Augment Code and Opencode are now available in Zed. 🎉
Both agents run natively through ACP. Install them in seconds from the extensions store and use them alongside Claude Code, Gemini CLI, or Codex.
Today we announced an upcoming change to how Augment Code is priced.
Starting October 20, 2025, plans will move from user messages per month → to a pool of credits that can be spent across activities.
📖 Read more on our blog → www.augmentcode.com/blog/augment...
Our early take on Sonnet 4.5 as compared to Sonnet 4?
✅ 34% fewer tool calls on average
✅ ~26% faster overall task completion time
The result: the same accuracy, delivered with more speed and flow.
Claude Sonnet 4.5 from Anthropic is now the default model for Augment Code.
We’re rolling it out to all customers over the next 24 hours, where it will be available alongside Sonnet 4 (for a limited time) and GPT-5 in the model picker.
Tomorrow, Friday, August 29.
10am PT.
AMA on r/webdev
RSVP and leave your questions:
reddit.com/r/webdev/com...
you like to be close to the metal, we get it.
youtu.be/6wK5q5mYNzQ?...
The Auggie CLI is now available for everyone.
Auggie brings Augment’s industry-leading context engine to every part of your stack—terminal, CI, and beyond.
Getting started is simple:
npm install -g @augmentcode/auggie
www.augmentcode.com/product/CLI
Our industry has moved from ‘still defining an agent’ at the start of 2025 to ‘building things that can actually build things’ by mid-year.
Here are some of the agentic demos that impressed me over the year, including @augmentcode.com @kiro.dev and @systeminit.com
redmonk.com/rstephens/20...
The top 3 requests?
🧠 "error" (35%)
✅ "test" (21%)
✨ "improve" (18%)
AI isn’t starting from a blank file.
It’s jumping into messy code and making sense of it.
The real value? Debugging, refining, and unblocking.
Most people think devs use AI to write code from scratch.
But we analyzed 81 million developer chats — and that’s not what’s happening.
Here's what we found 👇
Agent prompting = engineering communication.
Don’t think “prompt engineering.” Think “design doc + task breakdown + pair programming.”
Good prompts are good collaboration.
Ask for a plan before action.
“I need to expose time zone settings. First, suggest a plan—don’t write code yet.”
This gives you control. And gives the Agent a checkpoint to align.
Don’t cram it all in at once.
❌ “Read ticket, build UI, write tests, update docs”
✅ Break into steps:
- Read ticket
- Build UI
- Write tests
- Update docs
Let the Agent finish before moving on.
Point the Agent to the right files.
❌ “Add JSON parser to chat backend”
✅ “Add JSON parser in LLMOutputParsing (services/ folder). It’ll be used to extract structured output from chat completions.”
Precision = performance.
Give references to code, tests, or docs.
❌ “Write tests for ImageProcessor”
✅ “Write tests for ImageProcessor.Follow structure in test_text_processor.py”
The Agent learns better by example.
Include why, not just what.
❌ “Use events instead of direct method calls”
✅ “Reviewers flagged tight coupling in SettingsWebviewPanel.statusUpdate(). Let’s refactor to events to improve modularity.”
Reasoning aligns the Agent with your intent.
❌ “Fix bug in login handler”
✅ “Login fails with 500 on incorrect passwords. Repro: call /api/auth with wrong creds. Check auth_service.py. Add test if possible.”
Agents need context like humans do.
Most Agent failures aren’t about bad models.
They’re about bad prompts.
Here’s how to write prompts that actually work—based on thousands of real dev-Agent interactions 👇🧵
Thanks for the feedback, Michael - agree we were overzealous here. We'll go ahead and delete all your info so you don't hear from us again.
Ready to make your agent work the way you do? Create a .augment/rules/ folder in your repository and start customizing.
🔗 www.augmentcode.com/changelog/in...
Already using .augment-guidelines.md?
No changes required—your setup remains supported.
But Augment Rules offers even greater flexibility and control.
Three flexible ways to use Rules:
1️⃣ Always: Attach rules to every query automatically
2️⃣ Manual: Select rules per query as needed
3️⃣ Auto: Describe your task—the agent intelligently selects the most relevant rules
Get started in seconds:
🧠 Smart Rule Selection: Agent Requested mode finds what’s relevant for each task
🚀 Seamless Migration: Import rules from other tools, or use your existing Augment guidelines
🧩 Flexible Organization: Use any file name or structure to match your workflow
Every project, team, and workflow is unique.
Augment Rules empower you to specify exactly how your agent should behave. Simply add instruction files to .augment/rules/ and your agent will adapt.
With Augment Rules, your software agent can build just like your team does.
Stay in-session. Build context.
Correct it like you would a teammate:
“This is close—just fix the null case.”
“Leave the rest as-is.”
You’ll be surprised how far a few nudges go.
Failure is feedback.
It tells you:
– What the Agent misunderstood
– What you didn’t explain
– What to clarify next
Don’t bail—refine.
Let it write and run tests.
Then iterate:
“Tests failed—what went wrong?”
“Fix the off-by-one error in test 3.”
“Rerun and confirm.”
Quick cycles beat careful guesses every time.
