These intermediate agents handle multi-file synthesis and structured analysis — sprint retros, exec briefings, customer research synthesis, and OKR scoring. Each one replaces 2–8 hours of manual work per week.
March 2026AI Agents · Agile · Strategy · Research · PlanningBy Vishal Jaiswal
If you've already tried the beginner agents and want to go deeper, these four intermediate workflows tackle the higher-stakes work: the reports that go to leadership, the research that drives roadmap decisions, the OKR updates that define quarterly priorities.
These agents are “intermediate” not because they require coding, but because they involve working with multiple input files and producing more structured, judgement-heavy outputs. The prompts are more detailed — and so are the results.
01
AgileCowork
Sprint Retrospective Agent
Cowork reads your JIRA/Linear export + meeting notes
WHAT
Cowork ingests your sprint data plus retro meeting notes, and generates a structured retrospective report with actionable insights.
HOW
Point Cowork at a folder with your sprint export CSV and retro notes. It analyses velocity trends and writes the retro doc.
OUTCOME
Retro prep that took 2 hours now takes 10 min of review.
data-analysispattern-detection
Prompt — CoworkCopy-paste prompt
This folder contains:
- sprint_export.csv (JIRA/Linear sprint data)
- retro_notes.txt (raw meeting notes)
Analyse the sprint and write a structured retrospective:
## Sprint Summary
(velocity vs target, stories completed vs planned)
## What Went Well
(top 3, with evidence from the data)
## What Didn't Go Well
(top 3, with root cause hypothesis)
## Action Items
| Item | Owner | Due | Success Metric |
## Velocity Trend
(compare last 3 sprints if data available)
## Team Health Indicators
(blockers pattern, scope creep, late additions)
Save as sprint_retro_[SPRINT_NAME].md
02
StrategyClaude Code
Stakeholder Briefing Agent
Claude Code synthesises data from multiple sources
WHAT
Claude Code reads your product metrics CSV, roadmap file, and open risks doc, then generates a concise executive briefing tailored to your stakeholder.
HOW
Run Claude Code with your data files. Specify the stakeholder and their priorities. It produces a crisp one-pager in their language.
OUTCOME
Exec briefing prep cut from 3 hours to 20 minutes.
multi-file synthesisexec writing
Prompt — Claude CodeCopy-paste prompt
I need a stakeholder briefing for: [stakeholder name/role]
Their top priorities: [e.g. revenue growth, risk reduction, customer NPS]
This folder contains:
- metrics.csv (product KPIs, last 4 weeks)
- roadmap.md (current roadmap)
- risks.md (open risks and mitigations)
Write a one-page executive briefing:
## Headline (1 sentence — what they most need to know)
## Progress Since Last Brief
(3 bullet points max, metric-led)
## Decisions Needed
(be specific — what are you asking them for?)
## Risks on the Radar
(1–2 items, with your recommended response)
## What's Coming Next
(next 2–3 weeks, framed around their priorities)
Write in plain English. No jargon. Max 400 words.
Save as briefing_[stakeholder]_[DATE].md
03
ResearchCowork
Customer Interview Analyser
Cowork reads transcripts and synthesises themes
WHAT
Point Cowork at a folder of customer interview transcripts. It extracts themes, pain points, unmet needs, and verbatim quotes by segment.
HOW
Drop all transcript files into a folder. Tell Cowork your product area and target segments. It reads all files and writes a structured insights report.
OUTCOME
Synthesis of 20 interviews from 8 hours down to 30 minutes.
transcript-analysisthemes
Prompt — CoworkCopy-paste prompt
This folder contains customer interview transcripts (.txt or .docx).
Product area: [your product area]
Target segments in these interviews: [e.g. SMB, Enterprise, Power Users]
Analyse all transcripts and produce an insights report:
## Top Pain Points
(ranked by frequency — quote count + representative verbatim quote)
## Unmet Needs
(jobs they're trying to do that aren't being served)
## Current Workarounds
(how they solve the problem today)
## Sentiment by Segment
(table: segment | overall sentiment | top concern)
## Standout Quotes
(5–7 verbatim quotes worth sharing with the team)
## Implications for Roadmap
(3 bullet hypotheses based on the data)
Save as customer_insights_[DATE].md
04
PlanningClaude Code
OKR Progress Tracker Agent
Claude Code reads your metrics exports and scores OKRs
WHAT
Claude Code reads your metrics data and OKR definitions, auto-scores each key result, and writes a weekly OKR progress update with RAG status.
HOW
Keep your OKRs in a structured CSV. Claude Code reads current metrics, calculates progress %, assigns RAG, and outputs the update.
OUTCOME
Weekly OKR review prep automated end-to-end — no manual scoring.
metrics-scoringRAG-reporting
Prompt — Claude CodeCopy-paste prompt
This folder contains:
- okrs.csv (Objective, Key Result, Target, current Actual, Owner)
- metrics.csv (weekly metrics export)
For each Key Result:
1. Calculate progress % = (Actual / Target) × 100
2. Assign RAG status:
- Green: ≥ 70% of target on current trajectory
- Amber: 40–69% — at risk
- Red: < 40% — off track
Output:
## OKR Scorecard — Week of [DATE]
For each Objective:
- Overall RAG
- Each KR with: current value | target | % complete | RAG | trend (↑↓→)
- 1-line commentary if Red or Amber
## Executive Summary
(2–3 sentences: overall health, biggest risk, what needs attention)
Save as okr_update_[DATE].md
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All 4 agents with prompts — download the original slides as a PDF reference.