David Dacruz

Services

I make hard technical decisions and stay to implement them.

I work directly with small teams on AI systems, software products, and difficult releases. I define the risk, choose the smallest sound path, and build with the people who will own it.

Discuss a project Services 42 Fellowship

Services

Start with the problem in front of you.

01

Diagnose

Clarify the decision, risk, and best next move before committing to a build.

02

Build

Turn a defined workflow or product decision into software the team can operate.

03

Lead & enable

Add senior technical direction or give the team a shared working method.

04

Explain & discover

Make technical work understandable, verifiable, searchable, and easier to cite.

Featured starting points

The complete service pages contain scope, pricing where published, related guidance, and the right project enquiry route.

AI workflow opportunity assessment

AI Opportunity Audit

I audit one workflow, rank the opportunities, and hand you a 30-day action plan before a build starts.

  1. The problem

    One workflow is costing time or accuracy. The team knows it hurts, but not whether the answer is AI, simpler software, or a process fix.

  2. My job

    I map the inputs, decisions, handoffs, and failure points. Then I rank each change by value, effort, risk, and required human control.

  3. The outcome
    • Workflow findings
    • 3–7 ranked opportunities
    • Recommendation detail
    • 30-day action plan
AI search visibility diagnostic

AI Visibility Audit

I test real buyer questions, preserve the answers and cited sources, and show which evidence gaps are shaping AI recommendations.

  1. The problem

    The business is visible for its own name but missing, misdescribed, or outranked when buyers ask AI products to compare providers.

  2. My job

    I define the question set, record dated answers, compare competitors and cited URLs, and rank the smallest defensible fixes. A free Snapshot is available when you only need an initial signal.

  3. The outcome
    • Buyer-question baseline
    • Answer and competitor record
    • Citation and evidence-gap map
    • Prioritised action plan
AI automation consulting

AI systems

I build AI workflows around the way your team already works, with a human on the decisions that matter.

  1. The problem

    Manual research, support, reporting, or follow-up is slow, inconsistent, and split across tools.

  2. My job

    I connect the data, automate testable steps, log important actions, and require approval where the cost of a mistake is real.

  3. The outcome
    • AI workflow design
    • Knowledge bases and retrieval
    • Integrations with the tools you already use
    • Testing, safeguards, and human approval
Production AI agents

AI agent development

I build focused AI agents with controlled context, tool permissions, evaluations, logs, and explicit human approval.

  1. The problem

    A workflow needs judgment across changing inputs and several tools, but a simple automation cannot handle the branching safely.

  2. My job

    I define the agent's job and boundaries, connect approved context and tools, evaluate representative cases, and release actions gradually with logs and approval.

  3. The outcome
    • Agent contract and permission model
    • Retrieval, tools, state, and integrations
    • Evaluation and regression suite
    • Logs, approvals, fallback, and operating notes
Practical AI training for small teams

AI team training

I train small teams on a real workflow, then help them leave with a working prototype, evaluation method, and operating guide.

  1. The problem

    People are experimenting with AI individually, but the team lacks a shared method for choosing use cases, checking output, and using company data safely.

  2. My job

    I tailor a live workshop or private cohort to the team’s roles, tools, and current work. We practise on representative cases and finish with a capstone the team can keep using.

  3. The outcome
    • AI foundations for decision-makers
    • Workflow automation labs
    • AI agent engineering sprints
    • Team playbook, evaluation cases, and handover
Custom software development

Product engineering

I turn a product decision into working software, then stay for launch and the first hard lessons.

  1. The problem

    The idea is clear in a meeting. The interface, data, architecture, and delivery plan still disagree.

  2. My job

    I define the smallest release worth shipping, build the end-to-end path, and document trade-offs before they become expensive.

  3. The outcome
    • Product definition and technical plan
    • Full-stack web applications
    • APIs, data flows, and integrations
    • Launch, analytics, and iteration
Technical direction

Fractional CTO

I step in when a product needs a hard technical decision, a recovery plan, or a release that cannot drift.

  1. The problem

    The team is shipping, but unclear architecture, ownership, or delivery risk is slowing the next decision.

  2. My job

    I stay close to the product and code, challenge risky assumptions, record the decisions, and help ship the critical path.

  3. The outcome
    • Architecture and delivery reviews
    • Roadmap and scope decisions
    • Technical due diligence
    • Hands-on support for critical releases
Independent technical review

Technical audit

I inspect the code, architecture, delivery path, and operating risk behind one important technical decision.

  1. The problem

    A rewrite, investment, critical release, handover, or senior hire depends on a technical picture the team cannot yet verify.

  2. My job

    I scope the decision, inspect the available evidence, separate fact from inference, and rank the risks and next actions without assuming a rebuild.

  3. The outcome
    • System and ownership map
    • Code and delivery findings
    • Ranked technical risks
    • Prioritised action plan and decision gates
Technical writing services

Technical writing & publishing

I turn code, interviews, and evidence into technical articles, documentation, and reports people can use.

  1. The problem

    The knowledge is in the team and codebase. The reader still cannot act on it.

  2. My job

    I inspect the source material, interview the right people, verify the claims, write the piece, and carry it through technical review and publication.

  3. The outcome
    • Technical articles and explainers
    • Product and developer documentation
    • Research-backed technical reports
    • Editing, diagrams, metadata, and CMS publishing
AI visibility and citation services

GEO & SEO citations

I connect your entity, evidence, expert content, and public profiles so search and AI systems have clearer sources to retrieve and cite.

  1. The problem

    The business is credible, but names, services, claims, profiles, and proof are inconsistent or scattered across pages and platforms.

  2. My job

    I map the entity, verify the claims, implement the knowledge graph, publish citation-ready source pages, and strengthen legitimate external records without manufacturing mentions.

  3. The outcome
    • Entity and citation-gap audit
    • Knowledge graph and structured data
    • Evidence-led service and expert pages
    • Profile consistency and citation measurement
Selected proof See all case studies
Campus launch 42 Lisboa founding team

IT, pedagogy, systems, and launch operations

 Ethereum release 3,223-token launch

ERC-721 contract and mint pipeline

 Bitcoin release 1,500 inscriptions

Recursive assets and inscription operations

 Client feedback Source-linked reviews

Scored reviews and written recommendations

Working together

Make the risk visible. Ship the smallest useful proof.

The people making product decisions stay close to the work. I start with the riskiest useful slice and document what the team will inherit.

DD / SYSTEMS

Software decision loop

Every release creates evidence for the next decision.

  1. 01 Frame

    Define the outcome, constraints, and people affected.

    users · system · context
  2. 02 Decide

    Make trade-offs explicit and choose a reversible path.

    risk · ownership · scope
  3. 04 Observe

    Measure behavior, failures, and what the team learns.

    signals · feedback · recovery
  4. 03 Build

    Ship the smallest useful slice with controls in place.

    code · tests · release
I use the same loop for product decisions, system design, and delivery.

Good fit

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

  • There is a real product, workflow, or decision that needs to move.
  • You want senior technical thinking and hands-on implementation from the same person.
  • You are comfortable starting with a small, useful version and improving it from real feedback.
  • You value clear trade-offs, visible progress, and a clean handoff.

Not a fit

The project needs a different kind of team.

  • The project requires a large outsourced delivery team.
  • The goal is only to add an AI label without changing the product.
  • No one is available to make product decisions.
  • Success depends on claims that cannot be supported.

Common questions

The questions I hear most often.

Straight answers about the work, my background, and when an engagement makes sense.

What do I build?

I build AI workflows, web products, and the technical foundations behind them. I can take a messy problem from the first decision to working software—and leave the team with a system it can run.

Where am I based?

I am based in Ericeira, in the Lisboa region of Portugal. I work with teams across Europe and remotely.

What kind of project is the best fit?

A real product, workflow, or technical decision with an accountable owner. We can start small, but someone must be able to make product decisions and give access to the evidence.

How do I approach an AI system?

I start with the work: who owns it, what information moves, where decisions fail, and what a mistake costs. AI goes only where it can be tested. Permissions, review, logs, and recovery are part of the build.

Can I work as a hands-on technical lead?

Yes. I can set architecture and delivery direction while staying close to the critical code, product behaviour, and release path.

Do I work on Bitcoin and Ordinals products?

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

Have I shipped Ethereum smart contracts?

Yes. For Yakuza Inc., I 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.

An unfinished problem is enough.

Tell me what is blocked, risky, or costing the team time.

Discuss the project