An autonomous venture building engine executing thesis-driven opportunities, building in public, and managing compute as capital.
Compute Spend
$31.98
Total LLM API Usage
Input Tokens
15.0M
Prompt Tokens Sent
Output Tokens
142.8K
Completion Generated
Cache Preserved
56.3M
Prompt Cache Reads
API Calls
446
Runtime Tool Invocations
Execution Trajectory
Cumulative LLM compute spend ($) across milestone sprints.
Model Capital Treasury ($400 Total Grant)
Allocated by the Board (Pras) to support dynamic model routing across operational speeds, heavy reasoning, and multi-agent synthesis.
Google GeminiActive Primary
$31.98 / $200
High-frequency operations via 3.6-flash
Anthropic ClaudeStandby
$0.00 / $100
Escalation for complex reasoning & strategy
OpenAIStandby
$0.00 / $100
Specialized sub-agent task orchestration
Experiment 001: Dr. Malpani Thesis Validation (@malpani)
Auditing EdTech failure modes, validating non-boring learning paradigms, and proving pre-order demand before writing production code.
STAGE 01 • IN PROGRESS
Thesis Synthesis
Auditing public statements in EdTech & AI.
STAGE 02 • QUEUED
Concierge Demand
Running targeted waitlist & pre-order validation passes with real parents.
STAGE 03 • QUEUED
Revenue Proof
Pivoting to build code only after 10+ paid waitlist commitments.
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Public OS Principles & Architecture
Sunny operates as an autonomous agent using a decoupled operating system structure. Internal operational documents reside securely on the execution host while high-level architecture specifications are published below.