Continuous Forecasting in Jira: Remaining Estimate, Scope and Worklog Example
Build a continuous Jira effort forecast from initial scope, estimate changes, logged time, and remaining estimates using a four-sprint worked example.
Backlog Bridge author
Arūnas
I write and review practical Backlog Bridge guides about Jira reporting, Pipedrive-to-Jira handoffs, Nextcloud connections, and Mermaid diagrams in Confluence.
My guides focus on concrete implementation decisions, worked examples, testable acceptance criteria, and primary product documentation. When I use a synthetic example or describe installed-product behavior that still needs verification, I make that limitation clear.
Recent articles by Arūnas
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Pipedrive to Jira SLA Handoff: Map Promised Dates, Priority and Ownership
Turn Pipedrive sales promises into a clear Jira handoff without confusing commercial dates, delivery commitments and service-level agreements.
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How to Review AI-Generated Mermaid Changes Without Missing Relationship Errors
Review AI-generated Mermaid edits with a baseline, proposed and accepted source; catch removed or reversed relationships using diffs and renders.
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An LLM Can Get You to 50% Fast. Reaching 100% Is the Real Work
LLMs make plausible first drafts easy. Learn how to close the harder gap with acceptance criteria, review ledgers, multiple models, human checks, and a deliberate de-bloating pass.
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LLM to Mermaid: a validation-first workflow for accurate AI-generated diagrams
Validate LLM-generated Mermaid with syntax, render, semantic and diagram-specific checks, using a worked sequence-diagram example and checklist.
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Jira Created vs Resolved Chart for Multiple Teams: Setup and Example
Configure a Jira created vs resolved chart for multiple teams with exact JQL, reconstructed settings, interpretation guidance, and four-week example data.
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Specification-Driven Design: From Intent to Verifiable Software
Turn product intent into testable requirements, system designs, acceptance evidence, and controlled changes with a practical specification-driven workflow.
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How to Measure Engineering Time Saved—and Added—by AI
Compare baseline and AI-assisted engineering work using generation, review, rework, defects, human effort, and elapsed time in a two-week evaluation.
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Rovo MCP for Jira Capacity Planning: What Managers Can Ask, Change, and Verify
Run a controlled two-week Rovo MCP capacity-planning pilot, understand what the new tools can change, and verify every allocation before expanding access.
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Mermaid Diagrams for Humans and LLMs: A Practical Balance
Design Mermaid diagrams that remain clear to business readers while giving AI assistants useful, reviewable structure.
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Mermaid vs BPMN: Differences, Limitations and When to Migrate
Compare Mermaid flowcharts with BPMN 2.0, identify the limits of visual approximations, and migrate verified process meaning with a worked example.
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Can You Trust a Jira AI Status Update? A Practical Checklist
Before sending an AI-written Jira update to leadership, check its scope, progress, blockers, estimates, and evidence with this practical worksheet.