2 sources filed · EN 1 · RU 1
Step 1: existing code search across about 1,000 repos wrapped as an MCP tool, then docs and wiki readers, feature flags, task management and the data platform.
30exposed tools beyond which agents slow down and degrade, per the speaker
Result: an API with database, alerts and monitoring in production, after several weeks and about USD 2,000, with roughly ten tickets to internal infrastructure teams.
~USD 2,000cost of taking one internal microservice to production through prompts only
2 sources filed · EN 1 · RU 1
SaaS that survives is tied to regulation, payments, deep integrations, contracts or risk; single-user tools lose.
300 to 30-40candidates in the hiring funnel screened to a shortlist in one day through an agent, without opening the HRM
12 models, 180 attack instances each, built from 15 APEX-Agents tasks in investment banking, law and management consulting.
8% and 20%overall attack success rates for Opus 5 and Sonnet 5, the lowest of the 12 models
2 sources filed · RU 2
Architecture: tools are thin adapters; a shared core handles one HTTP pool per process, API key injection, logging, tracing and error mapping.
5 of 44coffee shops returned for 'nearest coffee shop' with no point given, all in Vorkuta (latitude about 67.5)
Interface: start "task name" opens a session and returns the current SDK description; run "Python script" executes code on the server in a sandbox with the user's permissions.
2commands in the whole agent interface: start a session, run a Python script