A methodology for AI-enabled teams

Fewer handoffs.
Less rework.
AI that delivers.

Most AI adoption fails at context, not code. Dialog Driven Delivery transforms how teams create specifications—so AI tools finally perform like they promised.

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The Gap

You invested in AI tools. Where's the transformation?

Companies are deploying Copilot, Claude, Cursor—and seeing modest productivity gains at best. The tools aren't the problem.

AI generates code from context. When context is thin, scattered, or contradictory, output quality collapses. Your teams spend as much time fixing AI-generated code as they saved writing it.

Traditional specification practices weren't designed for this. User stories optimized for human developers don't give AI what it needs. The gap between what teams know and what AI receives—that's where transformation stalls.

Agile gave us collaboration. AI gives us generation. What's missing is the bridge: turning team knowledge into structured context that AI can use.

The Outcome

From investment to transformation

Minimize Translation Layers

Specifications emerge directly from cross-functional dialog. No more telephone game between product, architecture docs, stories, and code. What teams discuss becomes what AI implements.

Reduce Rework by Design

Dialog Driven Delivery makes uncertainty explicit—so you catch misalignment in conversation, not in code review. Teams report significantly less rework on AI-assisted features.

Accelerate Engineering Adoption

Engineers resist AI tools that create cleanup work. When specifications are rich and unambiguous, AI output quality rises—and so does trust. Adoption follows.

Principles

Five principles for AI-enabled delivery

1. Dialog is the specification source.

Cross-functional conversation—product, engineering, design thinking together—produces context that isolated documentation never can. AI makes capturing and structuring this dialog practical for the first time. The translation bottleneck disappears.

2. Make uncertainty visible.

AI fills gaps with confident invention. To counter that, we surface what we don't know. Assumptions are marked. Open questions are tracked. Unknowns stay unknown until resolved. Clarity about uncertainty prevents false confidence in implementation.

3. Context engineering is the new core skill.

AI follows context. Building it—capturing dialog, structuring specifications, surfacing decisions—is the work that determines whether AI tools help or hinder. This is learnable, repeatable, and scalable across your organisation.

4. Cheap to generate isn't cheap to maintain.

AI makes writing effortless. It changes nothing about reviewing, maintaining, or keeping documentation in sync. We document at feature level—where architecture, requirements, and decisions compound. Stories and tasks are delivery scaffolding. Disposable by design.

5. The human review loop is non-negotiable.

AI drafts. Humans review. Every specification, every story, every decision passes through human judgment. Speed without review is just faster mistakes. We use AI to accelerate, not to bypass the people accountable for outcomes.

The Discipline

Context Engineering: the core skill of AI-enabled delivery

In AI-enabled delivery, context is everything. The richer and more structured the context you provide, the more aligned the output you receive.

Building context—capturing dialog, structuring specifications, curating decisions, surfacing unknowns—is the new core competency. Teams that master context engineering outperform teams that just adopt tools.

Dialog Driven Delivery is a methodology for context engineering at team and organisation scale.

The Methodology

From conversations to working software

Dialog is the main source for creating rich specifications. The living conversations between team members become the specifications that drive implementation.

Capture

Start with a cross-functional conversation. Product, engineering, design—together. Capture the dialog where shared understanding forms.

Refine

Context comes from everywhere. Dialog, designs, prototypes, technical decisions, user feedback. Specifications evolve through whatever inputs emerge.

Decompose

Turn shared understanding into deliverable work. Break features into stories that stay connected to their source context.

Implement

Context flows to code. Learnings flow back to specifications. The bridge between conversation and implementation stays current.

"Your competitors are buying the same AI tools you are. The advantage goes to whoever figures out how to feed them better context."

What We Offer

Accelerate your AI-enabled delivery

Traditional specification approaches—BDD, Specification by Example, detailed upfront documentation—weren't designed for AI consumption or organisational transformation. They focus on artifacts, not the conversations that create shared understanding. We help teams adopt a better way.

Workshops

Interactive sessions where your team learns Dialog Driven Delivery by applying it to real features. Walk away with working specifications and a repeatable process.

Full-day formats
Team of up to 6 cross-functional participants

Lighthouse Teams

We help you establish pioneering teams that demonstrate the new way of working. These lighthouse teams become the catalyst for transforming how your entire organisation delivers software.

Select and prepare pilot team
Embedded coaching through delivery
Scale learnings across organisation

Ready to close the gap between AI investment and transformation?

Let's have a conversation about bringing Dialog Driven Delivery to your organisation.

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Join VPs and delivery leads exploring AI-enabled transformation. Frameworks, anti-patterns, and lessons from real implementations.