Chatbots Talk. Agents Execute.
OpenAI defines an agent as a system where an LLM dynamically directs workflow execution using three core pillars: Model (reasoning engine), Tools (external capabilities), and Instructions (operational guardrails).
A comprehensive visual guide distilling OpenAI's "A Practical Guide to Building AI Agents" and Slite's "Company Brain" research into 12 square illustrated collector postcards. Built for teams of all technical levels.
OpenAI defines an agent as a system where an LLM dynamically directs workflow execution using three core pillars: Model (reasoning engine), Tools (external capabilities), and Instructions (operational guardrails).
OpenAI's central execution engine is the Run Loop. The agent runs iteratively: inspecting context, planning tools, executing calls, and evaluating results until reaching a verified exit condition or safe human escalation.
OpenAI emphasizes three architectural topologies: start with a focused Single Specialist; use a Router Agent when handling multi-intent triage; and use Manager-Worker Swarms for complex parallel synthesis.
LLMs are word predictors unsuited for raw accounting. OpenAI's guide mandates calling deterministic tools with strict JSON schemas, delegating mathematics and database mutations to verified code.
OpenAI mandates strict guardrails: input validation, circuit breakers, and Human-in-the-Loop (HITL) approval gates. Low-risk queries execute autonomously; high-risk actions pause for 1-tap human signoff.
Production agents require continuous evaluation against trajectory benchmarks. Once accuracy targets are met, optimize cost and latency by routing simpler tasks to smaller, ultra-fast specialist models.
Slite's research across 150+ organizations reveals that over 55% of company wikis are abandoned within months. When operational facts stay trapped in private chats and memory, both staff and AI bots are forced to guess.
A Company Brain is not a binder of static pages. It is an active memory layer that captures operational facts as work happens, turning everyday notes into atomic records queryable by humans and AI.
Three foundational pillars maintain organizational memory: 1. Capture naturally from audio and receipts; 2. Atomize into discrete self-contained cards; 3. Ground every reply with exact citations.
The primary blocker in enterprise AI is fear of inaccurate answers. A Company Brain eliminates hallucinations by forcing the model to cite the exact verified card ID, author, and timestamp.
New hires and AI bots should never require weeks of manual onboarding. Because both read from the exact same living SQLite memory, answers remain identical across counters, phones, and chats.
Build an active organization memory in one afternoon: 1. Audit top 10 repeated rules; 2. Store as local atomic cards; 3. Connect customer channels; 4. Enable 30-day auto-verification reminders.
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