AI
Our AI approach.
AI moves fast. We run a disciplined quarterly cycle so you get the benefits in speed, cost, and outcomes, without the noise.
AI is evolving too fast to land on a fixed playbook. Instead of pretending we have it all figured out, we run a structured, continuous improvement cycle: evaluating tools, deploying what works, measuring outcomes, and adapting every quarter.
Our strategy is to stay on top of AI so our customers don't have to, and to pass the benefits directly to them in faster delivery, better quality, and stronger outcomes.
A continuous improvement cycle.
Every quarter we evaluate, deploy, measure, and adapt. This is how we keep improving without introducing churn or risk.
Assess the latest tools and models
Every quarter we review the AI landscape: new models, tools, frameworks, and practices. We benchmark against our current stack, testing for accuracy, speed, cost, and reliability in real delivery scenarios.
Adopt what proves itself
When a tool or model earns its place, we roll it into our delivery process across all roles, not just engineering. Business analysts use AI for prototyping and requirements, QA use it for test generation and analysis, and engineers use it across the full development lifecycle. Structured onboarding and shared skills make adoption safe and consistent.
Track outcomes, not just output
We measure what matters: delivery speed, code quality, correction cycles, and customer outcomes. We also track the economics, including token costs, so we understand the full picture and can optimise for value.
Refine and repeat
Results feed back into the next cycle. Tools that underperform get replaced. Practices that deliver get standardised. The cycle keeps turning so improvements compound over time.
Measured, not guessed.
These are measured outcomes from our delivery teams, not marketing claims.
Measure
Code AI-authored
Evaluate
Faster delivery
Cycle Cadence
Evaluation cycles
Cycle in action
Every 3 months we run this loop and feed the outcomes into the next cycle.
The benefits you get.
Our AI discipline translates directly into better outcomes for your projects.
Faster delivery and higher quality
We evaluate so you don't have to
Model-agnostic, no vendor lock-in
Responsible AI with guardrails baked in
Go deeper on our AI thinking.
Our blog covers the detail behind our approach, from tooling decisions to responsible AI and IP.
The AI Velocity Report
Every quarter we publish what most consultancies keep private: the AI tools we use, what we dropped, and the measurable impact on delivery speed and code quality.
Read the latest issueShipping AI in the Real World: Lessons From Our Latest Cycle
Our current stack, why we dropped vibe-coding tools, how OpenSpec reduces codebase churn, and what our engineers are seeing on the ground.
Read articleEvaluating AI Tools Using a Task-Based Framework
How we decide which AI tools earn their place, using a structured framework that maps tasks to tools and measures real productivity.
Read articleThe Business Leader's Guide to Responsible AI Use
Data privacy, human oversight, ethics, and governance: a practical guide for leaders adopting AI in their organisations.
Read articleWho Owns AI-Written Code?
IP, licensing, and legal risks of AI-generated code. What CTOs, developers, and procurement teams need to know.
Read articleClaude Code Development
How we use Cursor and Claude Code to build custom software faster, with full code ownership, clear IP terms, and enterprise-grade security.
View serviceAI Development & Implementation
Our end-to-end AI development service: from Azure OpenAI integrations and RAG architectures to Copilot Studio agents and production AI features.
View serviceFrequently asked questions
What is Talk Think Do's approach to AI?
We run a disciplined quarterly cycle: evaluate the latest AI tools and models, deploy what proves itself across all roles, measure outcomes such as delivery speed and code quality, then adapt and repeat. Rather than committing to a fixed playbook in a fast-moving field, we keep improving so our clients get the benefits of AI without the noise or risk of keeping up themselves.
How much of your code is AI-authored, and is it still reviewed?
AI authors around 84% of our code, but every line is reviewed by a senior engineer and validated by ISTQB-qualified QA. AI accelerates the work; it does not replace human judgement on architecture, quality, or security. The result is 40-50% faster delivery with quality measurably improving alongside speed.
Are you locked into a single AI provider?
No. We design model-agnostic solutions so you are not tied to one provider. You can swap models as the landscape evolves, whether that is OpenAI, Anthropic, open-source models, or whatever comes next. This protects you from vendor lock-in and lets you optimise for accuracy, cost, and reliability over time.
How do you keep AI use responsible and secure?
Every AI solution includes content filtering, output validation, human-in-the-loop checkpoints, and audit trails. Your data stays within your security boundary and access controls are enforced at every layer. Our work is underpinned by ISO 27001 certification and Cyber Essentials Plus accreditation.
Where can I see evidence of your AI results?
We publish the AI Velocity Report every quarter, sharing what most consultancies keep private: the tools we use, what we dropped, and the measured impact on delivery speed and code quality. You can read it at our AI Velocity Report.
Ready to explore AI for your organisation?
Let's discuss how our AI approach can add genuine value to your workflows.
Book a free consultationor call 01202 375647