Saya mengubah model menjadi sistem siap pakai.
CTO di Of Them All dan pendiri Illuma. Saya membangun alur kerja AI, model niche, dan infrastruktur platform untuk domain yang mengutamakan penilaian, latensi, dan kepercayaan.
tahun mengubah ambiguitas menjadi sistem produksi
pasar di Asia dan Eropa dengan batasan operasional yang berbeda
insinyur yang direkrut, dilatih, atau dibimbing di seluruh tim terdistribusi
alur kerja mix audio berbantuan AI, turun dari 15 menit manual
AI yang bermanfaat bukanlah fitur. Ini adalah sistem produksi yang dilengkapi bukti, alur kerja, dan akuntabilitas.
Saya membangun infrastruktur pembayaran dan marketplace ketika uptime, penipuan, kepatuhan, dan jutaan transaksi harian adalah produknya. Kemampuan operasional tersebut kini membentuk cara saya membangun sistem AI.
Polanya konsisten: temukan bottleneck ahli, modelkan jalur keputusan, sambungkan lapisan data, lalu perkuat alur kerja hingga tim dapat mempercayainya dalam produksi.
Practical AI, wired into the systems that make it useful.
The work is not just prompting a model. It is designing the data path, product loop, delivery system, and operating cadence around it.
Agentic workflow design
I turn repetitive expert work into supervised AI workflows: tool calling, review gates, retrieval, and measurable human-in-the-loop throughput.
RAG and model adaptation
Domain corpora, embeddings, retrieval strategy, prompt contracts, evaluation loops, and targeted fine-tuning when the base model is not enough.
Platform architecture
Architecture for systems that must keep moving: payments, marketplaces, automation backplanes, queues, observability, and deployment paths.
Engineering operating system
Hiring, coaching, SDLC, delivery cadence, incident habits, and the technical narrative needed when teams and products need to mature fast.
Dari kemungkinan model menjadi kebiasaan operasional.
Saya lebih menyukai loop pendek, risiko yang terlihat, dan sistem yang berfungsi dibandingkan roadmap spekulatif yang panjang.
Petakan bottleneck
Identifikasi di mana penilaian ahli, latensi, atau keputusan berulang membatasi pertumbuhan.
Prototipe loop
Bangun jalur model + data + antarmuka terkecil yang dapat membuktikan pekerjaan bermanfaat.
Perkuat sistem
Tambahkan retrieval, evaluasi, izin, observabilitas, dan tinjauan manusia di mana risiko menuntutnya.
Terapkan kebiasaan
Ubah alur kerja menjadi perilaku tim dengan metrik, kepemilikan, dan irama iterasi.
Usaha sebagai laboratorium hidup, bukan hiasan portofolio.
Setiap produk adalah tempat untuk menguji tesis yang sama: AI khusus hanya relevan ketika tertanam dalam alur kerja dan bertanggung jawab terhadap hasil.
Illuma
Legal AI · illuma.law
A legal AI platform for evidence management, precision case analysis, and specialized workflows that need traceability instead of generic chatbot behavior.
Luminous Giant
AI systems consultancy · luminous-giant.com
A build practice for founders and operators who need AI workflows, platform architecture, and engineering execution in the same room.
AI systems are layered products.
The useful work happens where models, data, product logic, and operational discipline meet.
Model layer
LLMs, Gemini, prompt contracts, evaluation sets, fine-tuning, agent behavior, and task decomposition.
- LLMs
- Agent workflows
- Fine-tuning
- Prompt engineering
- Model evaluation
Knowledge layer
The retrieval and memory plane that keeps AI grounded in product, legal, media, or operational context.
- RAG pipelines
- Embeddings
- Vector search
- PostgreSQL
- Meilisearch
Application layer
The product systems where AI meets users, permissions, payments, workflows, and business-critical state.
- Laravel
- TypeScript
- Cloudflare Workers
- Microservices
- Payment systems
Operations layer
The delivery environment: CI/CD, containers, observability, incident loops, and teams that own production.
- Docker
- Kubernetes
- AWS
- Linux
- GitHub Actions
Bukti karir di marketplace, pembayaran, platform ML, dan tim.
Perluas setiap baris untuk bukti, sorotan, dan teknologi dari peran tersebut.
Orang-orang yang telah melihat sistem operasional dari dekat.
“Having worked 10 years ago and again hiring Miguel to work closely with me for the past 4 years tells a lot about how much trust and respect I have for him. Miguel Enes has a very entrepreneurial mindset that always sets him to find solutions and to move organisations forward. He does that relying on his profound and complete tech knowledge and on-hands experience, leading by example/execution and supporting his team along the way. I highly recommend him as an autonomous, energiser, tech-savvy and delivery oriented Engineering Manager.”
Tulisan terbaru dari lantai pembangunan.
What I'm Building in 2026
I am building new ventures in Portugal.
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Libatkan saya ketika prototipe perlu menjadi sebuah sistem.
Diskusi yang bermanfaat: pembangunan alur kerja AI, sistem teknologi hukum, arsitektur marketplace/platform, kepemimpinan rekayasa, dan strategi teknis untuk tim ventura.