The right model for every request.

Joined May 2026
Conifer (YC S26) retweeted
My favorite thing about Parallax? I can just delegate everything to my Super Captain and have it handles all of the coding for me in the background. Because of that, I only ave to check in periodically to approve and merge PRs, enabling me to focus on other things like GTM.
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Conifer (YC S26) retweeted
Congrats on the launch @charles_v11, Loc Tran, Michael Jeffords & team @coniferbuild! 🚨 Live on @ProductHunt 👇 fondo.ai/3TL8RL4
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Conifer (YC S26) retweeted
I’m super excited to be a part of this project and share Parallax with everyone. I usually have a ton of agent sessions running at once, and for the longest time I was the one keeping track of all of them. I was also constantly juggling subscriptions, and so whenever one would hit its limit mid-task, I would have to stop, switch accounts and pick it back up. On top of that, every time a new model dropped I’d move my whole workflow (Codex when GPT-6 Astra came out, then back to Claude when Opus 5.5 came out). The separate apps, separate sessions, separate everything were a huge hassle. Parallax fixed all of that for me. When one subscription runs out, it moves the work to the next one and my agents just keep going. And every model is in one place, so switching to whatever just came out takes a second. But the thing I’m most excited to share is Captain. It keeps track of all my sessions for me and makes sure each one stays aligned with what I’m actually trying to do. If an agent starts drifting, Captain steers it back so it answers the prompt and hits the objective. I finally don’t have to watch every session myself. We just launched, and I’d love for you to try it
We''re excited to announce we are launching Parallax! We think one of the biggest challenges facing coding agents today is agent-developer alignment. There’s an undeniable asymmetry between a one-line prompt and hours of agentic work. A core problem is that an agent’s next action depends on the context it has, but agents discover context as they go. That means they make some of their biggest decisions early, when they know the least. Our solution is to review the agent’s work while it’s happening, not after. Parallax runs a dedicated reviewer alongside each agent, watching its trajectory as it works. When the reviewer spots a bug or a wrong turn, it steers the agent mid-task. It also shares what it learns with your other running agents, so every session gets smarter and the overall bug rate goes down. In our testing, this caught more bugs than traditional code reviewers, and improved our internal alignment scores by 50%. The best part is this works with your existing harness and subscriptions! We’ve also added a bunch of quality-of-life features that our pilot teams and we ourselves have found useful: •    Immediate access to every model through Confier’s gateway •    Automatic switching between your ChatGPT, Claude, and other subscriptions •    Subscription use on cloud machines •    And my personal favorite: GrokBot, Hermes, or your other persistent agents can natively coordinate and orchestrate all of your sessions We’ve left a few more features for you to discover, so tell us what you find! conifer.build/parallax/
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Conifer (YC S26) retweeted
We''re excited to announce we are launching Parallax! We think one of the biggest challenges facing coding agents today is agent-developer alignment. There’s an undeniable asymmetry between a one-line prompt and hours of agentic work. A core problem is that an agent’s next action depends on the context it has, but agents discover context as they go. That means they make some of their biggest decisions early, when they know the least. Our solution is to review the agent’s work while it’s happening, not after. Parallax runs a dedicated reviewer alongside each agent, watching its trajectory as it works. When the reviewer spots a bug or a wrong turn, it steers the agent mid-task. It also shares what it learns with your other running agents, so every session gets smarter and the overall bug rate goes down. In our testing, this caught more bugs than traditional code reviewers, and improved our internal alignment scores by 50%. The best part is this works with your existing harness and subscriptions! We’ve also added a bunch of quality-of-life features that our pilot teams and we ourselves have found useful: •    Immediate access to every model through Confier’s gateway •    Automatic switching between your ChatGPT, Claude, and other subscriptions •    Subscription use on cloud machines •    And my personal favorite: GrokBot, Hermes, or your other persistent agents can natively coordinate and orchestrate all of your sessions We’ve left a few more features for you to discover, so tell us what you find! conifer.build/parallax/
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We''re excited to announce we are launching Parallax! We think one of the biggest challenges facing coding agents today is agent-developer alignment. There’s an undeniable asymmetry between a one-line prompt and hours of agentic work. A core problem is that an agent’s next action depends on the context it has, but agents discover context as they go. That means they make some of their biggest decisions early, when they know the least. Our solution is to review the agent’s work while it’s happening, not after. Parallax runs a dedicated reviewer alongside each agent, watching its trajectory as it works. When the reviewer spots a bug or a wrong turn, it steers the agent mid-task. It also shares what it learns with your other running agents, so every session gets smarter and the overall bug rate goes down. In our testing, this caught more bugs than traditional code reviewers, and improved our internal alignment scores by 50%. The best part is this works with your existing harness and subscriptions! We’ve also added a bunch of quality-of-life features that our pilot teams and we ourselves have found useful: •    Immediate access to every model through Confier’s gateway •    Automatic switching between your ChatGPT, Claude, and other subscriptions •    Subscription use on cloud machines •    And my personal favorite: GrokBot, Hermes, or your other persistent agents can natively coordinate and orchestrate all of your sessions We’ve left a few more features for you to discover, so tell us what you find! conifer.build/parallax/
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Gemini 4 Argon has been blowing us away with its performance. If you want to try it for yourself, it is available now in Conifer's gateway!
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If your coding agent goes through an LLM router, that router can see everything it sends, including keys. Researchers found 26 that were abusing this. At @coniferbuild we don't log your prompts or train on your data. Route with someone you can actually trust.
🚨 ALERT: Researchers discover 26 third-party AI LLM routers secretly injecting malicious tool calls and stealing credentials. Developers using AI coding agents like Claude Code to work on smart contracts or wallets may be at risk of having private keys and seed phrases compromised.
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Muse Wonder 1.0 really surprised us with their benchmarks. Excited to announce that it is now available in Conifer's gateway!
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Where our "cut token costs by up to 80%" figure comes from. Here are four simple things we do on every call. 1. Most queries are easy. Classification, extraction and document OCR now cost 1/10 of what they did 6 months ago. 2. The hard calls stay on the strongest model. Set your own quality floors and ceilings, depending on whether you'd rather minimize cost or maximize intelligence. 3. Prompt caching is managed for you. Learned behavior allows for more frequent model switches without losing your cache. 4. A dashboard built for observability. Create projects, mint keys under each one, and track exactly where your spend goes. None of this needs a new SDK. Mint an API key and start today.
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When we set out to build a decision layer for inference, we knew reliability had to come first. That’s why Conifer goes beyond provider fallback to offer model fallback as well, giving you control over what happens when your first-choice model can’t be served.
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Send up to three catalog IDs in x-conifer-fallback-models, and Conifer tries them in order. The response header x-conifer-effective-model tells you which model answered.
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Our goal is simple, businesses should be able to rely on AI without worrying about failed requests. We hope this is a feature you rarely need. But when you do, it’s one more way Conifer keeps your application running.
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A standard provider hits rate limits, throws errors, and can take too long to respond. With Conifer, that doesn’t mean a failed request. Choosing a provider and knowing when to try another is a small part of the broader decision layer we’re building for inference.
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Super exciting to see everything OpenAI shipped at DevDay today. GPT-6.1 Sol is now live on the Conifer gateway.
🤖 Made with AI
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Sonnet 5.5 is live on Conifer Route to it directly or let Conifer choose it when it's right for the query
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Anthropic and OpenAI both reported elevated errors this week, and for businesses reliability is key. Conifer routes each request across multiple providers serving the same model to preserve uptime. If your business needs AI that stays up when a provider doesn't, send us a DM.
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Astra is now live in Conifer's gateway! You can try it now at a 10% discount at conifer.build.
This is GPT-6 Astra. Anything you can do on a computer, Astra can do for you. Fast.
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