Erdeniz TunçProduct Manager
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How I use AI

AI helps with specific steps. I make the product decisions.

AI changes every day. I keep learning, like everyone. These are the tools I use today.

How each one runs

1Thinking and research

Optivideo · Optifeed

  1. InputRecorded internal interviews.
  2. AINotebookLM answers my questions. Interviews are the sources.
  3. AINotebookLM turns them into notes.
  4. AIClaude Code reads the notes.
  5. OutputA TODO.md of prototype changes.
  6. I decideI keep, cut or defer each item.
  7. NextPrototype development begins. Then another feedback round.

Also

  • PostHog data → a change list. On this site.
  • UX research → grouped problems.

Seen in Optivideo

2Prototyping and building

Product development model · Optifeed

  1. I decideNine-field PRD. One Key User Action.
  2. AIA coding agent builds a frontend prototype. In a day or two.
  3. InputInterviewees react to it. CTO checks feasibility.
  4. AIWrites the Product Knowledge Document. From prototype code and notes.
  5. I decideI set V1's inputs. AI formats scope, never chooses.
  6. NextPhased, spec-driven build. Or engineering handoff.

Also

  • Behaviour data → built, then measured again. On this site.
  • UX research → a tested build, not slides.
Prompt: Product Knowledge Document
You are a product architect. Read the codebase in this directory, thoroughly source files, types, API routes, state management, data structures config files, and any existing documentation. Also read the discovery notes provided below.
Then produce a single, comprehensive Product Knowledge Document in Markdown.
The document must be written as if for a new team member or an AI agent that
will work on this product. It must reflect only what actually exists in the code
and what was confirmed during discovery. Do not invent features, do not speculate
about future plans.
Required sections:
1. Goal: one sentence — what does this product do and for whom?
2. Core Questions: 3 to 6 questions the product answers for its user
3. Product Definition: 2 to 3 paragraphs. What it is, what it is not.
4. Current Problem / Target Experience: side-by-side comparison
5. End-to-End Product Workflow: ASCII block diagram of the full flow
6. Key Decision Logic: branching and routing logic as ASCII decision trees
7. Data Model: core TypeScript interfaces with field-level explanations
8. State Management: how state flows through the product
9. Scoring or Classification Logic: criteria and weights as a table, if applicable
10. Invalid / Weak Signals: what the product explicitly ignores and why
11. Output / Export: what the product produces for the user
12. V1 Scope: In Scope / Out of Scope as two lists
13. Open Questions: unresolved decisions visible in the code
14. Known Limitations: gaps, edge cases, honest weaknesses
15. Success Criteria: how you would know the product is working
For every major decision in the product, add a line:
"Design principle: [why this choice was made]."
Discovery notes:
[PASTE NOTES HERE / Or tell the coding agent which md files to read]
Prompt: V1 scope
You have the product knowledge document below.
Your task is to define V1.
V1 must deliver the core user flow and the core value proposition.
Nothing more.
Use the following inputs to scope V1:
CTO decisions and constraints:
[PASTE CTO DECISIONS]
Core requirements from the discovery loop:
[PASTE DISCOVERY REQUIREMENTS]
Must-haves for V1:
[PASTE MUST-HAVES]
Using the knowledge document and the inputs above, produce:
1. Core User Flow: the path from entry to core value, step by step
2. V1 Scope: what is in, what is out, as two lists
3. No-Gos: what is deliberately excluded from V1
4. Success Signal: how you will know V1 is working
[PASTE KNOWLEDGE DOCUMENT / Or tell the coding agent which md files to read]

Seen in the product development model, Optivideo

3Turning manual work into tools

OptiGTM · Optifeed

  1. InputMarketing researched leads by hand.
  2. I decideFlow mapped in Miro. Scope agreed with the CTO.
  3. AIBuilt in Rails. With Claude Code and Codex.
  4. AIClaude explains each candidate company.
  5. OutputResults saved per project.
  6. I decideMarketing reviews before any outreach.

Seen in OptiGTM

Rules in all three

  1. AI works from interviews, notes and code.
  2. I start with the smallest version.
  3. I test ideas by building them.
  4. A person reviews every AI output.
  5. I agree scope with the CTO.

Full idea-to-V1 workflow: How I work as a Product Engineer →

Email me →What I am open to →