Tool Recommendations (January 2026)
What AI tools should I use?
All of them. Also none of them. It depends.
Table of Contents
- Code Assistants (IDE Integration)
- Chat Interfaces
- API Providers
- Local Models
- Vector Databases
- Frameworks & Libraries
- What to Avoid
- The Minimal Stack
- How This Will Age
The AI tool landscape changes fast. This appendix captures what’s worth your time and money as of January 2026. It will age. Check the date.
Last updated: January 2026
Code Assistants (IDE Integration)
These tools live in your editor and help you write code.
GitHub Copilot
Price: $10-19/month individual, $39/user/month business
What it’s good for:
- Inline code completion (best-in-class)
- Boilerplate generation
- Test writing
- Tab-completing obvious code
What it’s not good for:
- Complex architectural decisions
- Code that requires deep context understanding
- Anything security-sensitive (review carefully)
Verdict: ✅ Worth paying for if you code daily. The time savings justify the cost.
Cursor
Price: $20/month Pro, $40/month Business
What it’s good for:
- Codebase-aware assistance (better context than Copilot)
- Multi-file edits
- Chat with your codebase
- Agent-style longer tasks
What it’s not good for:
- If you’re deeply invested in VS Code extensions ecosystem
- Very large codebases (context limits)
Verdict: ✅ Worth trying. Better context handling than Copilot, but more expensive. Good for those who want more than autocomplete.
Claude Code
Price: Usage-based through Claude API
What it’s good for:
- Terminal-based AI assistance
- Deep codebase understanding
- Long-running agentic tasks
- Multi-file refactoring
What it’s not good for:
- Quick one-liners (overhead of setup)
- If you want GUI-based experience
Verdict: ✅ Worth using for complex tasks. Best context handling currently available.
Amazon CodeWhisperer
Price: Free tier available, $19/user/month professional
What it’s good for:
- AWS-specific code
- Free tier for individual use
- Security scanning included
What it’s not good for:
- General coding (Copilot is better)
- Non-AWS contexts
Verdict: ⚠️ Situational. Good if you’re AWS-heavy and want free. Otherwise, Copilot is better.
Codeium
Price: Free for individuals
What it’s good for:
- Free alternative to Copilot
- Most languages supported
- Privacy (doesn’t train on your code)
What it’s not good for:
- Quality slightly below Copilot
- Fewer features
Verdict: ✅ Good free option. If you can’t or won’t pay for Copilot, this is solid.
Chat Interfaces
For when you need to have a conversation, not just get completions.
Claude.ai
Price: Free tier, $20/month Pro
What it’s good for:
- Long context (200K tokens)
- Nuanced conversation
- Code explanation and review
- Document analysis
- Artifacts (runnable code, diagrams)
What it’s not good for:
- Real-time information (training cutoff)
- Some creative writing tasks
Verdict: ✅ Recommended. Best for technical work and long documents.
ChatGPT (Plus/Pro)
Price: Free tier, $20/month Plus, $200/month Pro
What it’s good for:
- General conversation
- Image generation (DALL-E)
- Plugins/GPTs ecosystem
- Web browsing
What it’s not good for:
- Very long documents (shorter context than Claude)
- Consistent code style
Verdict: ✅ Good general-purpose. The ecosystem is broader, but Claude is better for pure coding.
Google Gemini
Price: Free tier, $20/month Advanced
What it’s good for:
- Google Workspace integration
- Long context (1M tokens on some tiers)
- Multimodal (images, video)
What it’s not good for:
- Code quality (not as good as Claude/GPT for code)
- Consistency
Verdict: ⚠️ Situational. Good if you’re Google-ecosystem heavy. Otherwise, Claude or ChatGPT.
Perplexity
Price: Free tier, $20/month Pro
What it’s good for:
- Research with citations
- Current information (searches web)
- Quick factual questions
What it’s not good for:
- Coding tasks
- Long conversations
Verdict: ✅ Good for research. Use alongside Claude/ChatGPT, not instead of.
API Providers
For building AI features into your applications.
Anthropic (Claude API)
Price: Pay per token (varies by model)
Models to know:
- Claude Opus 4: Most capable, expensive
- Claude Sonnet 4: Best balance for most uses
- Claude Haiku 3.5: Fast and cheap
What it’s good for:
- Complex reasoning
- Long context
- Code generation
- Tool use/agents
Verdict: ✅ Recommended for production. Most reliable for coding tasks.
OpenAI
Price: Pay per token (varies by model)
Models to know:
- GPT-4o: Multimodal, good all-around
- GPT-4-turbo: Older but cheaper
- GPT-3.5-turbo: Cheap, fast, less capable
What it’s good for:
- Broad capability
- Image understanding
- Largest ecosystem
Verdict: ✅ Solid choice. More options, slightly less reliable for code than Claude.
Google (Gemini API)
Price: Pay per token
What it’s good for:
- Multimodal (best video understanding)
- Very long context
- Google Cloud integration
What it’s not good for:
- Consistency
- Code quality
Verdict: ⚠️ Situational. Consider for multimodal or Google Cloud projects.
Mistral
Price: Pay per token
What it’s good for:
- European hosting (GDPR)
- Good price/performance
- Open weights models available
What it’s not good for:
- Cutting-edge capability
- Ecosystem (smaller than OpenAI/Anthropic)
Verdict: ⚠️ Niche choice. Good for EU compliance requirements.
Local Models
For running AI on your own hardware.
Ollama
Price: Free (open source)
What it’s good for:
- Running local models easily
- Mac M-series optimization
- Simple API
- Privacy (data never leaves your machine)
Verdict: ✅ Essential if you want to run local models. Best UX for local deployment.
Recommended Local Models (via Ollama)
| Model | Parameters | Good For | Min RAM |
|---|---|---|---|
| Llama 3.2 | 3B | Quick tasks, constrained hardware | 8GB |
| Llama 3.1 | 8B | General coding, good quality | 16GB |
| Llama 3.1 | 70B | Best local quality | 48GB+ |
| CodeLlama | 7B-34B | Code-specific tasks | 16GB+ |
| Mistral | 7B | Good balance | 16GB |
| DeepSeek Coder | 6.7B-33B | Code generation | 16GB+ |
| Qwen 2.5 Coder | 7B-32B | Code generation, instruction following | 16GB+ |
Reality check: Local models are worse than cloud APIs. Use them for privacy, cost, or offline work—not for better quality.
LM Studio
Price: Free
What it’s good for:
- GUI for local models
- Model discovery and download
- Chat interface for local models
Verdict: ✅ Good companion to Ollama. Better UI, similar functionality.
Vector Databases
For building RAG systems and semantic search.
Pinecone
Price: Free tier, then ~$70/month+
What it’s good for:
- Managed service (no ops)
- Fast and reliable
- Good documentation
What it’s not good for:
- Cost at scale
- Self-hosting requirements
Verdict: ✅ Best managed option. Start here unless you have specific requirements.
Qdrant
Price: Free (open source), cloud pricing available
What it’s good for:
- Self-hosting option
- Good performance
- Rich filtering
Verdict: ✅ Best self-hosted option. Good balance of features and ease of use.
Chroma
Price: Free (open source)
What it’s good for:
- Simple setup
- Good for prototypes
- Embedded (in-process) option
What it’s not good for:
- Production scale
- Advanced features
Verdict: ✅ Great for learning/prototypes. Graduate to Pinecone or Qdrant for production.
pgvector
Price: Free (PostgreSQL extension)
What it’s good for:
- Already using PostgreSQL
- Simple requirements
- No new infrastructure
What it’s not good for:
- Very large scale
- Advanced vector search features
Verdict: ✅ Good pragmatic choice. If you have Postgres, start here before adding another database.
Frameworks & Libraries
LangChain
Price: Free (open source)
What it’s good for:
- Quick prototypes
- Lots of integrations
- Learning concepts
What it’s not good for:
- Production reliability
- Debugging (abstraction overhead)
- Performance
Verdict: ⚠️ Controversial. Good for learning, often removed for production. Consider raw API calls instead.
LlamaIndex
Price: Free (open source)
What it’s good for:
- RAG-specific workflows
- Document processing
- Index management
What it’s not good for:
- Simple use cases (overkill)
- Non-RAG applications
Verdict: ⚠️ Situational. Use if you’re building complex RAG, skip for simple retrieval.
Vercel AI SDK
Price: Free (open source)
What it’s good for:
- Streaming UI
- Multiple provider support
- Next.js integration
Verdict: ✅ Recommended for web apps. Clean abstractions, good DX.
What to Avoid
❌ Any tool that promises “no hallucinations”
It’s lying. Move on.
❌ Enterprise platforms that won’t show pricing
If they hide the price, you can’t afford it.
❌ AI wrappers with no clear value-add
If it’s just a UI over ChatGPT, use ChatGPT.
❌ “AI agents” that require giving them your credentials
Security nightmare. Don’t.
❌ Tools requiring you to “train on your codebase” before basic use
Often unnecessary complexity. Try simpler tools first.
The Minimal Stack
If you’re just getting started, here’s the minimum:
For individual development:
- GitHub Copilot ($10-19/month)
- Claude.ai Pro ($20/month)
- Ollama (free) for offline/privacy
For building AI features:
- Anthropic Claude API
- Chroma or pgvector (free)
- Raw API calls (skip LangChain initially)
Total cost: ~$30-40/month + API usage
How This Will Age
This guide will be partially obsolete within 6 months. Things that will probably change:
- New models will be released (check benchmarks, ignore marketing)
- Prices will shift (generally downward)
- New tools will emerge (wait for maturity before adopting)
- Some listed tools will fade (watch GitHub activity)
When evaluating new tools, ask:
- What problem does this solve that existing tools don’t?
- Who’s using it in production?
- What’s the bus factor? (Is it one person’s side project?)
- What happens if they shut down?
Last updated: January 2026. Don’t use this guide in January 2027.