continuous planning, where engineers orchestrate AI agents rather than writing every line of code.
Harrysson and Maniar found that 70% of surveyed companies have not yet changed role definitions — creating friction as tools evolve faster than organisational structures.
The teams seeing the biggest gains have made deliberate changes:
Engineers transition from code execution to orchestrators managing agent workflows
Product managers create direct prototypes instead of documentation
Business analysts work closely with AI engineers on specifications
Two people — a business analyst and an AI engineer — can accomplish what previously required a larger team. The business analyst owns the functional requirements and specifications. The AI engineer validates, executes, tests, and refines.
The Australian Context
Australian organisations have invested heavily in software capability. IT spending was to grow 7.8% in 2025 according to Enterprise Monkey's analysis — that wasn't inflation, it was organisations doubling down on software to drive business outcomes.
The numbers on AI adoption tell the story:
85% of developers now regularly use AI tools for coding (IT Pro)
92% report using AI-assisted coding, saving an average of 7.3 hours per week (Channel Life Australia)
65% of senior developers believe their roles will be redefined this year (Channel Life Australia)
84% of Australian executives are willing to allocate more than half of their IT budget to innovation (Enterprise Monkey)
But adoption alone isn't delivering results. As McKinsey found, bolting AI tools onto existing Agile processes produces marginal gains. The organisations pulling ahead are the ones rethinking their operating model entirely.
The No-Regrets Approach
One of the underappreciated benefits of spec driven development: it's genuinely iterative without the traditional cost of rework.
If AI-generated output isn't right, you don't start from scratch. You rewind, improve the specification, and ask the agent to regenerate. Unlike traditional development where rework compounds, SDD makes iteration low-cost.
Refine your brief. Regenerate the code. Move forward.
This changes the risk profile of software projects. You can course-correct without significant sunk cost.
What This Means for Developers
The developer role is transforming from writing every line of code to becoming a system architect and AI orchestrator — breaking down complex challenges and coordinating multiple agents.
This isn't a threat. It's an opportunity.
The developers who learn to work effectively with AI agents will thrive. Those who compete with AI on code output will struggle. Steve Yegge's observation about 10x productivity differences at performance review time should be a wake-up call.
The skills that matter now:
Translating business requirements into precise specifications
Understanding technology stacks deeply (even if you're not writing every line)
Orchestrating AI agents effectively
Validating and testing generated output
How Hypergen Uses Spec Driven Development
At Hypergen, we've adopted spec driven development for our client projects. It's not an experiment — it's how we build.
The approach lets us deliver faster while maintaining quality. We invest time upfront in specifications, use AI agents for implementation, and focus our expertise on architecture, validation, and the problems that genuinely require human judgment.
For our clients, this means:
Compressed delivery timelines
Consistent quality from detailed specifications
Lower risk through the ability to iterate and regenerate
Solutions that are well-documented from day one
We're building our business on this methodology because we've seen the results firsthand.
Training for Enterprise Teams
For organisations looking to adopt spec driven development, we offer hands-on training that takes participants from concept to working application in a single day.
What we cover:
Why spec driven development outperforms traditional approaches
Writing specifications that AI agents can execute effectively
The GitHub Spec Kit workflow and tooling
Generating technical plans and task breakdowns
Running AI agents against specifications
Testing, validating, and iterating on generated components
Participants leave with practical experience they can immediately apply — not just theory.
Prerequisites:
A paid AI coding agent subscription (Claude Code Max, GitHub Copilot Pro+, or similar tier)
Command-line access (PowerShell, Terminal, or preferred CLI)
A Git repository for saving work throughout the day
The Bottom Line
The evidence is clear. Spec driven development isn't a trend — it's the next operating model for software teams.
McKinsey's research shows top performers achieving 5-6x faster delivery. Steve Yegge describes 10x productivity differences showing up in performance reviews. GitHub has released open-source tooling. The methodology works for both greenfield projects and existing codebases.
Australian organisations have a choice: continue with incremental AI adoption and marginal gains, or restructure around the approach that's delivering step-change improvements.
The companies that move now will have a significant advantage. The ones that wait will spend the next few years catching up.
Sources
McKinsey: Moving away from Agile — Martin Harrysson & Natasha Maniar
Enterprise Monkey: Software Development Trends Australia 2025
Channel Life Australia: AI to reshape software developer roles by 2026
Ready to Get Started?
Whether you're looking to adopt spec driven development for your projects or upskill your development team, we can help.