resolutionflow/docs/plans/2026-02-04-feature-ideas-brainstorm.md

ResolutionFlow Feature Ideas Brainstorm

Date: February 4, 2026 Participants: Michael Chihlas, Claude Context: Brainstorming features tailored to MSP engineers, focused on the "document as you go" gap

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Design Principle

Every feature should follow the core principle that makes ResolutionFlow work: Engineers don't document — they troubleshoot, and the tool captures documentation as a byproduct.

New features should:

• Reduce engineer cognitive load
• Automate capture of what they're already doing
• Make reusing knowledge frictionless
• Reduce context switching during troubleshooting

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Ideas Summary

#	Feature	Category	Effort	Priority Signal
1	Session Time Tracking	Export enhancement	Small	High — quick win
2	Share Progress / Escalation	Collaboration	Medium	High — daily use
3	Command Output Capture	Context capture	Small	High — quick win
4	Push Steps to Active Sessions	Collaboration	Medium-Large	Medium — needs notification system
5	Path Analytics	Intelligence	Medium	Medium — needs session volume
6	Session Scratchpad	Context capture	Small-Medium	High — must-have (per Michael)
7	Multi-Tree Sessions	Session enhancement	Large	Medium — complex UX
8	Recurring Issue Detection	Intelligence	Small-Medium	High — leverages existing data
9	Tree Health Scores	Intelligence	Medium	Medium — needs session volume
10	AI Tree Intelligence	Intelligence	Large	Long-term — ultimate vision

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Idea 1: Session Time Tracking

Category: Export enhancement Effort: Small (backend export change, no new UI)

What

Every session automatically tracks duration (start → end) and includes it in the export.

Export Output

Session Duration: 23 minutes
Started: 2:30 PM | Completed: 2:53 PM

Why

MSP engineers bill by the hour. They troubleshoot in ResolutionFlow, export notes, then separately log time in their PSA. This eliminates the second step.

Implementation Notes

• Timestamps already exist in session decisions — just compute elapsed time
• Add duration to export templates (markdown, text, HTML)
• No new UI required — purely a backend export enhancement

Future Enhancement

• When PSA integration exists: if no PSA connected, ResolutionFlow tracks time natively. If PSA connected, still track time but also push it directly to the ticket in the PSA.
• Analytics: average resolution time per tree, per client, per engineer

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Idea 2: Share Progress / Escalation

Category: Collaboration Effort: Medium

What

Two mechanisms for sharing in-progress troubleshooting context:

1. "Share Progress" button (available mid-session) — generates a formatted summary of steps completed so far. Copy to clipboard, paste into Teams/Slack. One click instead of typing "here's what I've tried."

2. Read-only session link — shareable URL where anyone with the link can see the session state. If they sign in and get assigned, they can resume from where the previous engineer left off.

Workflow

1. Junior engineer gets stuck → clicks "Share Progress"
2. Pastes formatted summary into Teams chat with senior
3. Senior reads structured summary (not a wall of chat text)
4. If needed, senior opens the read-only link to see full detail
5. If escalating: ticket reassigned in PSA, senior resumes the session in ResolutionFlow

Implementation Notes

• Copy/paste version is nearly free — existing export logic on incomplete sessions + "Steps remaining" section
• Read-only link: generate share token, create public read-only session view (no auth)
• Resume capability: allow session reassignment to another user

Why This Matters

Eliminates the "what have you tried so far?" back-and-forth that happens on every escalation. The structured format means the senior gets context in 30 seconds instead of 10 minutes of chat.

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Idea 3: Command Output Capture

Category: Context capture Effort: Small

What

Action nodes (which show commands to run) get an optional "Paste Output" text area. Engineer runs the command, copies output, pastes it in.

Export Output

> Ran: Get-Service -Name Spooler
> Output:
>   Status: Stopped
>   Name: Spooler
> Decision: Service was stopped, proceeded to restart

Why

Engineers already run commands and read output. Today the output is lost — the export says "ran this command" but not what it returned. This captures the evidence.

Implementation Notes

• Add optional command_output field to session decision JSONB
• Add collapsible text area below commands on action nodes in TreeNavigationPage
• Include in export with code formatting
• Pairs well with Scratchpad (Idea 6) and Share Progress (Idea 2)

Future Enhancement

• Syntax highlighting for common output formats (PowerShell, JSON)
• Image paste for screenshots of GUI-based evidence

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Idea 4: Push Steps to Active Sessions

Category: Collaboration Effort: Medium-Large

What

A senior engineer (or anyone) can send a troubleshooting step directly to someone's active session. Flips the step library from a pull model (browse and find) to a push model (someone sends it to you).

Workflow

1. Junior shares progress link (Idea 2)
2. Senior sees they're stuck at "VDA not registering"
3. Senior picks a step from their personal library (or types one quickly)
4. Senior hits "Send to [Junior]" → step appears as notification in junior's session
5. Junior sees: "Michael sent you a step: Check Citrix Broker Service binding"
6. One click to insert into session
7. Step documented in export, optionally saved to junior's library

Why

Replaces unstructured Teams/Slack troubleshooting advice with structured, documented, reusable steps. The knowledge stays in the system.

Implementation Notes

• Requires lightweight notification/inbox system (polling or WebSocket)
• Builds on: Share Progress (Idea 2) + Step Library (existing)
• New API: POST /api/v1/sessions/{id}/send-step
• Frontend: notification badge + step insertion flow

Analytics Potential

• Which seniors send the most steps (mentorship tracking)
• Which pushed steps get reused (knowledge value)
• Which juniors receive fewer pushes over time (skill growth)

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Idea 5: Path Analytics — "The Road Most Traveled"

Category: Intelligence Effort: Medium

What

Aggregate completed session data to show statistical hints on decision nodes:

• Badge: "78% of engineers chose Option B here"
• On solution nodes: "Resolved the issue 92% of the time"
• At common stuck points: "Engineers often add a custom step here"

Why

Delivers on the tagline. For a junior engineer staring at three options, seeing "most engineers went this way" is a confidence boost. For tree authors, analytics reveal dead-end branches.

Implementation Notes

• Aggregate query on session path_taken and decisions JSONB
• Compute per-node: choice distribution, resolve rate, custom step frequency
• Cache aggregates (recompute daily or on-demand)
• Display as subtle badges on decision nodes (not intrusive)
• Resolve rate: track whether session completed at a solution node + optional "did this fix it?" prompt

Data Requirements

• Needs sufficient session volume per tree to be statistically meaningful (suggest: show after 10+ sessions)
• Weight recent sessions higher than old ones

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Idea 6: Session Scratchpad

Category: Context capture Effort: Small-Medium Priority: Must-have (per Michael)

What

A persistent sidebar during active sessions for capturing ambient data: IP addresses, error codes, server names, usernames — anything that doesn't fit a specific decision node's notes field.

Why

During troubleshooting, engineers accumulate bits of data (from ipconfig, Event Viewer, phone conversations) that live on sticky notes or in their head. This gives it a home and includes it in the export.

Export Output

## Evidence / Reference
- Server IP: 192.168.1.50
- Error code: 0x80070005
- Affected user: jsmith@contoso.com
- Event ID: 4625 (repeated 47 times in last hour)

Implementation Notes

• Persistent sidebar (collapsible) in TreeNavigationPage
• Store in session JSONB as scratchpad array of entries
• Each entry: text + optional label + timestamp
• Include in export as "Evidence / Reference" section
• Start simple: just a text area with "Add Note" button
• Future: structured key-value pairs, tags, image paste

Pairs With

• Command Output Capture (Idea 3): structured output at nodes + freeform notes in scratchpad = complete evidence
• Share Progress (Idea 2): scratchpad content included in shared summary

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Idea 7: Multi-Tree Sessions

Category: Session enhancement Effort: Large

What

When troubleshooting reveals the problem is in a different domain, branch into another tree mid-session without losing context. The export captures the entire journey.

Workflow

1. Engineer is in "VPN Issues" tree, 5 steps deep
2. Discovers the actual problem is DNS, not VPN
3. Clicks "Open Related Tree" → selects "DNS Resolution Issues"
4. Current tree bookmarked, linked session starts in DNS tree
5. DNS session completes → returns to VPN tree where they left off
6. Export shows unified narrative with both trees

Export Output

## VPN Connection Issues
1. Verified VPN client version: OK
2. Checked tunnel status: UP
3. Tested connectivity through tunnel: FAIL
   → Branched to: DNS Resolution Issues

  ## DNS Resolution Issues (linked)
  1. Ran nslookup: timeout
  2. Checked DNS config: wrong DC
  3. Resolution: Updated DNS to 10.0.0.5

4. Returned to VPN - retested: PASS
5. Resolution: DNS misconfiguration causing apparent VPN failure

Implementation Notes

• Session model needs: parent_session_id, branched_at_node_id
• "Open Related Tree" action on any node (tree selector modal)
• Breadcrumb shows tree chain: VPN > DNS
• Export renderer handles nested/linked sessions
• Back button returns to parent session at bookmark point

Why

Real troubleshooting rarely stays in one domain. This captures the full diagnostic story.

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Idea 8: Recurring Issue Detection

Category: Intelligence Effort: Small-Medium

What

When an engineer starts a session and enters a client name, show previous sessions for that client in that tree. If the same resolution keeps being reached, prompt for root cause action.

UI

• At session start: "3 previous sessions for Warner Robins in this tree (last: Jan 28)" + link to view
• At resolution (if recurring): "This is the 3rd time this issue was resolved the same way for this client. Consider documenting a permanent fix or escalating to address root cause."

Why

Turns ResolutionFlow from reactive (fix the ticket) to proactive (fix the root cause). For MSP managers, recurring issues per client = business intelligence for infrastructure upgrade proposals.

Implementation Notes

• Query: sessions grouped by client_name + tree_id, count + last date
• Display at session start (inline, not blocking)
• Recurrence prompt: compare resolution node_id across sessions
• Future (with PSA/RMM): correlate with alert data for richer signals

Data Model

• No schema changes needed — query existing sessions table
• Optional: normalize client names (fuzzy match or client_id foreign key)

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Idea 9: Tree Health Scores

Category: Intelligence Effort: Medium

What

Data-driven health indicators for trees, surfaced to tree authors and admins.

Signals

• Custom step frequency: Engineers keep adding steps at the same node → tree is missing a branch
• Abandonment rate: Sessions started but not completed → tree isn't leading to resolutions
• Low resolve rate: Solution nodes that don't actually fix issues
• Staleness: No updates in X months for a technology area that changes frequently
• Escalation rate: High percentage of sessions shared/escalated from this tree

Display

• Green/yellow/red health badge on tree library cards
• Author notification: "Your 'VPN Issues' tree has yellow health — 4 engineers added custom steps at 'Check Split Tunnel Config' this month"
• Admin dashboard: team-wide tree health overview

Why

Creates a self-improving ecosystem. Sessions generate data → data identifies weak trees → authors improve trees → next engineer gets a better experience.

Implementation Notes

• Scheduled aggregation job (daily)
• Health score algorithm: weighted combination of signals
• Store as computed field on tree (or separate analytics table)
• Notification system (pairs with Push Steps notification infrastructure, Idea 4)

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Idea 10: AI Tree Intelligence (Long-term Vision)

Category: Intelligence Effort: Large (phased) Status: Ultimate goal

What

Three layers of AI, each building on the last, leveraging ResolutionFlow's unique structured troubleshooting dataset.

Layer 1: Smart Tree Suggestions

• Engineer pastes ticket description: "User at Warner Robins reports Outlook keeps crashing after latest update"
• AI suggests: "Recommended: Outlook/Email Issues tree → Start at 'Recent Update' branch"
• Not just which tree — which branch to start at, skipping generic initial questions
• Implementation: NLP parsing of ticket text, match against tree node content and tags

Layer 2: Session-Driven Tree Evolution

• Aggregate session data reveals patterns: "35% of engineers add 'Check MFA Token' after 'Auth Failed' node, and it resolves 80% of the time"
• Generate suggestion to tree author: "Recommended new branch based on 18 successful sessions"
• Author reviews and approves with one click — tree evolves from real usage
• Implementation: Aggregation queries + LLM formatting suggestions + author approval UI

Layer 3: AI Tree Generation

• Senior describes: "We keep getting Azure AD Sync issues, no tree exists"
• AI generates complete tree draft using:
  • Similar trees in the system
  • Custom steps engineers have created for Azure AD
  • Resolution patterns from session history
  • Real PowerShell commands from command output captures
• Senior reviews, tweaks, publishes
• Implementation: RAG over tree corpus + session data + LLM generation + tree editor integration

Why This Is the Moat

ConnectWise or IT Glue could build a decision tree tool. But they don't have hundreds of structured session paths with outcomes to learn from. ResolutionFlow's data is structured by design — decision trees + session paths + outcomes — not unstructured ticket notes. That's a dataset purpose-built for learning optimal troubleshooting paths.

Phasing

• Layer 1 can ship independently with basic NLP
• Layer 2 needs sufficient session volume (6+ months of real usage)
• Layer 3 needs Layers 1 + 2 data + LLM integration

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Quick Actions Dashboard (Bonus)

Category: UX improvement Effort: Medium

What

Replace the tree library as the default landing page with a troubleshooting command center.

Sections

• Resume sessions — "VPN Issues - Acme Corp (started 20 min ago)" for incomplete sessions
• Quick starts — Frequent tree+client combos: "File Share Access for Warner Robins — Quick start?" One tap.
• Team activity — "Sarah completed 'AD Replication' for Client X (12 min)" — visibility without a standup
• Your trees — Health scores for trees you authored, pending suggestions from AI (Layer 2)
• Recurring alerts — Clients with repeat issues that need attention

Why

Turns ResolutionFlow from a tool you visit per-ticket into something you keep open all day. Reduces friction from "open app → find tree → start session" to "open app → click the obvious next action."

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Suggested Build Order

Near-term (build now, small effort, immediate value)

1. Session Scratchpad (Idea 6) — must-have per Michael
2. Session Time Tracking (Idea 1) — quick win, enhances every export
3. Command Output Capture (Idea 3) — quick win, pairs with scratchpad

Mid-term (build next, medium effort, high value)

1. Share Progress / Escalation (Idea 2) — daily use for team collaboration
2. Recurring Issue Detection (Idea 8) — leverages existing data immediately
3. Quick Actions Dashboard (Bonus) — improves daily UX
4. Path Analytics (Idea 5) — needs session volume, start collecting data now

Later (larger effort, needs foundation)

1. Push Steps to Active Sessions (Idea 4) — needs notification system
2. Tree Health Scores (Idea 9) — needs session volume + analytics infrastructure
3. Multi-Tree Sessions (Idea 7) — complex UX, large refactor

Long-term vision

1. AI Tree Intelligence (Idea 10) — phased rollout, ultimate differentiator

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Dependencies & Connections

Scratchpad (6) ──────────────────────────────┐
Command Output (3) ──────────────────────────┤
Time Tracking (1) ───────────────────────────┤── Enhanced Exports
                                             │
Share Progress (2) ──┬── Push Steps (4) ─────┤── Collaboration
                     │                       │
                     └── Notification System ─┘

Path Analytics (5) ──┬── Tree Health (9) ────┬── AI Intelligence (10)
Recurring Issues (8) ┘                       │
                                             │
Multi-Tree Sessions (7) ────────────────────┘

Key insight: Ideas 1, 3, and 6 (time tracking, command output, scratchpad) are independent quick wins that make exports richer. Ideas 2 and 4 (share progress, push steps) build a collaboration layer. Ideas 5, 8, 9, and 10 (analytics, recurring issues, health, AI) form the intelligence layer that grows with usage.

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Generated during brainstorming session, February 4, 2026