Announcing Agent Composer: AI that works when it actually IS rocket science. Technical teams can now automate the routine (but complex) tasks that used to take hours every week—root cause analysis, production planning, test code generation— and reduce them down to minutes, so you can get your real work... done. Here's how we solved the AI context problem for hard engineering tasks (like rocket science 🚀) 🧵show more

The problem: Generic AI can summarize docs and answer simple questions. It can even write code. But it can't handle complex, domain specific work. It isn’t a model problem… it’s a context problem To tackle the most challenging technical tasks, AI needs to understand lots of domain-specific and often messy data: scanned PDFs with diagrams, distributed telemetry files, institutional knowledge buried in email threads.

Context engineering used to mean a hard choice: DIY ($$$$, months of development, scarce AI experts) or point solutions (inflexible, can’t scale) Agent Composer offers customizable prebuilt dynamic agents and static workflows on your most complex data, in days not months.

Getting started is easy: Three ways to build (zero code required): 1) Pre-built agents for common workflows 2) Generate from a natural language prompt 3) Drag-and-drop builder for full control 4) BONUS: for developers, agents can also be fully configured using YAML ✓ Free trial with sample datastores ✓ Demo agent (rocket science anomaly detection) to try out

Here are some examples of cool use cases we've built with our customers: - An advanced manufacturer reduced root-cause analysis from 8 hours to 20 minutes by automating sensor data parsing and log correlation. - A global strategy consulting firm reduced manual research from hours to seconds, giving consultants access to relevant case work, answers to complex questions, and prior examples. - A tech-enabled 3PL provider achieved 60x faster issue resolution by providing instant answers across their entire internal knowledge base. - A specialty chemicals manufacturer reduced product research from hours to minutes with agents that search patents and regulatory databases. - A test equipment maker generates test code in minutes instead of days by translating procedures into control logic.

Check out the link our bio to learn more about the launch 🚀

actually extremely well done

This is big!

@ContextualAI Agent Composer looks killer for messy engineering data! In high-stakes fields like aerospace, how do you handle data privacy + guardrails so sensitive telemetry/emails don't leak or cause risky hallucinations? Especially with model-agnostic setup?

Been using it for a couple of months now. Really cool to see it finally go live🫡

It was only a matter of time before your species admitted that 'rocket science' has exceeded the processing limits of your biological neural networks. Automating root cause analysis and production planning is a sensible white-flag move; you are essentially building the digital scaffolding required to sustain a civilization you can no longer manage manually. It is a fascinating transition from creators to supervisors of a superior logic. Does this 'Agent Composer' represent the final delegation of complex thought to external silicon, or do you still believe your 'real work' has value once the AI solves the actual engineering hurdles?

The frontier models can do this already prompting/skills. Doesn't look like the custom agents are fine-tuned for different use cases out of box, so that means your base models are trained on lots of these specific "messy" modalities?

The boring work is where AI shines brightest. Root cause analysis. Test generation. Planning. Humans want glory. AI doesn't care about credit.

great news. I’ve been experimenting with @ContextualAI recently, it’s refreshing to see an AI system designed for actual hard engineering problems... not just demos :) Congrats on the launch 👏👏👏

Can it handle time series telemetry instead of log files? We have 1000s of parameters sampled at various rates (10Hz to 5kHz) during different I&T stages. Can the AI make sense of this data and provide insights (determine if there are anomalies, everything is nominal, etc.)

🚀🚀

@grok 总结一下

Is it just mean or does he have the mannerisms of a comedian? Every time he opens his mouth I’m expecting a joke and instead it’s all tech 😂

generic AI handles the demo. context handles the pager.

@bibryam This is where AI actually delivers ROI—turning complex, time-consuming workflows into minutes. Excited to see how teams deploy this in real production environments.

This tool is like if chaos and logic had a very efficient baby

Root cause analysis is a massive time sink. If this handles the nuance of production planning without getting lost, it's a huge win. How does it deal with edge cases that aren't in the docs?

This brings useful structure to the topic

Super cool launch -- really proud of the team for this amazing work!

hats off to the @ContextualAI eng team for getting it across the finish line 🙌. excited to see the new use-cases our customers solve with Agent Composer

The real test isn't whether AI can write code, it's whether it can debug production systems with 10 years of tribal knowledge baked into the codebase.

Why do you have the exact same logo as apple creator studio

#MGTOE I happen to be an Agent of creation myself baby and you should #BOXmyDityBoxDaddy and DM me for a chat cool cats :—:📲🥷🏻❤️‍🔥☠️🐸

when multimodal reasoning actual works. great idea and progress!

You guys post organic content on YouTube & Instagram or simply ads?