what were you using before?

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AI

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10. Audit Trail Summarizer
- description: Converts system logs into readable summaries for auditors.
- technical skill required: 5/10
- estimated market size: $1.2B

9. KYC/AML Document Validator
- description: Validates customer docs and flags suspicious data or patterns.
- technical skill required: 7/10
- estimated market size: $5B

8. Automated ESG Report Writer
- description: Converts internal metrics and docs into ESG-compliant reports.
- technical skill required: 6/10
- estimated market size: $2.5B

7. Audit Prep Interview Assistant
- description: Simulates audit interviews to train employees using policy docs.
- technical skill required: 4/10
- estimated market size: $1B

6. LLM-Powered Evidence Organizer
- description: Auto-tags and organizes audit evidence by linking it to controls.
- technical skill required: 6/10
- estimated market size: $1.5B

5. Regulation Diff Tracker
- description: Tracks legal changes and auto-compares against internal policies.
- technical skill required: 5/10
- estimated market size: $2B

4. Smart Audit Sampling Engine
- description: Finds anomalies and suggests optimal samples from full datasets.
- technical skill required: 6/10
- estimated market size: $3B

3. Email & Chat Compliance Scanner
- description: Flags policy violations in internal comms via browser extension or API.
- technical skill required: 5/10
- estimated market size: $4B

2. Continuous Document Auditor
- description: Monitors internal files in real-time for compliance issues using LLMs.
- technical skill required: 7/10
- estimated market size: $6B

1. AI-Powered Policy Checker
- description: Scans corporate policies for gaps or violations against GDPR/AML/ESG standards.
- technical skill required: 6/10
- estimated market size: $5B

is basically the same, except for me spinning up dev tools quicker

Definitely!

Also, I forgot to answer your initial question of "how have you seen your workflows change?"

I'd say my overall workflows are really similar, I just spend more time writing prompts and reviewing code than I do actually writing code, and I can iterate quicker, but the overall process..

don't review the code at all, I just test it by running the script. I think this is fine for me because I don't want to overengineer small projects I build just to automate something or get work done quicker.

Depends on the use-case.

For production code in large repositories, I review every single line of code manually. Sometimes I make small manual changes to fix things, or will reprompt for larger changes.

I have ended up building more 'internal tools' for myself using AI coding tools in which I...

Until attendance picks up I decided to only run two chats per week. Do either of these work for you: Tuesday 9AM PST, Sunday 5PM PST?