One model, many products for the world.
SF, USA
Joined March 2026
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Meet our HUMAN team.
Ex-Uber, ex-Microsoft, ex-VMware. All trying to kill pager culture, once and for all.
24
It's Tuesday.
You're at your desk, and a config change goes through.
No worries - it’s been reviewed, approved, and merged.
Then an hour goes by and your phone lights up: a service you've never touched is down. Then another follows..
15 minutes later, something three layers downstream that nobody documented starts failing and there are 14 people in a channel, all asking, “what changed?”
You already know the answer, but you should also know: this was preventable with Cielara.
Before any change merges, Cielara runs it against a live map of your entire production system.
We simulate the impact, showing you what breaks (and why) before anything touches production.
It’s now been a week and you log in on yet another Tuesday morning.
Same change goes through, but this time, all you need to do is a two-line fix. You’re welcome.
causaldynamics.com/
22
Let me guess, this was you last weekend:
It's 3am. You and 11 of the sharpest people you know are all awake, coffee already made, and straight into Slack checking logs.
You’re scrolling, reading, and typing the same question you’ve been asking: “What changed?”
Nobody knows, but you all spend the next 6 hours digging through deploys, configs, and git blame, trying to reconstruct what happened to a system that was fine 8 hours ago.
No eng needs to live like this.
You can prevent the config change that would have started the outage using Cielara which simulates the impact of a change before it reaches production.
We built it so you can live by our favorite motto: prevention over panic.
causaldynamics.com
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24
AI coding adoption is growing 25% a year.
But system stability drops 72% for every 25% of that growth.
Only one reason why: AI writes the code, but nobody fully understands it.
That gap is called verification debt, and we built Cielara to close it.
Book a demo at causaldynamics.com
Developers in Seoul, Manila, São Paulo, Mumbai, San Francisco, and New York tested real codebases and repos on 1,000 issues.
...Codex and Claude Code burn thousands of tokens per query.
With Cielara Code, an autonomous coding agent built on our flagship product, Cielara, we're at a fraction - 16% fewer errors, backed by a 125M token context window.
Agents are great at thinking. They fail at finding. Cielara Code gives them a map to navigate with first (or as Forbes called it: the traceability missing in AI).
Causal Dynamics Lab: building AI that reasons on 20 watts, not 20 gigawatts. Check out our growing capabilities here: causaldynamics.com/
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Below the fold is the lost-in-the-middle phenomenon. 80% chance you've experienced it with an AI tool but had no idea it had a name:
You spend time building up a working session with an AI tool - adding context, reaching a point where the responses feel genuinely useful - then close the tab.
The next day, it's gone. You start over, and summarize where you left off, but that itself eats into your limit.
This phenomenon occurs because AI has a context window: its working memory.
Think of it as a desk - whatever fits on the desk can be connected and compared. Whatever doesn't fit might as well not exist.
What most people don't realize is that the size of that desk also determines what kinds of questions are even possible.
- At a small context window (~10,000 tokens), the AI is good at one document at a time. The moment you ask whether it conflicts with something from last week, it has already let last week go.
- At 100,000 tokens, an AI can hold an entire project's worth of documents simultaneously and catch contradictions between all of them at once.
- At 1,000,000 tokens, AI is reasoning across everything it holds and surfacing connections that were never visible when the documents lived in separate systems, meetings, or years.
We published a piece walking through all 6 orders of magnitude - from 10K to 1B tokens - and what becomes thinkable at each level.
Read about it here (no technical background required!): ordnl.link/1ssE6sF
P.S. We currently operate at 125M tokens 🚀
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Casual Dynamics Lab retweeted
BREAKING TODAY! Causal Dynamics Lab outperforms Anthropic & OpenAI in multiple coding tests -- radicaldatascience.wordpress…
@CausalDynamics #AI #GenAI #LLM #coding
Casual Dynamics Lab retweeted
DORA 2025: adoção AI coding causou 7.2% decline em deployment stability. Por quê? Agentes navegam por grep. Cielara mapeia causalidade: 'qual arquivo afeta qual', 'quem é dono', 'o que rodava antes'. Quando projeto > 6 arquivos, recall Claude/Codex cai de 0.579 → 0.143. Brute force.