Why We Built AI Agents, Not Another Copilot

When we started Synlets, copilot tools were everywhere. GitHub Copilot, Cursor, Cody — great tools for autocomplete and suggestions. But we saw a different opportunity.

The Copilot Ceiling

Copilots are fundamentally reactive. They wait for you to type, then suggest completions. They're spell-checkers for code — useful, but limited.

The problem? They still require your attention. Every suggestion needs review. Every completion needs context switching. You're still the bottleneck.

A copilot can't:

• Pick up a Jira ticket and implement it while you sleep
• Review a teammate's PR against your coding standards
• Clear 20 backlog items over the weekend

A copilot helps you code faster. It doesn't give you more hours in the day.

The Key Difference: Autonomy

Aspect	Copilot	Autonomous Agent
Trigger	You type, it suggests	You assign a ticket, it works
Scope	Lines or functions	Complete features and PRs
Attention	Requires your focus	Works in background
Output	Code suggestions	Merged pull requests
Workflow	Inside your IDE	Integrated with GitHub, GitLab, Jira, Asana, Linear

Copilots are reactive — they respond to what you're typing.

Agents are proactive — they pick up work and deliver results.

The Autonomy Spectrum

Not all AI coding tools are equally autonomous:

LOW AUTONOMY                                              HIGH AUTONOMY
     |                                                           |
     v                                                           v

Autocomplete → Chat Assistant → Code Generator → Autonomous Agent
  (Copilot)      (ChatGPT)       (Cursor)         (Synlets)

 "Complete      "Answer my       "Write this      "Pick up this
  this line"    question"        function"        ticket and
                                                  deliver a PR"

The further right you go, the less human attention required per task.

When to Use What

Copilots are great for:

• Writing code you're actively thinking about
• Quick completions during flow state
• Learning new APIs or patterns
• Exploring solutions interactively

Agents are great for:

• Routine tasks you'd otherwise deprioritize
• Work that doesn't need your unique insight
• Scaling your team's capacity without hiring
• Getting work done while you're offline

They Solve Different Problems

Copilots solve: "I wish I could type faster."

Agents solve: "I wish I had more engineers."

If your challenge is that coding feels slow, use a copilot. If your challenge is that you have more work than people, use agents.

The Future is Both

We're not replacing copilots. We're adding a new category: autonomous teammates.

The best teams will use both:

• Copilot when you're in the editor, building something complex
• Agents when you need capacity — background work, overnight tickets, weekend PRs

Think of it like this: your copilot is your pair programmer. Your agent is a teammate who handles the tickets you don't have time for.

One helps you build faster. The other helps your team ship more.

---

Keep reading:

• Beyond Vibe Coding: When AI Should Work Without You — The evolution from vibe coding to agentic coding
• Synlets vs Cursor — Detailed comparison of agents vs AI editors
• What is an Autonomous AI Developer? — Definition and use cases