From Concept to Production
Seven stages. One person. Full cycle.
I am the researcher, the definer, the designer, the builder, the QA tester, the shipper. Every role in this pipeline is me. I work with teams, but I don't depend on them to cross the finish line.
AI agents amplify every stage under my direction. Research synthesis, prototype iteration, code generation, deployment orchestration, monitoring. They accelerate the execution. I own the decisions. The thinking is human. The output is amplified.
Understand & Research
I do the research myself. No handoff to a separate researcher.
User interviews, competitive analysis, analytics review, current-state audit. I go straight to the source. AI helps me synthesize sessions, spot patterns across datasets, and flag assumptions I might have missed. But I ask the questions. I watch the recordings. I decide what matters.
Define & Strategize
I scope the feature. I set the principles. No PM gatekeeper.
Journey maps, prioritization, success metrics, design principles. I define what we are solving and why before anyone touches a design tool. AI helps me generate journey alternatives, stress-test assumptions against edge cases I might not have considered, and document decisions as I go.
Ideate & Prototype
Human-led exploration. AI-accelerated iteration.
I sketch in Figma first. Low-fi wireframes, flow diagrams, rough layouts. The thinking is mine — the information architecture, the decision hierarchy, the sequencing. Once the structure is right, AI helps me generate visual alternatives, fill in component variations, and spin up clickable prototypes faster so I can test sooner.
Test & Iterate
I watch every session. I decide what to fix.
Usability tests, stakeholder walkthroughs, pattern analysis. If one person struggles, I note it. If three struggle, I redesign it. AI helps me pull themes across test sessions, compile findings faster, and track which patterns keep appearing across projects so I don't solve the same problem twice.
At this point, the process changes.
Human direction shifts to AI-amplified execution.
Steps 1 through 4 are where the thinking happens. Research, strategy, design, testing. I own every decision. No AI shortcuts on judgment. Step 5 is where AI flips the switch. The foundation is locked, the direction is clear. Now I direct agents to build, iterate, and ship at a velocity most teams cannot match.
Build
AI-amplifiedFoundation is locked. AI flips the switch on execution.
I direct agents to generate code, write tests, scaffold components. They execute under my feedback and review. Every pull request runs through AI-assisted review alongside my eyes. I catch issues before they hit production. The result: what takes most teams two weeks ships in two days, without cutting corners on judgment.
Deploy
AI-amplifiedI handle the pipeline. Code doesn't ship until I ship it.
Docker images, CI/CD pipelines, DNS, SSL, environment configs, monitoring. I build the deployment infrastructure alongside the feature so there is no 'throw it over the wall to DevOps.' If something breaks at 2am, I know the stack well enough to fix it without escalating.
Measure & Optimize
AI-amplifiedDid it move the needle? I track it. I iterate it.
Post-launch metrics, user feedback, session replays, support ticket analysis. I don't launch and walk away. I watch how people actually use what I built, identify new friction points, and prioritize the next iteration. AI helps me surface anomalies across datasets and flag regression patterns early.
The Product Engineer Difference
One person, full cycle.
From research to deploy. No handoff tax, no translation loss. The person who designs it builds it. The person who builds it ships it.
Human direction, AI amplification.
I do the thinking. I set the strategy. AI accelerates the execution under my feedback. That means I ship what takes most teams two weeks in two days, without sacrificing judgment.
No PM buffer, no handoff chain.
I scope features, prioritize decisions, and manage tradeoffs directly with stakeholders. The person you talk to is the person building it. One conversation replaces a chain of meetings.
Design with reality, not theory.
I design in the stack. I prototype in production-grade tools. Every decision is made knowing how it will be built, deployed, and maintained. No surprises at implementation time.
Tools I Use
Design
Figma, Pen & Paper
Build
Next.js, React, Vue, Python, PHP, Node.js
Ship
Docker, Vercel, Cloudflare, CI/CD, AWS
Amplify
Claude Code, Pi, Hermes, Codex
Test
Production monitoring, Umami, session replay
Manage
Obsidian, Linear, GitHub, n8n
What to Expect
I ask a lot of questions upfront.
I need to understand the problem, constraints, and goals before I design or build anything. Expect a deep discovery phase.
I show work early and often.
First in Figma, then in a live staging environment. I don't disappear for two weeks. You see progress in real time.
I push back when it hurts the user or the architecture.
I'm collaborative but direct. If a requirement creates a bad experience or technical debt that will bite you later, I will explain why and propose alternatives.
I ship the full pipeline.
Design, code, deploy, monitor. I don't hand off and disappear. I see features through to production and measure their impact. That is the full cycle.
Let's Work Together
If this sounds like how you want features built, let's talk.