Product Development 101

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Investors fund traction.

Traction requires ~10x better product performance than status quo.

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What specific user behaviors would convince someone your product has real traction?

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Post-Cambrian explosion:

Rapid AI product launches, followed by rapid extinction.

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Most AI products fail due to poor execution, unclear UX, and lack of user trust.

How are you addressing execution risk?

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Codewalla is a NYC-rooted AI-native product studio.

We partner with startups and enterprises to de-risk product development. We use three lenses to guide product clarity and traction.

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LENS 1: Investor Lens

What investors look for — and how it’s changed.

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Market, Early traction, Sharp problem, Focused solution.

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AI changes expectations:

Model access is not a moat. What gives your product enduring leverage beyond the underlying model?

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Modern fundable signals:

Usage depth, compounding systems, clear wedge. Where are you seeing real user pull — retention, repeat behavior, or feature demand?

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Credibility risks:

Vague AI claims, shallow adoption, overbuilt MVPs. Is your current product scope helping or hurting your credibility?

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SignalFrame (Case Study)

Ambient Manager Assistant

Pitch works because the product delivers behavior change. What is the smallest version of your product that reveals the long-term vision?

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LENS 2: Product Craft Lens

What hasn’t changed — even in an AI-saturated environment.

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Real pain > Ideas

Clarity > Coverage

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An MVP is a tool to learn — not a lite version of the final product. Strong teams build in tight loops, measure behavior, and adjust quickly.

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Operationalize product craft:

Outcome-based roadmaps, aligned success/failure definitions.

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Common pitfalls:

Overbuilding, no tracking, analytics, feature management, automation, experimentation, observability AI masking poor UX.

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Good product craft is required for trustworthy AI.

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LENS 3: AI Lens

Building with AI — what changes, what breaks, what works.

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AI introduces new capabilities — and new failure modes

There is a trust and usability gap.

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Products must scaffold the gap:

Fallback logic, visibility, refusal handling.

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Maximalist AI claims often fail — design must balance power with predictability.

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Case Study: SignalFrame

Ambient Manager Assistant

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Case Study: Gamified Training Platform

Enterprise SAAS (Mature product, AI retrofitted for ops leverage)

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Case Study: Global e-Commerce Product

Legacy product, leveraging AI to modernize

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Opportunities for beginners and experts.

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Comparison:

SignalFrame : Ground-up

Gamified Training Platform: Retrofitted AI

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AI is many things, but it’s not a shortcut.

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SUMMARY

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The 3 lenses increase odds and reduce product risk, use them together.

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Investor Lens

Fundable stories require traction and proof.

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Product Craft Lens

Iteration, learning, clarity, outcome focus.

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AI Lens

Fill the gap, design for trust, scaffold intelligently.

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