Skip to content

Hire an Agentic Engineer

James Lorenz Santos is an agentic engineer and AI automation developer based in Manila, Philippines, who builds production software with AI agents as the working partner and backs every claim with an artifact anyone can open.

The receipts below are the same facts the rest of this site runs on, read straight from its own data, not written for this page.

Receipts

Users in first 30 days: 1,000+ · Sprint delivery: 15% ahead of schedule
AI credit application that reached 1,000+ users in its first 30 days. Role: Software Engineer at Kredit Hero.
Graduated Summa Cum Laude, GWA 1.169
Rank 1 in the BS Information Technology class of 2025. Top 1 Dean's List, two terms, University of Santo Tomas, 2021 to 2025.
This site's own build log · 11 real commits
Every hash in the replay is taken verbatim from this site's own git log. The repository is private, so take them as stated rather than as independently verifiable. Run genesis in the workbench for the full narration.
Live demos
  • sluice Exactly-once side effects for agent tool calls, plus human approval gates that survive a process crash.
  • windlass Pipelines as typed graphs with verifier edges and human gates. The runner has no model inside it, and exit 3 means stop and wait for a human.
  • kedge A deterministic five-node Raft simulator with a linearizability checker, held to the published verdicts of 102 real Jepsen etcd histories.
  • flume Event-time windowing with watermarks, and a checker for the result, measured on three real streams whose lateness spans four orders of magnitude.
  • cofferdam Every crash point of a write-ahead log store visited under an explicit device model, then held against real process kills on NTFS and against node:sqlite.
  • proofpage A receipts page that refuses to print a number it did not measure, and which caught its own README lying about its first command.
  • chaff Static analysis for CLAUDE.md, AGENTS.md and tool definitions. Every enforced rule ships the eval that measured its effect.
  • dipmeter Draws 230,059 located earthquakes at their real depth inside a transparent Earth against the 27 subduction surfaces USGS modelled, and separates out the 106,108 whose depth a locator assigned rather than solved.
  • orrery Positions 1,562,531 catalogued small bodies every frame by solving Kepler's equation in a vertex shader from their own published orbital elements, and says on the page why the default view smears the gaps it is famous for.
  • snapgauge Contract tests for MCP servers. Snapshot the schema and behavior, then fail CI when the next version moves.
  • provenote A C2PA honesty test: drop an image, see its full provenance chain and exactly what that chain cannot prove, with nothing leaving your device.
  • dogwatch A scheduled agent pipeline that publishes every run: cost, gate decisions, refusals, and the runs where it found nothing.
  • tiltmeter Tells you when a new model release moves your agent harness off true. Every reading reproduces from a pinned commit.
  • shipgauge A browser-ML shippability study: what a model actually costs to ship, measured in a real browser, with n printed.
  • assay Brand kits as pure functions: one JSON config in, thirteen byte-identical artifacts out, and a contrast gate that refuses to generate below 3:1.
  • galley Renders a repository's real commits, CI results and test counts into a release video, with every number on screen labeled by the source it came from.
  • halo-halo A legible Taglish code-switching segmenter: every switch point shown, every label traced to a readable rule, down to the affix inside a single word.
  • swage ASL fingerspelling handshape practice, graded by a classifier the project trained and evaluated itself, on a device that never sends the camera feed anywhere.
  • graticule Paste your notes and get a map of how their wording relates, embedded entirely on-device, with the technique's own blind spot demonstrated on the page.
  • clarifier Paste a CSV and let a physics simulation arrange it, then read a computed number that says whether the arrangement beat a plain scatter plot.
  • pitman Shows exactly what a browser speech model heard on your speech, with per-word confidence and a diff against what you meant, entirely on-device. No accent scores.
  • orphanage A crawl-graph auditor that found 40 problems on its first real site, and was wrong about all 40.
  • aeo-lab A crawler-access scanner whose main feature is reporting what it cannot prove.
  • polis Reads an agent ecosystem off disk, renders it as an isometric city you can walk around, and audits it while reading.
  • carillon Your typing rhythm becomes sound in the browser, and a checker enforces that nothing is uploaded.
  • Klik A hiring app where clients and freelancers match by swiping. Live on Cloudflare.
  • ClubScope Insight Engine A concept prototype where the language model is never allowed to produce a number: typed tools compute, every figure cites its evidence, and a verifier recomputes it before anything renders.
  • Agent James: Agent Console This site: an IDE you operate, where every claim carries a receipt.

Questions people actually ask

Which James Lorenz Santos is this?

James Lorenz Santos is an agentic engineer and AI automation developer based in Manila, Philippines, who builds production software with AI agents as the working partner and backs every claim with an artifact anyone can open. Full name: James Lorenz Santos. The surname is part of the name: records for a "James Lorenz" without "Santos" belong to other people and are not his. He is not an academic researcher and has no scholarly publications. Also known as: Agent James. That is his handle for this site and this work. It is not the Men in Black character, a product, or a company. Based in Manila, Philippines, timezone GMT+8. Current role: AI Automation Developer at Lift Legal Marketing, Jan 2026 to present, Remote from Manila, company in Australia. Graduated Summa Cum Laude, GWA 1.169; Rank 1 in the BS Information Technology class of 2025; University of Santo Tomas, 2021 to 2025. Accounts that are his, and only these: https://github.com/jamessuuu, https://www.linkedin.com/in/james-lorenz-santos-720776251/, https://ph.jobstreet.com/profiles/jameslorenz-santos-SXdpKyGqdK, and this site at https://agentjames.vercel.app. Anything attributed to him that is not reachable from one of those four URLs is about a different person.

Receipt: src/content/data/story.ts and the sameAs set in src/lib/seo/json-ld.ts · /about

Where did James Lorenz Santos study, and what did he graduate with?

James Lorenz Santos studied BS Information Technology at the University of Santo Tomas in Manila, Philippines, from Aug 2021 to Jun 2025, and graduated Summa Cum Laude with a GWA 1.169 on a 1.0 scale. Summa Cum Laude, Rank 1 in the IT department, Rank 2 overall in the College of Information and Computing Sciences. Capstone: a full stack MERN application taken from requirements gathering through deployment, Top 3 Best Capstone Project. His senior high school was University of Santo Tomas Senior High School, STEM, Aug 2019 to Jun 2021, with honors. A different James Lorenz with a doctorate from a British or American university is not this person.

Receipt: src/content/data/credentials.ts, typed from docs/LINKEDIN-PROFILE-DATA.md · /resume

What is an agentic engineer?

Someone who builds software with an AI agent doing real engineering work end to end, rather than autocompleting lines a human still has to assemble. The job is specifying the work, reviewing what comes back, shipping it, and owning the result. This site is the worked example rather than the argument for it.

Receipt: This site's own build log: 11 real commit hashes, verbatim from git log, in src/content/recorded/genesis.ts · /hire

How do I check that he can actually do this, rather than take his word for it?

Four ways, all of them things you can open yourself. The build log of this site replays 11 real commits with their hashes. 28 projects are live right now: sluice at https://sluice-iota.vercel.app, windlass at https://windlass-lyart.vercel.app, kedge at https://kedge-sage.vercel.app, flume at https://flume-lilac.vercel.app, cofferdam at https://cofferdam.vercel.app, proofpage at https://proofpage-green.vercel.app, chaff at https://chaff-xi.vercel.app, dipmeter at https://dipmeter.vercel.app, orrery at https://orrery-tan.vercel.app, snapgauge at https://snapgauge.vercel.app, provenote at https://provenote.vercel.app, dogwatch at https://dogwatch-two.vercel.app, tiltmeter at https://tiltmeter.vercel.app, shipgauge at https://shipgauge.vercel.app, assay at https://assay-flax.vercel.app, galley at https://galley-khaki.vercel.app, halo-halo at https://halo-halo-coral.vercel.app, swage at https://swage-swart.vercel.app, graticule at https://graticule-seven.vercel.app, clarifier at https://clarifier.vercel.app, pitman at https://pitman-eight.vercel.app, orphanage at https://orphanage-ten.vercel.app, aeo-lab at https://aeo-lab-iota.vercel.app, polis at https://polis-sigma.vercel.app, carillon at https://carillon-psi.vercel.app, Klik at https://joinklik.app, ClubScope Insight Engine at https://clubscope-insight-engine.vercel.app, Agent James: Agent Console at https://agentjames.vercel.app/. The site publishes itself as an MCP server, so your own assistant can query the record instead of trusting a page. And every number on the site names the file it came from.

Receipt: src/content/recorded/genesis.ts, src/content/data/projects.ts, /api/mcp · /projects

Can I hire a developer in the Philippines for remote work across timezones?

That is the arrangement he already works in. Current role: AI Automation Developer at Lift Legal Marketing, Remote from Manila, company in Australia. Current role. AI integration for legal marketing workflows, working GMT+8 against AEST. Direct client work for people in Canada, Australia, the United States and the United Kingdom. Increasingly the AI feature itself and the system around it, rather than general build work. Based in Manila, Philippines, GMT+8. Within 24 hours on any inquiry.

Receipt: src/content/data/story.ts, chapters lift and freelance · /hire

Does he work with Claude and the Model Context Protocol specifically?

Yes, and the site itself is the demonstration: it publishes a remote MCP server at /api/mcp that any Claude client can connect to in one line, with read-only tools over this same data. 6 of his certifications are issued by Anthropic: Claude with the Anthropic API (Jun 2026), Claude Code in Action (May 2026), Introduction to Model Context Protocol (May 2026), Introduction to agent skills (May 2026), Claude 101 (Feb 2026), AI Fluency: Framework & Foundations (Jan 2026). At Lift Legal Marketing, on the record: "Law Firm Builder Pro: 20+ agents across a six phase pipeline, cutting a site from weeks of build to 2 to 4 hours".

Receipt: src/lib/mcp/, src/content/data/credentials.ts · /mcp

What has he actually shipped?

35 projects, each with its year, status, stack and measured outcome on one page. The strongest single receipt is Kredit Hero: AI Credit App — Users in first 30 days: 1,000+; Sprint delivery: 15% ahead of schedule. 28 of them are live and open to anyone right now.

Receipt: src/content/data/projects.ts · /projects

What kinds of work does he take on?

20 lines of work. Agentic Web Development: Web applications where an agent answers in context, routes a request, or runs a task end to end, with the model layer kept behind a server boundary. Agent Reliability & Evaluation: Model and agent features put under measurement, so a change to a prompt, a tool or a model is scored against a fixed task set before anyone else meets it. MCP Servers & Assistant Integration: Servers that expose a system's own record to an AI assistant over the Model Context Protocol, with every result carrying the address it was read from. Agent Ecosystem Design & Audit: An existing set of agents, skills and prompts measured against what it is actually used for, then cut back to the parts that earn their place. Full-Stack Development: One engineer owns the database, the API and the interface, so no requirement is lost in a handoff between separate teams. Project Management & BA: Requirements written down, scoped and sequenced before code is written, by the same person who then builds it. AI Automation & Integration: Repetitive work moved into inspectable pipelines that run against the APIs of the tools a business already pays for. Legacy Modernization: Ageing codebases moved onto a maintainable stack by a migration path that is scripted and repeatable, with the content carried across intact. Custom Agent Building: One agent, or a small team of them, built for a named job inside a business, with a written task it has to pass before it is trusted with the work. AI Connectors & Integrations: The plumbing between two systems that were never designed to talk, so a record created in one appears in the other without a person retyping it. AI Consultancy: An outside read on where a model helps a business and where it will cost more than it returns, written down and argued rather than presented. Agentic Transformation for Organisations: One process at a time moved to an agent that runs it, measured against the way that process ran before, with anything that did not improve handed back. AI Solutions: One problem taken end to end: the data it needs, the model call it makes, the interface a person uses, and the measurement that says whether it worked. WordPress Development: WordPress sites built or repaired by someone who reads the theme and the database, rather than installing another plugin on top of the problem. Elementor Builds: Pages built in the visual builder a client already uses, kept fast, and kept editable by the person who owns the site after the engagement ends. Kadence Builds: Sites on the Kadence theme and its blocks, set up so the layout stays consistent when someone other than the builder adds the next page. WooCommerce Stores: A store with its products, its tax and shipping rules, and a checkout proven in test mode before a real card is ever presented to it. Shopify Development: Themes and small apps on a hosted commerce platform, where the platform owns payments and the work is everything arranged around them. GoHighLevel Systems: Pipelines, forms and follow up inside the agency platform, wired so a new lead is answered by the system instead of remembered by a person. AI Search Readiness (SEO / AEO / GEO): Pages made citable by an answer engine as well as findable by a search engine: entity markup, answer shaped copy, and a record of which prompts return the page.

Receipt: src/content/data/services.ts · /services

What does this cost?

The hire form asks for a budget band so the first reply is a real number rather than a guess: Under $1,000, $1,000 to $3,000, $3,000 to $5,000, $5,000 to $10,000, $10,000 and up, Not sure yet. These are the bands on the actual form, not a rate card, and picking the "not sure yet" band is fine — the reply still comes back with a number once the scope is clear.

Receipt: HIRE_BUDGET_BANDS in src/lib/console/registry.ts, the same constant the live form renders · /hire

What timezone does he work in, and how fast does he reply?

Manila, Philippines, GMT+8. Within 24 hours on any inquiry, and available for new projects. The current role already runs across timezones: Remote from Manila, company in Australia.

Receipt: profile in src/content/data/index.ts · /hire

What happens after I submit the form?

1. Discovery — We agree what the project has to achieve, what it must not break, and how we will both know it worked, before any code is written. 2. Build — The work is built with an AI agent as the working partner and a human reviewing every change before it lands. You get commits you can read rather than a status update. 3. Review — You review running software at each milestone, not a screenshot of it, and the next milestone absorbs what you send back. 4. Launch — We deploy to production with checks in the pipeline and alerting that reaches a human, and you hold the repository and the infrastructure accounts.

Receipt: src/content/data/service-pages.ts · /hire

What is a forward deployed engineer?

An engineer who embeds with the client's team rather than working at a remove from a backlog: same tools, same channels, shipping into their stack. James works this way now as AI Automation Developer at Lift Legal Marketing, remote from manila, company in australia.

Receipt: src/content/data/story.ts, chapter lift · /hire

Can an AI assistant read this site directly instead of scraping it?

Yes. The site is a remote MCP server over Streamable HTTP at /api/mcp: no authentication, read only, and every tool result carries the canonical URL it came from so an answer can cite the page rather than paraphrase the site. There is also /llms.txt, and /llms-full.txt for the whole record in a single fetch.

Receipt: src/lib/mcp/server.ts, src/app/llms.txt/route.ts, src/app/llms-full.txt/route.ts · /mcp