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Yes, not a dashboard on top of the existing tools, but a replacement for them. One database owns the truth, and each website becomes a feed into and out of it: orders, inventory, shipping labels, returns, customer service, and the accounting connection in one place.

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It can start carrying real orders within weeks, then grow feature by feature while the business runs on it. I treat it as a product that keeps evolving, not a project with an end date.

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There are two problems here. The retyping is straightforward to automate, since an engine can reprice every product on a schedule. The harder problem is strategy: if the engine simply chases the lowest price, it automates the race to the bottom instead of ending it.

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So the engine never chases the floor. It works from tiered targets with per-product floors and cooldowns, and it recognizes the situations where holding a price is the better move.

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The fix is a rule enforced in code: the master catalog is written by people, never by a sync. Each storefront gets its own listing layer that can hold whatever that marketplace needs, but the sync jobs have no write path to the master at all.

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Then the sync files it as a suggestion and a person approves it. Corrections flow through review instead of overwriting silently.

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The disagreement is a symptom. The fix is one connection that pushes every transaction across with supporting evidence, plus a permanent record of every discrepancy anyone has investigated, so the same false alarm never costs an afternoon twice.

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A rule I build these systems around: a number that’s plausibly wrong is more dangerous than a page that’s obviously broken. The reconciliation is designed to fail loudly rather than drift quietly.

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All three happened, once each. The answer isn’t hoping for better-behaved agents; it’s making the unsafe operations impossible. Guard hooks block dangerous git and test commands, a coordination layer lets sessions see each other and queue instead of colliding, and each session works in its own isolated checkout by default.

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The rule gets a hook, the hook gets a test, and the incident gets written down so no future session repeats it.

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Built in a weekend, partly to learn where AI-assisted OCR actually breaks. The answer: reading crumpled thermal paper. The durable lesson was to never trust a model’s reading without keeping the original image to verify against.

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That lesson carried directly into my production work: store the raw input at every ingestion point, and parse it afterward.

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Yes, after a human has tested it first. A team of ten of us automated a modern ERP with Selenium and Cucumber: readable Given/When/Then specifications, run nightly in Jenkins. The manual exploratory pass stays, because it finds the bugs no script was told to look for.

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I built an arcade shooter inside that ceiling: five attackers, three destructible bases with eight damage states each, a two-hit boss, a bomb pickup, a charge-based teleport, and a points shop. Where the tooling had no answer I paid for it in volume. Every alien-versus-projectile pair is written out by hand because there was no loop to write it in.

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The lesson landed years later: the shape of your code is dictated by what your language refuses to give you. A loop and a collection aren’t elegance, they’re the ability to add a sixth alien without editing fifteen places.

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My portfolio, presented as a service desk, because that’s how the work actually arrives. Every project here began as a request from someone, described in their own words, and ended as running software. Each ticket shows the original problem, the working conversation, and the measured result.

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If you are short on time: DSG-001 is the main body of work (an ERP handling ≈520 orders a day), DSG-002 is the most interesting engineering problem (repricing strategy), and DSG-005 shows how I work with AI tooling. The Resume link in the top bar is the fast path, and "Exit help desk mode" returns to the standard site.