zed-industries/zed
Mar 2025 – Apr 2025
2 Months active
Languages Used
RustJavaScriptYAML
Technical Skills
Rustbackend developmentAI EvaluationBackend DevelopmentCode RefactoringContinuous Integration
Thomas Mickley-Doyle
PROFILE
Thomas Mickley-doyle
Thomas contributed to the zed-industries/zed repository by delivering five features over two months, focusing on telemetry, user feedback, and AI evaluation. He implemented token usage telemetry for LanguageModelTextStream in Rust, enabling detailed tracking of input and output tokens for performance analysis. In JavaScript and Rust, Thomas built a user-facing reaction system with thumbs up/down and comment capture, integrating telemetry to support rapid agent quality improvements. He overhauled the ACE evaluation framework, adding language-based filtering, daily automation, and telemetry integration. His work enhanced observability, developer tooling, and data-driven decision-making, demonstrating depth in backend development, telemetry, and asynchronous programming.
Overall Statistics
Feature vs Bugs
100%Features
Repository Contributions
13Total
Bugs
0
Commits
13
Features
5
Lines of code
3,668
Activity Months2
Your Network
391 people
Work History
April 2025
12 Commits • 4 Features
Apr 1, 2025April 2025 performance summary for zed-industries/zed highlighting four key feature deliveries, telemetry enhancements, ACE evaluation framework overhaul, and networking/tools codebase improvements. The work delivered in 2025-04 focused on strengthening user feedback loops, increasing observability, and elevating evaluation automation, while also expanding developer tooling and metrics collection to support data-driven decisions. Key points: - Strong user-facing feedback mechanisms: introduced a per-response reaction system (thumbs up/down) with a dedicated comment box for negative feedback and telemetry for submissions, enabling faster agent quality improvements and customer-centric iterations. - Telemetry and observability upgrades: expanded agent panel telemetry to include tool names and added auto-capture of thread activity behind a feature flag, improving troubleshooting and performance insights while enabling controlled rollout. - AI evaluation framework (ACE) overhaul: substantial improvements to evaluation processes, language-based filtering, more examples, Git ops fixes, daily evaluation automation, and telemetry integration; included telemetry for eval runs and daily eval automation, plus commit-level traceability. - Networking/tools codebase enhancements: added Rust code examples to strengthen packet sniffer capabilities (ARP support, improved input parsing, email verification, EXIF handling) and improved database metric collection to support more accurate performance measurements. Overall impact: these changes deliver measurable business value through faster feedback loops, richer instrumentation for product decisions, more robust AI evaluation pipelines, and richer developer tooling, contributing to higher agent quality, better reliability, and clearer metrics for prioritization. Technologies/skills demonstrated: Rust, telemetry instrumentation, feature flags, GitOps and automation (CI/CD, GitHub Actions), AI evaluation tooling (ACE), language-based filtering, and telemetry integration.
12 Commits • 4 Features
Apr 1, 2025April 2025 performance summary for zed-industries/zed highlighting four key feature deliveries, telemetry enhancements, ACE evaluation framework overhaul, and networking/tools codebase improvements. The work delivered in 2025-04 focused on strengthening user feedback loops, increasing observability, and elevating evaluation automation, while also expanding developer tooling and metrics collection to support data-driven decisions. Key points: - Strong user-facing feedback mechanisms: introduced a per-response reaction system (thumbs up/down) with a dedicated comment box for negative feedback and telemetry for submissions, enabling faster agent quality improvements and customer-centric iterations. - Telemetry and observability upgrades: expanded agent panel telemetry to include tool names and added auto-capture of thread activity behind a feature flag, improving troubleshooting and performance insights while enabling controlled rollout. - AI evaluation framework (ACE) overhaul: substantial improvements to evaluation processes, language-based filtering, more examples, Git ops fixes, daily evaluation automation, and telemetry integration; included telemetry for eval runs and daily eval automation, plus commit-level traceability. - Networking/tools codebase enhancements: added Rust code examples to strengthen packet sniffer capabilities (ARP support, improved input parsing, email verification, EXIF handling) and improved database metric collection to support more accurate performance measurements. Overall impact: these changes deliver measurable business value through faster feedback loops, richer instrumentation for product decisions, more robust AI evaluation pipelines, and richer developer tooling, contributing to higher agent quality, better reliability, and clearer metrics for prioritization. Technologies/skills demonstrated: Rust, telemetry instrumentation, feature flags, GitOps and automation (CI/CD, GitHub Actions), AI evaluation tooling (ACE), language-based filtering, and telemetry integration.
April 2025
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025: Delivered token usage telemetry for LanguageModelTextStream in the zed repository, introducing a TokenUsage structure and token metrics reporting to enable token-level visibility for telemetry and performance analysis.
March 2025
1 Commits • 1 Features
Mar 1, 2025March 2025: Delivered token usage telemetry for LanguageModelTextStream in the zed repository, introducing a TokenUsage structure and token metrics reporting to enable token-level visibility for telemetry and performance analysis.
Activity
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Quality Metrics
Correctness87.8%
Maintainability83.2%
Architecture83.2%
Performance83.2%
AI Usage46.2%
Skills & Technologies
Programming Languages
JavaScriptRustYAML
Technical Skills
AI EvaluationBackend DevelopmentCode RefactoringContinuous IntegrationDatabase ManagementDevOpsGitGitHub ActionsImage ProcessingJavaScriptNetwork ProtocolsRustRust DevelopmentSoftware DevelopmentSoftware Engineering
Repositories Contributed To
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