Property of T. Damiba · Do Not Remove

Building infrastructure
for delegated thought.

I’m Thierry Damiba, Developer Evangelist at Arcade and founder of Scale Intelligence. I write field notes on secure agent tool use, retrieval, benchmarks, and the infrastructure required to move AI workflows from demos into measurable revenue systems.

※ Featured Card · Cover

Cat. № TD-026.001
★ Essay · Cover · May 2026Class. 006.3 / DAM
by T. Damiba — 12 min read
Why production agents need authorization, governance, and tool execution, not just better prompts. A working theory of the agent runtime.

※ Catalog · Recent Entries

05 cards
Field Note006.3 / DAM-002
by T. Damiba — 4 min read
Protocols matter, but runtimes decide whether agents can safely ship inside real companies.
Technical006.3 / DAM-003
by T. Damiba — 6 min read
The enterprise agent stack is less about remembering everything and more about accessing the right thing safely.
Essay006.3 / DAM-004
by T. Damiba — 8 min read
How brands get cited by ChatGPT, Claude, Perplexity, and Google AI.
Project006.3 / DAM-005
by T. Damiba — 7 min read
70 tasks across 7 categories, deterministic graders, head-to-head matches for agentic GTM workflows.
Essay006.3 / DAM-006
by T. Damiba — 12 min read
NBA stats, Balatro, and the cost of curiosity. Notes on building RL environments with Prime Intellect.

※ Reading-Room Bulletin

Receive new entries by post when they are filed. No advertising; ten emails per year, perhaps fewer.

※ Operating Record · Index Drawer

5 affiliations
A
ArcadeDeveloper Evangelist
2025 — Present
Building developer education, demos, and field notes around secure agent tool use: MCP, OAuth, authorization, and production agent infrastructure.
S 2024 — Present
Forward-deployed AI lab building agentic go-to-market systems for traffic, pipeline, and AI search visibility.
G 2024 — Present
Community and event series for people building programmable go-to-market systems.
Q
QdrantDeveloper Advocate
2023 — 2025
Developer education, demos, docs, and applied retrieval systems for vector search and agents.
SAICML Engineer
2021 — 2023
Machine learning and applied data systems for enterprise and government environments.