Optimizing AI Workflows: Key AI Working Procedures
To effectively harness artificial intelligence, understanding different AI working procedures is crucial. These models define how humans and AI collaborate for optimal productivity:
- Human First, AI Assist: human is focusing on the high-level tasks and design to instruct AI for high-level decision making or cross-multiple domain tasks.
- AI First, Human Assist in Sync: human design the task and instruct AI to do the task in a synchronous way, and human is focusing on revise and review the AI's work till the task is done.
- AI First, Human Assist in Async: human design the task and instruct AI to do the task in an asynchronous way, AI using
Agentic
approach to do the task, and human is focusing on later review and revise the AI's work till the task is done. These tasks are usually self-contained and not coupled with other domains, so AI can work independently.
Let's take software development as an example:
Human First, AI Assist
- App production, tech-architecture, and market high-level design within the artificial intelligence landscape.
- Core modules, core features, and core functions design.
- Key-decision making about the technology stack, architecture, and modules features, a vital part of AI best practices.
- Complex problem solving and reasoning, such as systematic and systemic reasoning.
- ...
In this mode, Arno try to create
Elaboration Studio
e-studio.ai to leverage the power of AI and personal context engineering to do the high-level design and decision making, and then use the AI to assist in the low-level tasks. This approach is central to productivity with AI.
AI First, Human Assist in Sync
- app development, coding, and programming in specific modules
- write PRD, design documents, and technical documents
- code review, PR review, and design review
- software development lifecycle, such as devops, CI/CD, and testing
- ...
In this mode, dedicated AI tools are used to assist in the coding and programming tasks, such as
Cursor
,Github Copilot
, andV0
. These tools are designed to work in sync with human developers, providing real-time assistance and suggestions.
AI First, Human Assist in Async
- Do market or product research using specialized AI tools.
- Write unit-test and integration-test as part of an AI-driven development cycle.
- Refactor modules, features, and functions, optimizing AI workflows.
- Batch job on data processing or information processing.
- ...
In this mode, AI tools are used to work independently on specific tasks, such as
Google Deep Research
,Manus
andGoogle Jules
which can run in the server-end or background without human intervention. These tools are designed to handle specific tasks and can work asynchronously, allowing for greater efficiency and productivity with AI.
Practical AI Application Scenarios & Tool Recommendations
This section explores various scenarios where AI can be applied, along with recommended AI tools and platforms that fit each AI workflow.
Daily QA
Gemini Pro 2.5 x DeepSeek R1 (with specific domain search data)
General knowledge and information retrieval.
- public domain knowledge
- time sensitive information
- domain specific knowledge
- experience driven query
- personal context required query
dimension:
- open search based
- private search based
- domain specific pre-trained model based
- personal context based
- direct or reasoning based
AI in Coding & Programming: Tools and Techniques
Cursor x GithubCopilot
Programming and coding tasks.
- vibe-coding & code-generation
- code-review
- tabs engineering
- software-development-lifecycle -> devops
AI for Research, Study & Learning: Enhancing Knowledge Discovery
Google Deep Research x Gemini Pro 2.5 x Artifact x DeepSeek R1
- public domain knowledge based
- private domain knowledge based
- professional & profound knowledge based
- short v.s. long form of report (research, study, learning, etc.)
AI-Assisted Article Writing & Content Creation
Cursor x Github x Markdown = YYDS!
- short and middle form
- long form
AI in Media Generation: Images, Video, and Audio
GPT4o x Midjourney x JiMeng
- image generation
- video generation
- audio generation
- 3D generation
AI for Complex Problem Solving & Strategic Reasoning
Gemini Deep Research x Reasoning models x Elaboration Studio
- context engineering: KESW x data x info
- complex reasoning
- systematic and systemic powered
Navigating the AI Landscape: Essential Tools, Platforms & Models
The following legend explains the icons used to categorize these AI technologies:
- π free for now
- π¬ research its features and capabilities
- ππ» recommended, good to have
- β₯οΈ my favorite, must-have
- π valuable but cost
Comparative Guide to AI Tools & LLM Models (2025)
LLM Models Comparison
Model | Speed | Price | Best For | Limitations |
---|---|---|---|---|
Gemini Pro 2.5 | Fast | ππ»β₯οΈ | Research, Knowledge retrieval | Less creative than GPT-4 |
ChatGPT 4.1 | Fast | π | General tasks, Coding | Less capable than 4o |
Claude 4 | Medium | π | General tasks, Coding | Cost, API limits |
DeepSeek R1 | Medium | π | Domain-specific tasks | Limited general knowledge |
ChatGPT 4.5 | Slow | π | Complex reasoning, Image generation | Cost, API limits |
Kimi | Search | Quick information | π | |
Yuanbao | Chinese market research | Local insights | π |
General Intention Tools
Tool | Type | Best For | Integration | Cost |
---|---|---|---|---|
Manus | Research & General Usages | AutoRun tasks | API | ππ¬ |
AI Development Tools for Software Engineering
Tool | Type | Best For | Integration | Cost |
---|---|---|---|---|
Cursor | IDE | Full-stack development | Git, AI models | ππ»β₯οΈ |
Github Copilot | Code Assistant | Real-time coding | IDE plugins | ππ»β₯οΈ |
V0 | Prototyping | Quick app prototypes | Vercel | ππ» |
devv.ai | Developer QA | Code search & solutions | API | π¬ |
DeepWiki | Knowledge Base | AI run under repo and build knowledge | API | π¬ |
Loveable | Full-Stack Site Builder | Code search & solutions | WebSite | ππ¬ |
Augment | IDE Extension | Vibe Coding & Cursor competitor | IDE plugins | π |
Jules | AI Agent | Run in server-end to operate code tasks | WebApp | π¬ |
OpenAI Codex | Remote Container Mode | Run in remote container | WebApp | π¬ |
For local IDE VibeCoding, Arno's recommendation is:
Cursor = Augment > Windsurf = Microsoft Github Copilot
AI Tools for Research & Knowledge Management
Tool | Features | Best For | Cost |
---|---|---|---|
Google Deep Research | Advanced search, Insights | Deep research | ππ»β₯οΈ |
Google Notebook ML | Knowledge organization | Research synthesis | ππ» |
Flowith | AI-powered agentic workflow | Parallel tree like ai-powered workflow | π¬ |
AI Creative & Design Tools
Tool | Type | Best For | Cost |
---|---|---|---|
Midjourney | Image Generation | High-quality art | π |
JiMeng | Image Generation | Chinese style art | π |
Figma Make | AI Design & Impl. | Automated design | π |
AI Deployment & Infrastructure Platforms
Platform | Purpose | Features | Cost |
---|---|---|---|
Vercel | Deployment | Serverless, Edge | ππ» |
OpenRouter | API Gateway | Multiple models | ππ» |
idea that sparks
- dig deeper with deep research: one research -> research conception and topic -> deeper research and build the zoom-in and zoom-out effect
Trace
- 2025-04-20: initial version
- 2025-05-10: upgrade some more details and scenarios for AI to use and mapping to the tools and models
- 2025-05-23: add
AI Working Procedure
for better understanding of the AI working procedure and how to use the tools and models