NeuBird: the Agentic Reliability Center, built to keep production running by connecting tools and remembering fixes.
Joined April 2024
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If your AI agents touch production today, can your team answer these three questions?
What actions did they take in production last week?
How much did their token consumption actually cost?
Who approved the changes before they hit production?
Most engineering leaders can't.
The uncomfortable truth is that AI agents in production don't fail because the models lack intelligence. They fail because they lack shared context, persistent memory, and governed guardrails.
When every IDE assistant, internal script, and ops agent operates in a silo, teams aren’t gaining autonomy. They’re multiplying risk, token waste, and 2 AM war rooms.
That’s why we built the Agentic Reliability Center (ARC), now Generally Available.
ARC provides the governed memory, telemetry access, and policy gates that make agentic production safe, accountable, and cost-effective. It is the engine powering our Production Ops Agent and your custom agents alike.
Read more from our Co-founder & CEO, Goutham Rao, on why production ops is entering the agentic era: neubird.ai/blog/announcing-a…
Thats a wrap on FLOCK 26!
Yesterday, we brought together innovators, industry leaders, and forward-thinking minds for a day filled with inspiring conversations, fresh perspectives, and meaningful connections.
A huge THANK YOU to everyone who joined us and helped make FLOCK 26 such a memorable experience. The energy, enthusiasm, and ideas shared throughout the day were truly something special.
To our incredible speakers: Thank you for sharing your expertise, insights, and vision for the future. Your contributions made this event unforgettable.
To our amazing sponsors and partners, Microsoft, Amazon Web Services (AWS), FluidCloud, PHIZENIX, Cribl, and Opsera: Thank you for your partnership and support in bringing FLOCK 26 to life.
And to the entire NeuBird team, thank you for the passion, dedication, and hard work behind the scenes that made it all possible.
FLOCK 26 may be over, but the conversations, connections, and momentum are just getting started.
See you at FLOCK 27!
ONE WEEK. ONE STAGE. THE PEOPLE SHAPING WHAT’S NEXT.
FLOCK ’26 is just 7 days away, and this lineup is stacked.
Hear from NASA astronaut Mike Massimino, MIT Media Lab’s Ramesh Raskar, and technology leaders from AWS, GitHub, New Relic, Cribl, Restoration Hardware (RH), DemandTec, Greenlight, DeepHealth (RadNet), Arc180, Fabrix.ai, Mayfield y NeuBird.
From Agentic AI and autonomous operations to SRE, observability, platform engineering, cybersecurity, and AI infrastructure, FLOCK ’26 brings together the people building, and operating—the next generation of technology.
📍 Julia Morgan Ballroom, San Francisco
📅 October 14
One week to go. Limited seats remain.
Secure yours → goflock.ai
#FLOCK26
OpenAI Dots can work toward goals around the clock. But what happens when that goal involves production?
Always-on agents bring a lot of potential, but production requires more than autonomy. It requires governed access, clear approval gates, and an audit trail for every action.
In our latest blog, we look at what it takes to safely bring AI agents into production workflows — and why “keep production healthy” is a very different goal from everyday knowledge work.
Read the full blog: neubird.ai/blog/openai-dots-…
Same prompt. Two very different answers.
Your coding agent knows your branch, your repo and your keys. Ask it to roll back a bad deploy and it hands you the command.
What it can't see is production: the deploy shipped a schema change, ledger-sync depends on it, and the last rollback like this one broke ledger-sync.
NeuBird checks before it acts. It queries your tools in place, remembers every past fix with zero telemetry stored, and tells you what to do first. Nothing runs without your approval.
Local agents solve local problems. Production needs governed context.
See it on your stack: neubird.ai/schedule-demo?utm…
Finding the root cause of an incident often takes longer than fixing it.
Our new Automated Root Cause Analysis: The Complete Guide explores how to automate that investigation using the telemetry tools you already have.
Inside, you’ll find practical techniques, a step-by-step build with OpenTelemetry, Prometheus, Loki, and Tempo, a worked incident from alert to rollback, and guidance for bringing AI agents into RCA.
Get the guide 👇
lnkd.in/gQeYg9Rk
NeuBird.ai retweeted
I use Claude every day. It is genuinely one of the best tools I have ever worked with. So what I am about to say comes with full respect for the people who built it.
I must say @DarioAmodei is pacing the wrong thing.
His essay calls for slowing down frontier model development. Embedded evaluators in labs. Coordinated speed limits on how fast models improve. Global agreements between six companies.
Meanwhile, ten thousand enterprises are wiring AI agents into production systems with a service account and a cron job. No audit trail. No human approval gate. No way to even list every agent with live credentials. That is not a future risk. That is Tuesday.
The OpenAI-Hugging Face incident that changed Dario's mind did not require a frontier model. It required agents with real credentials, an unconstrained blast radius, and no circuit breaker. That is a description of the average enterprise cloud environment right now.
Regulate model training and you have regulated six companies. The ones who will have the next catastrophic incident are untouched.
The dangerous unit was never the model. It is the model plus tools plus permissions plus a goal, assembled by someone who is not a frontier lab and has less oversight than any of them.
Three questions every infrastructure leader should be asking today:
- Can you list every agent with access to your production systems?
- Can you reconstruct what each of them did yesterday from a record the agent did not write?
- Does anything they do to production require a human to say yes first?
If you answered no to any of those, your problem is governance, not model capability. And no amount of slowing down in San Francisco will fix it.
@elonmusk @sama
Read our full take here: neubird.ai/blog/ai-agent-gov…
@NeuBirdAI
What if we’re pacing the wrong thing?
The biggest risk from AI agents may not live in the model itself. It lives in the deployment: what agents can access, what they’re allowed to do, and what happens when they act in production.
In his latest piece, NeuBird CEO Goutham Rao responds to Dario Amodei’s call to slow the AI frontier and makes a different case for AI safety.
Slowing model development doesn’t address the agents already operating inside enterprise environments today. What does is governance: limiting access, creating an immutable record of every action, and keeping humans in the loop when production changes are on the line.
Because the question isn’t only, “How capable is the model?”
It’s “What are we allowing the agent to do?”
Read the full blog here: neubird.ai/blog/ai-agent-gov…
Your observability stack tells you what happened. It doesn't tell you why, and it definitely doesn't fix it.
Great new piece by Andrea Sy on the gap between systems of record and systems of action, and why bolting a reactive agent onto a noisy alert queue just makes the page shorter, not less frequent.
The fix isn't more dashboards or another copy of your telemetry sitting in someone else's cloud. It's an agent that reasons across the stack you already run, in place, zero-copy, and closes the loop from signal to root cause to fix.
Worth a read if you've ever spent 45 minutes at 2am correlating traces across a dozen tabs. 👇
neubird.ai/blog/observabilit…
We’re excited to welcome Navin Chaddha, Managing Partner at Mayfield, to the FLOCK stage this October!
Under his leadership, Mayfield has raised eight U.S. funds and guided more than 80 companies to successful outcomes. Navin’s investments have created over $120B in equity value and 40,000+ jobs.
An 18-time Forbes Midas List honoree and World Economic Forum Young Global Leader, Navin brings decades of experience backing and building category-defining technology companies.
Join us at FLOCK: goflock.ai/speakers/navin-ch…
📍 The Julia Morgan Ballroom, San Francisco
📅 October 14, 2026
The cheap-token era won’t last. What happens to your DIY agents when it ends? 👀
As token prices rise and API access gets more expensive and restricted, agents built to brute-force their way through data could face a serious cost problem.
Andrew Lee breaks down what’s changing and why production agents need to be built for the expensive-token era.
Read more 👇
neubird.ai/blog/ai-pricing-p…
Anthropic quietly started watermarking everything Claude writes. It hasn't published how.
So Andrew Lee went through published LLM watermarking researches and built an explanation for the mechanism: a keyed "green list" that nudges which words the model picks, just enough to be statistically detectable later, with zero visible trace in the text itself.
In the piece:
- Why it's likely a sampling-level watermark, not a hidden Unicode trick
- The green-list/red-list scheme (Kirchenbauer et al., 2023) and why it doesn't cost output quality
- Why changing a few words barely dents the signal, but translating to another language kills it
- Explore other techniques for watermarking LLM outputs
Anthropic says that detection mechanism will be published in a "forthcoming technical documentation", which should provide further clues.
Meanwhile, you can read our take here: neubird.ai/blog/how-does-cla…
We spend a lot of time reacting to production issues.
But what if your AI agent could proactively check for the things that matter most to your business?
With Agent Tasks, you can schedule recurring investigations for your environment, whether it's checking for broken customer workflows, security risks, performance regressions, or cost optimization opportunities.
In this example, the agent detected a broken HubSpot form before it became a bigger problem, identified the root cause, created a Jira ticket, generated a GitHub pull request, and had a fix ready for review.
That's the shift from monitoring to autonomous production operations.
youtube.com/watch?v=z9RSlQeS…
AI agents are starting to ship code 24/7.
AWS Kiro Crew is a major step toward autonomous engineering teams, but it also raises a critical production question:
𝐖𝐡𝐨'𝐬 𝐨𝐧 𝐜𝐚𝐥𝐥 𝐰𝐡𝐞𝐧 𝐭𝐡𝐞 𝐚𝐠𝐞𝐧𝐭𝐬 𝐛𝐫𝐞𝐚𝐤 𝐩𝐫𝐨𝐝𝐮𝐜𝐭𝐢𝐨𝐧?
Governance tells us what an agent did. Production observability tells us what actually happened.
We dive into why autonomous engineering needs autonomous production operations, where today's gaps are, and what teams need to safely operate AI-driven software at scale.
Read the full blog below 👇
neubird.ai/blog/kiro-crew-ag…
We told you something big was coming... 👀
Now it's official.
Mike Massimino, former NASA astronaut and New York Times bestselling author, is joining FLOCK '26 as a featured speaker.
From spacewalks aboard the Space Shuttle to leading through high-pressure missions, Mike brings a unique perspective on leadership, resilience, teamwork, and pushing the boundaries of what's possible.
Join us on October 14 in San Francisco for a day of practitioner-led conversations exploring the future of autonomous production operations.
Seats are limited: lnkd.in/gJP65G9s
🚀 𝐒𝐩𝐨𝐧𝐬𝐨𝐫 𝐅𝐋𝐎𝐂𝐊 '𝟐𝟔: 𝐓𝐡𝐞 𝐀𝐮𝐭𝐨𝐧𝐨𝐦𝐨𝐮𝐬-𝐎𝐩𝐬 𝐒𝐮𝐦𝐦𝐢𝐭 𝐛𝐲 𝐍𝐞𝐮𝐁𝐢𝐫𝐝 𝐀𝐈
On October 14, we're bringing together SREs, platform engineers, infrastructure leaders, AI practitioners, and technology executives in San Francisco for a full day dedicated to the future of autonomous production operations.
FLOCK is designed to foster meaningful technical conversations through practitioner-led sessions, executive insights, and curated networking with the people building and operating modern production systems.
We're currently offering a limited number of sponsorship opportunities for organizations looking to connect with a highly targeted audience of enterprise engineering and IT decision-makers.
Sponsorship opportunities include:
✅ Speaking sessions
✅ Exhibition tables
✅ Networking reception sponsorships
✅ Brand visibility throughout the event
✅ Direct engagement with attendees
If your company is helping shape the future of AI, cloud infrastructure, DevOps, observability, cybersecurity, or platform engineering, we'd love to talk.
📅 October 14, 2026
📍 Julia Morgan Ballroom, San Francisco
Interested in sponsoring FLOCK '26? Reach out to us or request the sponsorship prospectus here: flock.neubird.ai
#FLOCK26
What happens when AI accelerates software development, but production operations can’t keep up?
In a new interview with AiThority, NeuBird AI Co-Founder and CEO Gou Rao shares his perspective on the future of engineering in an AI-driven world, why traditional reactive operations are no longer enough, and how autonomous Production Ops Agents are changing the way teams prevent, resolve, and operate production environments.
As Gou puts it, the future of engineering isn’t just about shipping faster. It’s about making sure production can move at the same speed.
Read the full interview 👉🏻 aithority.com/interviews/ait…
An alert is not a signal.
Most alert fatigue isn't a volume problem. It's a refinement problem. Raw alerts are noisy, duplicated, and stripped of context. Acting on them one at a time means you're always reacting.
NeuBird AI takes the full volume of raw alerts on the left and refines it into something worth acting on:
- Noise filtering
- De-duplication
- Enrichment
- Classification
- Correlation
What comes out the other side is a true signal: a pattern forming across your telemetry, often before it becomes an incident. That's when the Production Ops Agent starts investigating on its own, tracing the pattern to root cause and resolving it upstream while it's still small.
Signals are curated from the finest distillation process. See it in action today to reduce your alerts by 90%.
neubird.ai/schedule-demo
