Introduction: Production AI – A Real Challenge
Artificial intelligence promises rapid solutions, but when moving from demo to production, AI agents often hit roadblocks. Incomplete search data, repeated failed actions, and exceeding time or cost limits are major obstacles.
1. TinyFish: The Web Infrastructure Backbone for AI Agents
TinyFish has designed four essential primitives that form the foundation of its autonomous agents: TinySearch, TinyFetch, TinyBrowser, and TinyAgent. Each plays a precise role, from gathering information to executing tasks.
TinyFish Web Primitives
- TinySearch: a search engine specialized for AI queries.
- TinyFetch: reliable retrieval of documents and metadata.
- TinyBrowser: automated web navigation.
- TinyAgent: orchestrator of actions based on model logic.
2. Agentic Search Architecture: The Seven‑Phase Loop
The architecture is built around a control loop that guides the agent through the following steps:
- Search planning
- Query execution
- Result collection
- Evidence evaluation
- Action decision
- Execution and monitoring
- Model feedback
Each phase is designed to minimize errors and maximize relevance.
3. Failure Management: From Retry to Continuous Learning
TinyFish incorporates robust mechanisms to handle failures:
- Intelligent retry: limits attempts and adjusts strategy.
- Evidence evaluation: filters unreliable data before action.
- Time/cost limits: stops processes that exceed defined thresholds.
“The key is to turn every failure into useful data for the model.” – TinyFish team
4. Results on OpenBenchmarks: 79% Completion Rate
On the OpenBenchmarks platform, TinyFish achieved a 79 % completion rate for coding tasks, far surpassing industry averages. This performance is the result of thoughtful architecture and continuous learning.
5. Lessons Learned from Building a Deep Search System
The experience shows that:
- A clear separation between reasoning logic and deterministic execution is crucial.
- Pre‑evaluation of evidence reduces production errors.
- A rapid feedback loop improves model quality over time.
Conclusion: Adopt an Agentic Search Architecture for Your AI
To get your AI agents from demo to smooth production, you need a solid architecture like TinyFish’s. Implement these principles today and transform your approach to artificial intelligence.
