Background
Know yourself and your opponent to better develop private AI Agents
1. Innate Capabilities of ChatGPT (LLM Native Abilities)
| 1 Language Understanding & Generation | 2 Knowledge Reasoning | 3 Programming Skills | 4 Information Structuring | 5 Multimodal Understanding |
|---|---|---|---|---|
| Q&A | Logical Reasoning | Writing Code | Extracting from Text | Image Understanding |
| Summarization | Common-sense Reasoning | Debugging | OCR | |
| Translation | Solution Design | Code Explanation | Chart Interpretation | |
| Paraphrasing | Architecture Design | API Design | ||
| Information Extraction | Programming Issues | Architecture Design | ||
| Text Classification | ||||
| Dialogue |
2. Limitations of ChatGPT by Design
| 1 No Access to Private Data | 2 Cannot Operate Real-World Systems | 3 No Long-Term Memory | 4 Cannot Handle Complex Multi-Step Planning | 5 Cannot Guarantee 100% Accuracy | 6 Context Window Limitations | 7 Poor Stability for Long Tasks |
|---|---|---|---|---|---|---|
| Examples: Company internal knowledge bases, emails, contracts, user data, CRM | Examples: Sending emails, creating calendar events, creating Jira tickets, querying databases, payments, code deployment | ChatGPT is stateless by default. It doesn’t remember: who the user is, past behavior, preferences, long-term goals | Although LLMs can reason, they are unstable, prone to skipping steps, and don’t self-correct | LLMs suffer from hallucinations | Example: 1000k tokens limit; excess data is lost | Example: 100-step tasks tend to forget steps and deviate from goals |
| Solution: RAG systems | Solution: Function Tools | Solution: Memory systems | Solution: Agent systems | Solution: Tool verification, retrieval grounding, rule engines | Solution: Chunking, retrieval | Solution: Agent loops |
3. Tasks Unsuitable for ChatGPT
| 1 Precise Calculations | 2 Database Queries | 3 Large-Scale Data Processing |
|---|---|---|
| Examples: Financial calculations, statistics, scientific computing | Examples: LLM-generated SQL, database execution | Examples: Processing millions of records |
关于作者
我是Louis,一名长期从事iOS与AI相关工程实践的工程师,也是一个正在探索产品与商业可能性的准创始人.
这里的文章,更多是我在项目中用过,踩过坑,反复验证过的东西,而不是为了流量而写的“快内容”.
☕ 打赏
如果这篇文章对你有帮助,欢迎请我喝一杯咖啡☕️
GitHub Sponsors（推荐）
PayPay
You can support my work via PayPay by searching my PayPay ID:
PayPay ID: luochuan
微信支付
支付宝
你的支持会让我有更多时间,把真实项目中的经验持续整理和分享出来.
不打赏也完全没关系,感谢你读到这里.
联系与合作
如果你:
· 正在做iOS App / AI / 自动化相关的项目
· 对技术选型、架构设计、产品落地有困惑
· 或希望进行技术交流、合作探讨
欢迎通过以下邮箱联系我:
luochuanad@gmail.com
