David Dacruz

Capabilities

Senior engineering where the problem is still taking shape.

I help turn ambiguous product and workflow problems into a system a team can run, inspect, and continue improving.

01

AI systems

Agents and workflows that do useful work inside the tools a team already uses.

Where it starts

Research, routing, support, reporting, and follow-up still depend on someone moving context by hand.

What I build

I map the decision points, connect the right data, add model judgment where it is reliable, and keep human review where it matters.

Typical outputs
  • Agent and workflow architecture
  • Knowledge and retrieval systems
  • Tool integrations and structured outputs
  • Evaluation, failure handling, and operator controls
02

Product engineering

From a rough idea to software people can actually use.

Where it starts

The product is clear in conversation but breaks down when architecture, interface, data, and delivery have to meet.

What I build

I turn the core behavior into a scoped system, build the critical path, and make the trade-offs visible before they become expensive.

Typical outputs
  • Product and technical framing
  • Full-stack web applications
  • APIs, data flows, and integrations
  • Launch, instrumentation, and iteration
03

Technical direction

Senior engineering judgment for founders and teams between product decisions.

Where it starts

A team can ship quickly and still move in the wrong technical direction. The cost shows up later as rewrites, brittle delivery, or stalled hiring.

What I build

I work close to the product and code, pressure-test decisions, define the operating plan, and help the team keep momentum.

Typical outputs
  • Architecture and delivery reviews
  • Roadmap and scope decisions
  • Technical due diligence
  • Hands-on support for critical releases
04

Technical discovery

Search and AI-readable product surfaces built into the system, not added at the end.

Where it starts

Strong work stays invisible when the site, content model, and public proof do not explain the business clearly to search engines or AI systems.

What I build

I align information architecture, structured data, content, performance, and evidence so the product is easier to find and easier to understand.

Typical outputs
  • Information architecture and technical SEO
  • Structured data and entity signals
  • AI-readable source files and content models
  • Measurement and discovery diagnostics

Operating model

Small loop. Visible progress.

The exact work changes. The delivery rhythm stays intentionally simple.

01

Frame

I define the decision, user behavior, and failure modes that matter most.

02

Build

The critical path ships early, so real inputs shape the next decision.

03

Stress-test

Outputs, permissions, exceptions, and human control are tested before release.

04

Hand off

The finished system stays understandable, measurable, and ready to evolve.

Good fit

The work is concrete, even if the answer is not yet obvious.

  • There is a real workflow, product, or decision to improve.
  • You want the person shaping the system to stay close to the build.
  • The work can start narrow and become more capable after it proves itself.
  • You value clear trade-offs, visible progress, and a clean handoff.

Not a fit

The project needs theatre more than engineering.

  • You need a large outsourced delivery team.
  • The brief is only to add an AI label to an existing product.
  • There is no owner available to make product decisions.
  • The outcome depends on invented proof or inflated claims.

Common questions

A few useful answers before we talk.

Scope, location, and working style—without turning the site into a service catalogue.

What does David Dacruz build?

David designs and ships AI agent systems, production web products, technical architecture, and search-ready product surfaces. He can own the path from an unclear problem to a working system.

Where is David Dacruz based?

David is based in Ericeira, in the Lisboa region of Portugal. He works with teams across Europe and remotely.

What kind of project is the best fit?

The strongest fit is a real product, workflow, or technical decision that needs senior judgment and hands-on delivery. The scope can start small as long as there is an owner who can make product decisions.

How does David approach an AI system?

He starts with the workflow, decision points, source data, and failure modes. Model judgment is added where it is reliable, with human review, evaluation, permissions, and recovery paths built into the operating system.

Can David work as a hands-on technical lead?

Yes. David can frame architecture and delivery decisions while staying close to the critical code, product behavior, and release path.

Does David work on Bitcoin and Ordinals products?

Yes. His public work includes Pizza Ninjas, Pizza Pets, and Project Spartacus, covering inscription pipelines, recursive assets, on-chain systems, and mempool-aware operations.

Has David shipped Ethereum smart contracts?

Yes. For Yakuza Inc., David owned the ERC-721 contract and mint pipeline from allowlist through public sale. The 3,223-token launch collected 321.4 ETH through the contract.

A difficult technical problem is enough to begin.

I can help turn it into a clear first move.

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