🗺️ Arno's AI Map: A Guide to AI Tools, Workflows & Best Practices 2025

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 a systemic and systematic approach 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, and V0. 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 and Google 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

Daily general QA task -> Gemini Pro 2.5, deep understanding and reasoning -> Open AI O3Pro

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 (Claude 4 / o3)

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 Google Artifact x Google Notebook ML (Knowledge based QA)

• 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 = Worked perfectly!

• short form (text completion with cursor)
• middle form (text generation / editing with cursor)
• long form (agentic approach with cursor)

AI in Media Generation: Images, Video, and Audio

GPT4o x Midjourney x Google Video Generation

• image generation
• video generation
• audio generation
• 3D generation

AI for Complex Problem Solving & Strategic Reasoning

Gemini Deep Research x Reasoning models x Context Engine (for context engineering)

• context engineering: KESW x data x info
• complex reasoning
• systematic and systemic context powered

Navigating the AI Landscape: Essential Tools, Platforms & Models

The following legend explains the icons used to categorize these AI technologies:

• 🆓 free for now
• 🔬 research its features and capabilities
• 👍🏻 recommended, good to have
• ♥️ my favorite, must-have
• 💎 valuable but cost

Comparative Guide to AI Tools & LLM Models (2025)

LLM Models Comparison

Latest models recommendations till 2025-06-16

AI Development Tools for Software Engineering

For local IDE VibeCoding, Arno's recommendation is:

Cursor ~= Augment > Windsurf = Microsoft Github Copilot

AI Tools for General Purpose

AI Tools for Research & Knowledge Management

AI Creative & Design Tools

AI Deployment & Infrastructure Platforms

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

Context Engineering: The Key to AI Productivity

WIP -> new article to write

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