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    Augment Code Blog

    augmentcode.com · Company blog · on HN since 2024

    Augment Code, an AI coding assistant company, writes about its product, agent workflows, model choices, and funding.

    Visit blogHN submissions
    AI & Machine LearningProgrammingTech Industry
    What HN says

    Commenters who use Augment praise its code context, remote agent, and review quality, and an employee shares testing of Claude 3.7.

    Stats for nerds
    39HN people shared it
    60linked in comments
    365story points
    Mar 2026last shared
    2024people per year2026

    Top posts on HN

    1. 1
      Developers are choosing older AI models
      2 people · 185 points · first shared 2025 · 176 comments on HN
    2. 2
      How We Optimize LLM Inference for AI Coding Assistant
      2 people · 34 points · first shared 2024 · 5 comments on HN
    3. 3
      Augment Code: Developer AI for Teams
      1 person · 29 points · first shared 2024 · 2 comments on HN
    4. 4
      #1 open-source agent on SWE-Bench Verified by combining Claude 3.7 and O1
      2 people · 12 points · first shared 2025 · 3 comments on HN
    5. 5
      Why GPT-5.2 is our model of choice for Augment Code Review
      1 person · 12 points · first shared 2025 · 4 comments on HN
    6. 6
      Augment Raises $227M at $977M Valuation to Empower Software Teams with AI
      3 people · 10 points · first shared 2024 · Discussion on HN
    7. 7
      A good AGENTS.md is a model upgrade. A bad one is worse than no docs at all
      4 people · 8 points · first shared 2026 · 1 comments on HN
    8. 8
      What spec-driven development gets wrong
      2 people · 5 points · first shared 2026 · Discussion on HN
    9. 9
      How I went AI-native in my terminal workflow
      2 people · 4 points · first shared 2026 · Discussion on HN
    10. 10
      Show HN: We got sick of juggling terminals for AI agents so we built a workspace
      1 person · 4 points · first shared 2026 · Discussion on HN

    What HN people wrote when they linked it

    • logicprogNov 2025

      > Nothing on infra costs, hardware throughput + capacity (accounting for hidden tokens) & depreciation

      That's because it's coming at things from the other end: since we can't be sure exactly what companies are doing, we're just going to look at the actual market incentives and pricing available and try to work backwards from there. And to be fair, it also cites, for instance, deepseek's paper where they talk about what their power foot margins are on inference.

      > just a blind faith that pricing by providers "covers all costs and more".

      It's not blind faith. I think they make a really good argument for why the pricing by providers almost certainly does cover all the costs and more. Again, including citing white papers by some of those providers.

      > Naive estimate of 1000 tokens per search using some simplistic queries, exactly the kind of usage you don't need or want an LLM for.

      Those token estimates were for comparing to search pricing to establish whether — relative to other things on the market — LLMs were expensive, so obviously they wanted to choose something where the domain is similar to search. That wasn't for determining whether inference was profitable or not in itself, and has absolutely no bearing on that.

      > Doesn't account at all for chain-of-thought (hidden tokens) that count as output tokens by the providers but are not present in the output (surprise).

      Most open-source providers provide thinking tokens in the output. Just separated by some tokens so…

    • mythzJun 2025

      Nice, only got the pro plan and didn't want to get Nickel and Dimed per usage so ended up ignoring claude code, but will give it another go now to see how far I can get with the Pro plan.

      Turned out to be a blessing as it led me to discovering augmentcode.com which I'm now using. It's a monthly usage cap but has a unique context engine where it indexes your entire code base which gives its agents access to a lot more content about your code base which helps when adding features to match your existing implementations without needing to explicitly feed it context in every agent message. It still uses Claude Sonnet 4 [1] under the hood so the results are great.

      Blows me away what AI agents are capable of these days, it's especially nice when they end up creating new Tailwind UIs (Vue) that's better looking than what I was even thinking about creating.

      [1] https://www.augmentcode.com/blog/claude-sonnet-4-the-best-model-with-the-best-context-engine

    • atombenderSep 2025

      I wonder if Augment [1] are working on a Zed plugin.

      I've been using Augment for more than a year in Jetbrains IDEs, and been very impressed by it, both the autocomplete and the Cursor-style agent. I've looked at Cursor and couldn't figure out why anyone needed to use a dedicated IDE when Augment exists as a plugin. Colleagues who have used Cursor have switched to Augment and say it's better.

      Seems to me like Augment is an AI tool flying under most people's radar; not sure why it's not all over Hacker News.

      [1] https://www.augmentcode.com/

    • jannesblobelAug 2025

      Think of a refactor where you tried one approach, rolled it back, then found the right fix. If you squash, all those failures vanish. With full history, an AI (or future you) can see the dead ends and spot patterns. I think that’s what Augment Code is doing with their Context Lineage idea: indexing the messy history so tools can explain how code evolved.

      https://www.augmentcode.com/blog/announcing-context-lineage

    • chimeJun 2025

      Augment Code (https://www.augmentcode.com/) extension in VSCode. The remote agent feature is fantastic and the local agent is worth buying credits for. I've tried almost every AI editor (Cursor, Windsurf, Roo/Cline etc.), tried CLI-based coders (Claude Code, Aider, Codex etc.), and have used them all with ton of useful MCPs and in the end, I've had the best results with Augment.

    • bp93592203Jan 2026

      totally agree. Looks like the most common problem with the bubble is the terrible signal to noise ratio. Has anyone found a solution that works well? I see augment code is claiming their review agent is the best in terms of signal to noise ratio

      https://www.augmentcode.com/blog/we-benchmarked-7-ai-code-review-tools-on-real-world-prs-here-are-the-results

      has anyone tried it?

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