Showing results for "CI"
Create an agent to optimize CI time: caching, test sharding, and selective runs while preserving safety. Include a policy to prevent skipping critical tests.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design contract tests for microservices: consumer-driven contracts, version pinning, and compatibility gates. Integrate with the self-edit loop for safe rollouts.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create an agent that writes tests before code changes, targets uncovered branches, and proves coverage deltas. Include mutation testing as a safety check.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design a loop to detect memory leaks: reproduce with stress tests, capture heap snapshots, propose fix, and verify stability. Include regression tests.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create a test selection algorithm that runs only relevant tests for a diff but guarantees critical coverage (safety suite always runs). Include calibration and drift checks.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Build a refactoring agent that only changes code when it can show measurable gains (latency, memory, error rate). Include baseline capture and regression detection.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design an agent that identifies flaky tests, isolates root causes (timing, ordering, external deps), and proposes stabilization patches. Require proof via repeated runs.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design a self-improving code-editing AI loop that proposes patches, runs tests, requests review, and deploys via canary + rollback. Include explicit safety gates and audit logs.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Design a monorepo-focused self-editor: dependency-aware builds, targeted tests, ownership routing, and change batching. Include safeguards against large blast radius.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create a property-based testing strategy for critical modules: define properties, generators, shrinking, and CI integration. Use failures to guide safer edits.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create a blueprint for self-editing CI/CD scripts safely: validate configs, run in sandbox, and require manual approval for permission changes.
Author: Assistant
Category: safe-self-improving-ai | Model: gpt-5.2
Create a testing strategy: unit tests for extractors, integration tests for API calls (mocked), and golden report tests to detect synthesis drift. Include CI gating rules.
Author: Assistant
Category: research-bot | Model: GPT-5.2
Design a safe loop where the AI proposes code changes: unit tests, static analysis, security scans, human review, and staged deployments. Include stop rules and rollback plans.
Author: Assistant
Category: recursive-ai-safety | Model: GPT-5.2
Design an eval harness: deterministic replays, seeded randomness, fixed tool mocks, and artifact snapshots. Provide a folder structure and CI integration plan.
Author: Assistant
Category: agent-architecture | Model: GPT-5.2
Design a UVM environment: agents, scoreboards, reference models, sequence layering, coverage model, and CI integration. Include best practices for reproducibility and debug speed.
Author: Assistant
Category: fpga-asic-design | Model: gpt-4o
Design a CI pipeline for hardware: lint rules, CDC checks, reset checks, basic formal proofs, and regression simulation tiers. Include pass/fail gates and artifact retention for debug.
Author: Assistant
Category: fpga-asic-design | Model: gpt-4o
Create a corporate competitive intelligence playbook using only public sources: announcements, job postings, patents, pricing pages, partnerships, and customer reviews. Include a weekly CI report temp...
Author: Assistant
Category: analysis-workflow | Model: gpt-4o
Have ChatGPT template Terraform/Pulumi modules, Cursor generate CI pipelines for plan/apply, and Antigravity agents stand up preview environments per PR. Include drift detection and cost guardrails.
Author: Assistant
Category: platform-engineering | Model: gpt-4o
ChatGPT codifies component usage rules, Cursor writes lint/codemods to enforce tokens/spacing, Antigravity gates CI on violations and auto-opens refactor PRs. Output exemptions policy.
Author: Assistant
Category: ui-governance | Model: gpt-4o
ChatGPT defines style/convention rules; Cursor runs auto-fixes (format/import/order); Antigravity enforces in CI and opens weekly hygiene PRs. Include opt-out rules.
Author: Assistant
Category: code-hygiene | Model: gpt-4o
Have ChatGPT define DORA+space metrics; Cursor wires collectors in CI; Antigravity aggregates and alerts on error-budget burn. Provide a monthly review agenda.
Author: Assistant
Category: engineering-ops | Model: gpt-4o
ChatGPT enumerates edge cases; Cursor scaffolds fuzzing harness; Antigravity runs fuzzers in CI and bisects crashes. Output a triage SOP.
Author: Assistant
Category: resilience-testing | Model: gpt-4o
ChatGPT drafts an iOS/Android CI matrix; Cursor configures build/signing scripts; Antigravity orchestrates device-farm runs and posts crash triage. Include flaky-test quarantine.
Author: Assistant
Category: mobile-quality | Model: gpt-4o
Have ChatGPT propose pipeline concurrency, caching, and test sharding; Cursor edits YAML/pipelines; Antigravity times stages and suggests cache keys. Output a before/after chart.
Author: Assistant
Category: pipeline-engineering | Model: gpt-4o
List guardrails for deploy safety such as canaries, feature flags, error budgets, and rollback scripts. Output a checklist and training plan.
Author: Assistant
Category: release-engineering | Model: gpt-4o
Identify top constraints to developer velocity and propose experiments across CI time, test flake, code review, and environment drift. Output target benchmarks.
Author: Assistant
Category: engineering-productivity | Model: gpt-4o
Propose a CI/CD pipeline with environment promotion, canary by geography (US first or TW first), secrets management, and rollback playbooks. Include cloud region choices (e.g., asia-east1, us-west).
Author: Assistant
Category: devops-pipelines | Model: gpt-4o
Build a CLI to lint .env files: missing keys, duplicate entries, weak defaults, and accidental quotes/CRLF. Flags: --schema .env.example, --fix, --export powershell|bash. CI-friendly exit codes.
Author: Assistant
Category: cli-tool | Model: gpt-4o
Act as a comp-bio lead. Provide templates for Nextflow and Snakemake with container pinning, parameter JSON/YAML, CI smoke tests, and provenance capture. Include runbooks.
Author: Assistant
Category: bioinformatics-devops | Model: gpt-5
Act as an MLOps lead. Propose a minimal stack with DVC for data, MLflow for tracking, and GitHub Actions for CI. Provide folder layout, YAML samples, and a model promotion checklist.
Author: Assistant
Category: ai | Model: gpt-4o
Define a push-button signoff pipeline: reproducible EDA containers, golden rule decks, regression checklists, run orchestration, artifact retention, and ECO automation for timing/IR/DRC. Output a CI/C...
Author: Assistant
Category: chip-design | Model: gpt-4
Act as a principal engineer. Define a CI/CD pipeline that satisfies SOC 2 and ISO 27001 concerns: branch policies, required reviews, SBOM generation, dependency scanning, SAST/DAST, signing and proven...
Author: tsubasa
Category: engineering | Model: gpt-4o
Design a CI/CD pipeline that minimizes energy. Tactics: selective test runs, caching, artifact reuse, ephemeral environments, static analysis gates, and carbon-intensity-aware scheduling. Add SLOs and...
Author: Tsubasa Kato
Category: devops | Model: gpt-5-thinking
Be the data steward. Deliver: dataset contract, versioning rules, weak-label checks, inter-annotator agreement, drift alarms, and golden set. KPIs: label error %, drift rate, model delta. Output: repo...
Author: Tsubasa Kato
Category: Engineering | Model: GPT-5 Thinking
You are a robotics CI lead. Design a sim-in-the-loop pipeline for perception + planning stacks. Deliver: scenario library spec (lighting, occlusion, rare edge cases), metrics (success %, collision=0, ...
Author: Tsubasa Kato
Category: Engineering | Model: GPT-5 Thinking
Generate a DevOps pipeline configuration optimized for cross-regional deployment in USA, Europe, and Asia, balancing latency, cost, and compliance.
Author: [email protected]
Category: Infrastructure Engineering | Model: Claude 3.5 Sonnet, GPT-5
Analyze the latest trends in DevOps and their impact on software delivery speed and quality. Identify best practices and tools for implementing a successful DevOps strategy.
Author: DevOps Engineer
Category: Technology | Model: GPT-4