Case Studies

Microsoft Edge
DevTools

A Microsoft Edge engagement focused on AIdriven inbrowser features, including realtime content simplification, alongside integrated developer tooling and structured feedback systems.

Screenshot of the Microsoft website; part of John Kavanagh's selected project work.

In Brief

Microsoft Edge is Microsoft's crossplatform web browser, built on Chromium and developed alongside a wider ecosystem of browser technologies and developer tools. This engagement explored ways to extend those capabilities through AIdriven inbrowser features and developer tooling, with a particular focus on improving the connection between web developers and browser teams.

My Role

I was engaged as a Principal Engineer within a Microsoft Edge working group, collaborating with Web We Want and W3Caligned stakeholders. I led a small external engineering team to define and deliver developer tooling, whilst providing architectural direction and coordinating delivery across multiple Microsoft teams. In a subsequent engagement, I returned to Microsoft to help explore AIdriven features within the browser itself.

Technologies

  1. TypeScript & JavaScript
  2. Microsoft Edge DevTools
  3. Extension APIs
  4. Node.js
  5. AI / Machine Learning

In Detail

This engagement formed part of Microsoft's "Web We Want" initiative, which focuses on strengthening the relationship between developers and browser vendors in collaboration with the World Wide Web Foundation and W3Caligned stakeholders.

Working closely with external stakeholders and industry leaders, I helped identify and prioritise opportunities for exploration within the browser, shaping a roadmap of experiments and MVPs to improve both developer feedback loops and the wider browsing experience.

To support that work, I assembled and led a small external engineering team responsible for turning selected ideas into practical demonstrations and earlystage implementations. My own handson focus was on the developer tooling strand, helping define and deliver new capabilities integrated directly within Microsoft Edge DevTools.

In a subsequent engagement at Microsoft's Redmond campus three years later, I returned to work with stakeholders on further experimentation into AI applications within the browser runtime. A key prototype explored realtime analysis of web pages, intelligently identifying and removing distracting or nonessential elements to improve clarity, focus, and usability without requiring changes from site authors.

Together, these engagements formed part of a broader programme of exploratory work within Microsoft Edge, investigating how the browser could better support both developers and end users, several years before AIassisted browsing experiences became increasingly common across the industry.

AI‑Assisted Content Simplification

A prototype exploring how AI could operate directly within the browser to improve clarity and focus by interpreting and restructuring live web pages in real time.

The system analysed page structure and content to identify nonessential or distracting elements, including adverts, overlays, and visual noise, and removed or suppressed them without requiring any changes from the site itself. This resulted in a cleaner, more readable experience, demonstrating how intelligent systems could augment the browsing experience at runtime rather than relying on upstream optimisation.

A cluttered web page layout displaying multiple content blocks, including images of furniture, side panels, and promotional-style cards. The main content area is surrounded by distracting elements such as a right-hand sidebar with stacked product cards, embedded images within the article flow, and visually competing sections. The page appears dense and fragmented, with competing focal points and multiple interruptions to the reading experience.A simplified version of the same web page with all non-essential elements removed, leaving a clean, text-focused layout. The right-hand sidebar, embedded promotional images, and visual distractions have been stripped away, resulting in a structured, readable column of content. The page now presents a clear hierarchy with improved focus, emphasising readability and reducing visual noise.

In‑Browser Developer Tooling

A set of inbrowser tools my team and I developed within Microsoft Edge DevTools to create a direct and structured feedback channel between developers and browser teams. Rather than relying on external issue trackers or fragmented reporting mechanisms, this approach embedded feedback capture directly into the developer workflow.

The tooling enabled developers to raise issues in context, preserving relevant page state and reducing friction in reporting. AIassisted analysis was used to help classify and enrich submissions, improving signal quality and making feedback more actionable at scale.

A web page displayed within a browser with an overlay panel from a developer tool showing a bug icon and structured input fields, representing an in-browser issue reporting interface integrated into the browsing experience.

Developer Feedback Pipeline

My team and I developed a structured feedback pipeline connecting inbrowser developer tooling to internal Microsoft systems, transforming ad hoc reports into actionable product signals. Issues raised within DevTools were captured with contextual metadata, enriched through automated classification, and routed into triage workflows to help browser teams identify and prioritise realworld problems.

A horizontal diagram showing a developer feedback pipeline within Microsoft Edge. It illustrates a five-step flow from a developer encountering an issue in the browser, submitting it via DevTools, generating a structured feedback payload with page data and logs, enriching it through AI classification, and routing it to internal Microsoft triage, backlog, and product teams.

The Outcome

Across two engagements with Microsoft Edge, my work took ideas from early exploration through to working prototypes and developer tooling, combining handson engineering with technical leadership and collaboration across the organisation and the wider web community.

These projects explored ways for the browser itself to play a more active role for both developers and end users, from creating a more direct feedback channel between developers and browser teams to experimenting with AIassisted browsing within the browser runtime itself.


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