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AI product direction

Turn AI uncertainty into a clear product direction.

Choose what to build, prove it with a working prototype, and move forward with confidence.

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Elisha Terada
IntentBehaviorEvidenceBuild

Experience grounded in shipped work

15+ yearsbuilding digital products
200,000+people using Brancher.ai
Multi-million-dollardigital programs led at Fresh Consulting

Ways to work together

Bring structure to the decision before scale makes it expensive.

Each engagement is shaped around the uncertainty preventing a good product decision, not a predetermined package of AI features.

01

Opportunity direction

Decide where AI can create meaningful value

When this helps

You have several plausible opportunities, competing stakeholder opinions, and no defensible reason to choose one direction over another.

What you leave with

A prioritized opportunity, a clear user and business case, the assumptions that matter most, and a decision about what deserves investment.

02

Working prototype

Turn the strongest opportunity into a working prototype

When this helps

The idea sounds promising in a presentation, but nobody has experienced how the product should behave in a real workflow.

What you leave with

A tangible product experience your users, leaders, and technical team can evaluate together, plus evidence about what should change next.

03

Build direction

Give the team a practical direction for the build

When this helps

The prototype has momentum, but product behavior, data, architecture, ownership, and delivery constraints are still disconnected.

What you leave with

A coherent product model, technical direction, risk map, and implementation plan grounded in what the prototype revealed.

The work expands only when the evidence supports the next commitment.

The goal is not to prove that AI can do something. It is to prove that this product should exist, how it should behave, and what your team should do next.

Selected evidence

Strategy is more credible when it survives the build.

These projects span product strategy, interaction, technical prototyping, architecture, and production delivery.

Visual explainers

Technology, made understandable.

Interactive field guides that reveal how modern AI systems work without requiring you to become an AI expert.

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What a trusted partner should provide

Leadership that connects ambition to delivery.

As Technical Innovation Director at Fresh Consulting, I bridge executive intent, emerging technology, and the teams responsible for making the product real.

Complex delivery stays understandable

I have led multi-million-dollar digital programs while keeping client stakeholders, product decisions, and global delivery teams aligned.

The value becomes visible early

Rapid AI prototypes replace abstract promises with something decision makers can experience, evaluate, and fund in weeks rather than months.

Global teams move as one

I have rebuilt collaboration across U.S., LATAM, and APAC teams, connecting technology, design, hardware, and client leadership around shared outcomes.

Emerging technology serves the business

I connect AI, automation, SaaS, and third-party platforms to practical product opportunities that can create client confidence and commercial momentum.

Writings

How I think about the decisions behind AI products.

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Questions before we talk

A clearer first conversation starts here.

01When is the right time to bring you in?+

When an AI opportunity matters but the product direction is still uncertain. That may be before a roadmap exists, after a demo creates momentum, or when a prototype needs to become a credible build decision.

02Do you only advise, or do you build?+

Both. I work from product and business framing through interaction design, technical prototyping, architecture, and delivery direction. The balance depends on which uncertainty is holding the team back.

03Can you work with our existing product and engineering teams?+

Yes. The goal is to create shared clarity across leadership, product, design, engineering, operations, and subject experts, then leave the team with decisions and artifacts they can carry forward.

04Does every engagement begin with an AI solution?+

No. AI is a means, not the requirement. If a better workflow, clearer product behavior, conventional software, or improved data foundation is the stronger answer, the work should reveal that.

05How are engagements structured?+

Some opportunities fit a focused strategy or prototype engagement. Others require a broader delivery team and may be better supported through Fresh Consulting. The first conversation is used to determine the right fit.

06What do we need before starting?+

A meaningful problem, access to the people who understand it, and a willingness to test assumptions. You do not need a complete AI strategy, polished requirements, or a selected model.

07What happens in the first conversation?+

We discuss the decision your organization is facing, what has already been tried, where uncertainty remains, and whether a focused engagement could create useful evidence. It is a fit conversation, not a commitment.

An important opportunity deserves a clearer decision

Tell me what your team is trying to make possible.

We will identify the decision in front of you, where uncertainty remains, and whether making the idea tangible is the right next move.

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