# dd0c/cost — AWS Cost Anomaly Detective
## Brainstorming Session

**Date:** February 28, 2026  
**Facilitator:** Carson, Elite Brainstorming Specialist  
**Product:** dd0c/cost (Product #5 in the dd0c platform)  
**Target:** Teams spending $10K–$500K/mo on AWS who want instant alerts when something spikes  

---

## Phase 1: Problem Space (25 ideas)

### The Emotional Gut-Punch

1. **The 3am Stomach Drop** — You open your phone, see a Slack message from finance: "Why is our AWS bill $18K over budget?" Your heart rate spikes. You don't even know where to start looking. AWS Cost Explorer loads in 8 seconds and shows you a bar chart that means nothing.

2. **The Blame Game** — Someone left a GPU instance running over the weekend. Nobody knows who. The CTO asks in the all-hands. Three teams point fingers. The intern who actually did it is too scared to speak up. The political fallout lasts weeks.

3. **The "It Was Just a Test" Excuse** — A developer spun up a 5-node EMR cluster "just to test something real quick." That was 11 days ago. It's been burning $47/hour. Nobody noticed because nobody looks at billing until month-end.

4. **The NAT Gateway Surprise** — The single most rage-inducing line item on any AWS bill. Teams discover they're paying $3K/month for NAT Gateway data processing and have zero idea which service is generating the traffic. AWS gives you no breakdown.

5. **The Data Transfer Black Hole** — Cross-region, cross-AZ, internet egress, VPC endpoints, PrivateLink — data transfer costs are a labyrinth. Even experienced architects can't predict them. They just show up as a lump sum.

6. **The Autoscaling Runaway** — A traffic spike triggers autoscaling. The spike ends. Autoscaling doesn't scale back down because the cooldown period is misconfigured. You're now running 40 instances instead of 4. For three days.

7. **The Reserved Instance Waste** — You bought $50K in reserved instances for m5.xlarge. Six months later, the team migrated to Graviton (m7g). The reservations are burning money on instances nobody uses.

8. **The S3 Lifecycle Policy That Never Was** — "We'll add lifecycle policies later." Later never comes. You're storing 80TB of debug logs from 2023 in S3 Standard at $0.023/GB. That's $1,840/month for data nobody will ever read.

9. **The EBS Snapshot Graveyard** — Hundreds of orphaned EBS snapshots from deleted instances. Each one costs pennies, but collectively they're $400/month. Nobody even knows they exist.

10. **The CloudWatch Log Explosion** — A misconfigured Lambda starts logging every request payload at DEBUG level. CloudWatch ingestion costs go from $50/month to $2,000/month in 48 hours. The default CloudWatch dashboard doesn't show cost impact.

### Why AWS Cost Explorer Sucks

11. **24-48 Hour Delay** — Cost Explorer data is delayed by up to 48 hours. By the time you see the spike, you've already burned thousands. Real-time? AWS doesn't know the meaning.

12. **Terrible Filtering UX** — Want to see costs for a specific team's resources? Hope you tagged everything perfectly. Spoiler: you didn't. Cost Explorer's filter UI is a nightmare of dropdowns and "apply" buttons.

13. **No Actionable Context** — Cost Explorer tells you "EC2 costs went up 300%." It does NOT tell you which specific instances, who launched them, when, or why. You have to cross-reference with CloudTrail manually.

14. **Anomaly Detection is a Joke** — AWS Cost Anomaly Detection exists but: alerts are delayed (same 24-48hr lag), the ML model is a black box you can't tune, false positive rate is absurd, and the notification options are limited to SNS/email (no Slack native).

15. **No Remediation Path** — Even when you find the problem in Cost Explorer, there's no "fix it" button. You have to context-switch to the EC2 console, find the resource, and manually terminate/resize. That's 15 clicks minimum.

16. **Forecasting is Useless** — AWS's cost forecast is a straight-line projection that ignores seasonality, deployment patterns, and common sense. "Based on current trends, your bill will be $∞."

### What Causes Cost Spikes (The Usual Suspects)

17. **Zombie Resources** — EC2 instances, RDS databases, Elastic IPs, Load Balancers, Redshift clusters that are running but serving no traffic. The #1 source of waste. Every AWS account has them.

18. **Right-Sizing Neglect** — Running m5.4xlarge instances that average 8% CPU utilization. Nobody downsizes because "what if we need the headroom?" (They never do.)

19. **Dev/Staging Environments Running 24/7** — Production needs to be always-on. Dev and staging do not. But they run 24/7 because nobody set up a schedule. That's 75% waste on non-prod.

20. **Marketplace AMI Licensing** — Someone launched an instance with a marketplace AMI that costs $2/hour in licensing fees on top of the EC2 cost. The license cost doesn't show up where you'd expect.

21. **Elastic IP Charges** — Allocated but unattached Elastic IPs cost $0.005/hour each. Sounds tiny. 50 orphaned EIPs = $180/month. Death by a thousand cuts.

22. **Lambda Concurrency Explosions** — A recursive Lambda invocation bug or a sudden traffic spike causes thousands of concurrent executions. The per-invocation cost is low but at 10K concurrent, it adds up fast.

23. **DynamoDB On-Demand Pricing Surprises** — Teams choose on-demand for convenience, then discover their read/write patterns would be 80% cheaper with provisioned capacity + auto-scaling.

24. **Multi-Account Sprawl** — Organizations with 20+ AWS accounts lose track of which accounts are active, who owns them, and what's running in them. Consolidated billing hides the details.

25. **Savings Plans Mismatch** — Bought Compute Savings Plans based on last quarter's usage. This quarter's usage shifted to a different instance family/region. Savings Plans don't cover it. You're paying on-demand AND wasting the commitment.

---

## Phase 2: Solution Space (42 ideas)

### Detection Approaches

26. **CloudWatch Billing Metrics (Near Real-Time)** — Poll `EstimatedCharges` metric every 5 minutes. It's the fastest signal AWS provides. Not perfect, but way better than Cost Explorer's 48-hour lag.

27. **CloudTrail Event Stream** — Monitor `RunInstances`, `CreateDBInstance`, `CreateFunction`, `CreateNatGateway` etc. in real-time via EventBridge. Detect expensive resource creation the MOMENT it happens, before any cost accrues.

28. **Cost and Usage Report (CUR) Hourly Parsing** — AWS CUR can be delivered hourly to S3. Parse it with a lightweight Lambda/Fargate job. Gives line-item granularity that Cost Explorer API doesn't.

29. **Hybrid Detection: Events + Billing** — Use CloudTrail for instant "something was created" alerts, then correlate with CUR data for actual cost impact. Best of both worlds.

30. **Tag-Based Cost Boundaries** — Let users define expected cost ranges per tag (e.g., `team:payments` should be $2K-$4K/month). Alert when any tag group exceeds its boundary.

31. **Service-Level Baselines** — Automatically learn the "normal" cost pattern for each AWS service in the account. Alert on deviations. No manual threshold setting required.

32. **Account-Level Anomaly Scoring** — Assign each AWS account a daily "anomaly score" (0-100) based on deviation from historical patterns. Dashboard shows accounts ranked by anomaly severity.

### Anomaly Algorithms

33. **Statistical Z-Score Detection** — Simple, explainable. Calculate rolling mean and standard deviation for each service/tag. Alert when current spend exceeds 2σ or 3σ. Users understand "this is 3 standard deviations above normal."

34. **Seasonal Decomposition (STL)** — Decompose cost time series into trend + seasonal + residual. Alert on residual spikes. Handles weekly patterns (lower on weekends) and monthly patterns (batch jobs on the 1st).

35. **Prophet-Style Forecasting** — Use Facebook Prophet or similar for time-series forecasting. Compare actual vs. predicted. Alert on significant positive deviations. Good for accounts with complex seasonality.

36. **Rule-Based Guardrails** — Simple rules that catch 80% of problems: "Alert if any single resource costs >$X/day", "Alert if a new service appears that wasn't used last month", "Alert if daily spend exceeds 150% of 30-day average."

37. **Peer Comparison** — "Your EC2 spend per engineer is 3x the median for companies your size." Anonymized benchmarking across dd0c customers. Powerful social proof for optimization.

38. **Rate-of-Change Detection** — Don't just look at absolute cost. Look at the derivative. A service going from $10/day to $50/day is a 5x spike even though the absolute number is small. Catch problems early when they're cheap to fix.

39. **Composite Anomaly Detection** — Combine multiple signals: cost spike + new resource creation + unusual API calls = high-confidence anomaly. Single signals = low-confidence (reduce false positives).

### Remediation

40. **One-Click Stop Instance** — See a runaway EC2 instance? Click "Stop" right from the dd0c alert. We execute `StopInstances` via the customer's IAM role. No console context-switching.

41. **One-Click Terminate with Snapshot** — For instances that should be killed: terminate but automatically create an EBS snapshot first, so nothing is lost. Safety net built in.

42. **Schedule Non-Prod Shutdown** — "This dev environment runs 24/7 but only gets traffic 9am-6pm ET." One click to create a start/stop schedule. Instant 62% savings.

43. **Right-Size Recommendation with Apply** — "This m5.4xlarge averages 8% CPU. Recommended: m5.large. Estimated savings: $312/month." Click "Apply" to resize. We handle the stop/modify/start.

44. **Auto-Kill Zombie Resources** — Define a policy: "Any EC2 instance with <1% CPU for 7 days gets auto-terminated." dd0c enforces it. Opt-in, with a 24-hour warning notification before termination.

45. **Budget Circuit Breaker** — Set a hard daily/weekly budget. When spend approaches the limit, dd0c automatically stops non-essential resources (tagged as `priority:low`). Like a financial circuit breaker.

46. **Savings Plan Optimizer** — Analyze usage patterns and recommend optimal Savings Plan purchases. Show the exact commitment amount and projected savings. One-click purchase through AWS.

47. **Reserved Instance Exchange Assistant** — Got unused RIs? dd0c finds the optimal exchange path to convert them to instance types you actually use. Handles the RI Marketplace listing if exchange isn't possible.

48. **S3 Lifecycle Policy Generator** — Scan S3 buckets, analyze access patterns, generate optimal lifecycle policies (Standard → IA → Glacier → Delete). One-click apply.

49. **EBS Snapshot Cleanup** — Identify orphaned snapshots, show total cost, one-click bulk delete with a confirmation list.

50. **Approval Workflow for Expensive Actions** — For remediation actions above a cost threshold, require manager/lead approval via Slack. "Max wants to terminate 5 instances saving $2,100/month. Approve?"

### Attribution

51. **Team-Level Cost Dashboard** — Break down costs by team using tags, account mapping, or resource ownership. Each team sees ONLY their costs. Accountability without blame.

52. **PR-Level Cost Attribution** — Track which pull request / deployment caused a cost change. "Costs increased $340/day after PR #1847 was merged (added new ECS service)." Integration with GitHub/GitLab.

53. **Environment-Level Breakdown** — Production vs. Staging vs. Dev vs. QA. Instantly see that staging is costing 60% of production (it shouldn't be).

54. **Service-Level Cost per Request** — Combine cost data with traffic data. "Your payment service costs $0.003 per request. Your search service costs $0.047 per request." Unit economics for infrastructure.

55. **Slack Cost Bot** — `/cost my-team` in Slack returns your team's current month spend, trend, and anomalies. No dashboard needed for quick checks.

### Forecasting

56. **End-of-Month Projection** — "Based on current trajectory, your February bill will be $47,200 (budget: $40,000). You'll exceed budget by $7,200 unless action is taken." Updated daily.

57. **What-If Scenarios** — "What if we right-size all oversized instances? Projected savings: $4,200/month." "What if we schedule dev environments? Savings: $2,800/month." Quantify the impact before acting.

58. **Deployment Cost Preview** — Before deploying a new service, estimate its monthly cost based on the Terraform/CloudFormation template. "This deployment will add approximately $1,200/month to your bill." Pre-deploy, not post-mortem.

59. **Trend Analysis with Narrative** — Not just charts. "Your EC2 costs have increased 23% month-over-month for 3 consecutive months, driven primarily by the data-pipeline team's EMR usage. At this rate, EC2 alone will exceed $30K by April."

### Notification

60. **Slack-Native Alerts with Action Buttons** — Alert lands in Slack with context AND action buttons: [Stop Instance] [Snooze 24h] [Assign to Team] [View Details]. No context-switching.

61. **PagerDuty Integration for Critical Spikes** — Cost spike >$X/hour? That's an incident. Page the on-call FinOps person (or the team lead if no FinOps role exists).

62. **Daily Digest Email** — Morning email: "Yesterday's spend: $1,423. Trend: ↑12% vs. 7-day average. Top anomaly: NAT Gateway in us-east-1 (+$89). Action needed: 3 zombie instances detected."

63. **SMS for Emergency Spikes** — Configurable threshold. "Your AWS spend exceeded $500 in the last hour. This is 10x your normal hourly rate." For the truly catastrophic events.

64. **Weekly Cost Report for Leadership** — Auto-generated PDF/Slack message for non-technical stakeholders. Plain English. "We spent $38K on AWS this week. That's 5% under budget. Three optimization opportunities worth $2,100/month were identified."

### Visualization

65. **Cost Heatmap** — Calendar heatmap showing daily spend intensity. Instantly spot the expensive days. Click any day to drill down.

66. **Service Treemap** — Treemap visualization where rectangle size = cost. Instantly see which services dominate your bill. Click to drill into sub-categories.

67. **Real-Time Cost Ticker** — A live-updating ticker showing current burn rate: "$1.87/hour | $44.88/day | $1,346/month (projected)". Like a stock ticker for your AWS bill.

68. **Anomaly Timeline** — Horizontal timeline showing detected anomalies as colored dots. Red = unresolved, green = remediated, yellow = acknowledged. Visual history of your cost health.

69. **Cost Diff View** — Side-by-side comparison of any two time periods. "This week vs. last week: +$2,100 total. EC2: +$800, RDS: +$1,100, S3: +$200." Like a git diff for your bill.

70. **Infrastructure Cost Map** — Visual representation of your AWS architecture with cost annotations. See your VPC, subnets, instances, databases — each labeled with their daily cost. Like an AWS architecture diagram that shows you where the money goes.

### Wild Ideas 🔥

71. **"Cost Replay"** — Rewind your AWS bill to any point in time and replay cost changes like a video. See exactly when costs started climbing and correlate with CloudTrail events. A DVR for your cloud spend.

72. **Auto-Negotiate Reserved Instances** — dd0c monitors your usage patterns, identifies RI opportunities, and automatically purchases optimal reservations (with configurable approval thresholds). Fully autonomous FinOps.

73. **Zombie Resource Hunter (Autonomous Agent)** — An AI agent that continuously scans your account for unused resources, calculates waste, and either auto-terminates (if policy allows) or creates a cleanup ticket. It never sleeps.

74. **"Cost Blast Radius" for PRs** — GitHub Action that comments on every PR: "If merged, this change will increase monthly AWS costs by approximately $340 (new ECS task definition with 4 vCPU)." Shift cost awareness left.

75. **Competitive Benchmarking** — "Companies similar to yours (50 engineers, SaaS, Series B) spend a median of $28K/month on AWS. You spend $45K. Here's where you're overspending." Anonymous, aggregated data from dd0c's customer base.

76. **"AWS Bill Explained Like I'm 5"** — AI-generated plain-English explanation of your bill. "You spent $4,200 on EC2 this month. That's like renting 12 computers 24/7. But 4 of them did almost nothing. If you turn those off, you save $1,400."

77. **Cost Gamification** — Leaderboard: "Team Payments reduced their AWS spend by 18% this month! 🏆" Badges for optimization milestones. Make cost optimization fun and competitive.

78. **Automatic Spot Instance Migration** — Identify workloads that are spot-compatible (stateless, fault-tolerant) and automatically migrate them from on-demand to spot. 60-90% savings with zero manual effort.

79. **"What's This Costing Me?" Chrome Extension** — Hover over any resource in the AWS Console and see its monthly cost. Like a price tag on every resource. Because AWS deliberately makes this hard to see.

80. **Multi-Cloud Cost Normalization** — Normalize costs across AWS, GCP, and Azure into a single dashboard. "Your compute costs $X on AWS. The equivalent on GCP would cost $Y." Help teams make informed multi-cloud decisions.

81. **Cost-Aware Autoscaling** — Replace AWS's native autoscaling with a cost-aware version. Instead of just scaling on CPU/memory, factor in cost. "We could scale to 20 instances, but 12 instances + a queue would handle the load at 40% less cost."

82. **Invoice Dispute Assistant** — AI that reviews your AWS bill for billing errors, credits you're owed, and generates dispute emails. AWS makes billing mistakes more often than people think.

---

## Phase 3: Differentiation & Moat (18 ideas)

### Beating AWS Native Cost Anomaly Detection

83. **Speed** — AWS Cost Anomaly Detection has a 24-48 hour delay. dd0c/cost detects anomalies in minutes via CloudTrail events + CloudWatch billing metrics. This alone is a 100x improvement.

84. **Actionability** — AWS tells you "anomaly detected." dd0c tells you "anomaly detected → here's the specific resource → here's who created it → here's the one-click fix." Context + action, not just a notification.

85. **UX That Doesn't Make You Want to Cry** — AWS Cost Anomaly Detection is buried in the Billing console behind 4 clicks. The UI is a table with tiny text. dd0c is a beautiful, purpose-built dashboard with Slack-native alerts.

86. **Tunable Sensitivity** — AWS's ML model is a black box. dd0c lets you tune sensitivity per service, per team, per account. "I expect RDS to fluctuate ±20%, but EC2 should be stable within ±5%."

87. **Remediation Built In** — AWS detects. dd0c detects AND fixes. The gap between "knowing" and "doing" is where all the value is.

### Beating Vantage / CloudHealth

88. **Time-to-Value** — Vantage requires connecting your CUR, waiting for data ingestion, configuring dashboards. dd0c: connect your AWS account, get your first anomaly alert in under 10 minutes. Vercel-speed onboarding.

89. **Pricing Transparency** — CloudHealth/Apptio: "Contact Sales." Vantage: reasonable but still opaque at scale. dd0c: pricing on the website, self-serve signup, no sales calls ever.

90. **Focus** — Vantage is becoming a broad FinOps platform (Kubernetes costs, unit economics, budgets, reports). dd0c/cost does ONE thing: detect anomalies and fix them. Focused tools beat Swiss Army knives.

91. **Developer-First, Not Finance-First** — CloudHealth was built for FinOps teams and CFOs. dd0c is built for the engineer who gets paged when something breaks. Different user, different UX, different value prop.

92. **Real-Time, Not Daily** — Vantage updates costs daily. dd0c provides near-real-time monitoring. For a team burning $100/hour on a runaway resource, daily updates mean $2,400 wasted before you even know.

### Building the Moat

93. **Cross-Module Data Flywheel** — dd0c/cost knows your spend. dd0c/portal knows who owns what. dd0c/alert knows your incident patterns. Together, they create an intelligence layer no single-purpose tool can match. "The payment service owned by Team Alpha had a cost spike correlated with the deployment that triggered 3 alerts."

94. **Anonymized Benchmarking Network** — The more customers dd0c has, the better the benchmarking data. "Your RDS spend per GB is 2x the median." This data is exclusive to dd0c and improves with scale. Classic network effect.

95. **Optimization Intelligence Accumulation** — Every remediation action taken through dd0c trains the system. "When customers see this pattern, they usually do X." Over time, dd0c's recommendations become eerily accurate. Data moat.

96. **Open-Source Agent, Paid Dashboard** — The in-VPC agent is open source. This builds trust (customers can audit the code), creates community contributions, and makes dd0c the default choice. The dashboard/alerting/remediation is the paid layer.

97. **Terraform/Pulumi Provider** — `dd0c_cost_monitor` as a Terraform resource. Define your cost policies as code. This embeds dd0c into the infrastructure-as-code workflow, making it sticky.

98. **Slack-First Architecture** — Most FinOps tools are dashboard-first. dd0c is Slack-first. Engineers live in Slack. Alerts, actions, reports — all in Slack. The dashboard exists for deep dives, but daily interaction is in Slack. This is a UX moat.

99. **Multi-Cloud (Strategic Expansion)** — Start AWS-only (Brian's expertise). Add GCP and Azure in Year 2. Become the cross-cloud cost anomaly layer. No single cloud vendor will build this because it's against their interest.

100. **API-First for Automation** — Full API for everything. Let customers build custom workflows: "When dd0c detects a spike > $500, automatically create a Jira ticket and page the team lead." Programmable FinOps.

---

## Phase 4: Anti-Ideas & Red Team (12 ideas)

### Why This Could Fail

101. **AWS Improves Cost Explorer** — AWS could ship real-time billing, better anomaly detection, and native Slack integration. They have the data advantage (it's their platform). Counter: AWS has had 15 years to make billing UX good and hasn't. Their incentive is for you to SPEND more, not less. They'll never build a great cost reduction tool.

102. **Vantage Eats Our Lunch** — Vantage is well-funded, developer-friendly, and already has momentum. They could add real-time anomaly detection tomorrow. Counter: Vantage is going broad (FinOps platform). We're going deep (anomaly detection + remediation). Different strategies.

103. **IAM Permission Anxiety** — Customers won't give dd0c the IAM permissions needed for remediation (terminate instances, modify resources). Counter: Tiered permissions. Read-only for detection (low trust barrier). Write permissions only for remediation (opt-in). Open-source agent for auditability.

104. **Race to the Bottom on Pricing** — Cost optimization tools compete on price because their value prop is "we save you money." If you charge too much relative to savings, customers leave. Counter: Price as % of savings identified, not flat fee. Align incentives.

105. **False Positive Fatigue** — If dd0c alerts too often on non-issues, users will ignore it (same problem as AWS native). Counter: Composite anomaly scoring, tunable sensitivity, and a "snooze" mechanism. Learn from user feedback to reduce false positives over time.

106. **Small Market Size** — Teams spending $10K-$500K/month is a specific segment. Below $10K, savings aren't worth the tool cost. Above $500K, they have dedicated FinOps teams using enterprise tools. Counter: This segment is actually massive — hundreds of thousands of AWS accounts. And the $500K ceiling can rise as dd0c matures.

107. **Security Breach Risk** — dd0c has read (and optionally write) access to customer AWS accounts. A breach would be catastrophic for trust. Counter: Minimal permissions, open-source agent, SOC 2 compliance from day 1, no storage of sensitive data (only cost metrics).

108. **"We'll Build It Internally"** — Platform teams at mid-size companies might build their own cost monitoring. Counter: They always underestimate the effort. Internal tools get abandoned. dd0c is cheaper than one engineer's time for a month.

109. **AWS Organizations Consolidated Billing Complexity** — Large orgs with complex account structures, SCPs, and consolidated billing make cost attribution incredibly hard. Counter: This is actually a FEATURE opportunity. If dd0c handles multi-account complexity well, it becomes indispensable.

110. **Terraform Cost Estimation Tools (Infracost) Expand** — Infracost could add post-deploy monitoring to complement their pre-deploy estimation. Counter: Different core competency. Infracost is CI/CD-focused. dd0c is runtime-focused. They're complementary, not competitive. Could even integrate.

111. **Economic Downturn Kills Cloud Spend** — If companies cut cloud budgets aggressively, there's less to optimize. Counter: Downturns INCREASE demand for cost optimization tools. When budgets tighten, every dollar matters more.

112. **Customer Churn After Optimization** — Customers use dd0c, optimize their spend, then cancel because there's nothing left to optimize. Counter: Cost drift is continuous. New resources, new team members, new services — waste regenerates. dd0c is a continuous need, not a one-time fix. Also, the monitoring/alerting value persists even after optimization.

---

## Phase 5: Synthesis

### Top 10 Ideas (Ranked by Impact × Feasibility)

| Rank | Idea | Why |
|------|------|-----|
| 1 | **CloudTrail Real-Time Event Detection** (#27, #29) | The single biggest differentiator vs. every competitor. Detect expensive resource creation in seconds, not days. This is the core innovation. |
| 2 | **Slack-Native Alerts with Action Buttons** (#60) | Where engineers live. Alert + context + one-click action in Slack = the entire value prop in one message. This IS the product for most users. |
| 3 | **One-Click Remediation Suite** (#40-44) | Stop, terminate, resize, schedule — all from the alert. Closing the gap between detection and action is the moat. |
| 4 | **Zombie Resource Hunter** (#73, #44) | Autonomous agent that continuously finds and flags waste. Set-and-forget value. This is the "it pays for itself" feature. |
| 5 | **End-of-Month Projection** (#56) | "You'll exceed budget by $7,200 unless you act." Simple, powerful, and something AWS does terribly. |
| 6 | **Team-Level Cost Attribution** (#51) | Accountability without blame. Each team sees their costs. Essential for organizations with 3+ engineering teams. |
| 7 | **Schedule Non-Prod Shutdown** (#42) | The single easiest win for any customer. "Turn off dev at night" = instant 62% savings on non-prod. Proves ROI in week 1. |
| 8 | **Cost Blast Radius for PRs** (#74) | Shift-left cost awareness. GitHub Action that comments estimated cost impact on PRs. Viral distribution mechanism (developers share cool GitHub Actions). |
| 9 | **Real-Time Cost Ticker** (#67) | Emotional hook. A live burn rate counter creates urgency and awareness. Makes cost visceral, not abstract. |
| 10 | **Rule-Based Guardrails** (#36) | Simple rules catch 80% of problems. "Alert if daily spend > 150% of average." Easy to implement, easy to understand, high value. |

### 3 Wild Cards 🃏

| Wild Card | Idea | Why It's Wild |
|-----------|------|---------------|
| 🃏 1 | **"Cost Replay" DVR** (#71) | Rewind your bill like a video. Correlate cost changes with CloudTrail events in a timeline. Nobody has this. It would be a demo-killer at conferences. |
| 🃏 2 | **Competitive Benchmarking Network** (#75, #94) | "Companies like yours spend 30% less on RDS." Anonymized cross-customer data creates a network effect moat that grows with every customer. Requires scale but is defensible. |
| 🃏 3 | **Invoice Dispute Assistant** (#82) | AI that finds AWS billing errors and generates dispute emails. AWS overcharges more than people realize. This would generate incredible word-of-mouth: "dd0c found $2,400 in billing errors on my account." |

### Recommended V1 Scope

**V1 Goal:** Get a customer from "connected AWS account" to "first anomaly detected and remediated" in under 10 minutes.

**V1 Features (4-6 week build):**

1. **AWS Account Connection** — IAM role with read-only billing + CloudTrail access. One CloudFormation template click.
2. **CloudTrail Event Monitoring** — Real-time detection of expensive resource creation (EC2, RDS, EMR, NAT Gateway, EBS volumes).
3. **CloudWatch Billing Polling** — 5-minute polling of EstimatedCharges for account-level anomaly detection.
4. **Statistical Anomaly Detection** — Z-score based, per-service, with configurable sensitivity (low/medium/high).
5. **Slack Integration** — Alerts with context (what, who, when, how much) and action buttons (Stop, Terminate, Snooze, Assign).
6. **Zombie Resource Scanner** — Daily scan for idle EC2 (CPU <5% for 7 days), unattached EBS volumes, orphaned EIPs, unused ELBs.
7. **One-Click Stop/Terminate** — Optional write permissions for direct remediation from Slack.
8. **End-of-Month Forecast** — Simple projection based on current burn rate with budget comparison.
9. **Daily Digest** — Morning Slack message with yesterday's spend, trend, and top anomalies.

**V1 Does NOT Include:**
- Multi-cloud (AWS only)
- CUR parsing (too complex for V1; use CloudWatch + CloudTrail)
- Savings Plan/RI optimization (Phase 2)
- Team attribution (requires tagging strategy; Phase 2)
- PR cost estimation (Phase 2; integrate with Infracost instead)
- Dashboard UI (Slack-first for V1; web dashboard in Phase 2)

**V1 Pricing:**
- Free: 1 AWS account, daily anomaly checks only
- Pro ($49/mo): 3 accounts, real-time detection, Slack alerts, remediation
- Business ($149/mo): Unlimited accounts, zombie hunter, forecasting, team features

**V1 Success Metric:** First 10 paying customers within 60 days of launch. Average customer saves >$500/month (10x the Pro price).

---

*Total ideas generated: 112*  
*Session complete. Let's build this thing.* 🔥
