geek, scribe, coffee snob, and wanna-be cyclist. Contributor to Apache Spark and Delta Lake maintainer. Developer Relations at Databricks (opinions r my own)
Seattle
Joined May 2008
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dennylee retweeted
What people do at work all day is changing.
Agents can take on more of the work we already know how to do, while people closest to the problem gain more room to investigate and act without waiting on layers of hierarchy.
a16z's @bhorowitz and @mikemcg0 explore why the system of record powering agents matters so much to that shift, and why Databricks is well-positioned to power it.
Read the full article: a16z.news/p/databricks-and-t…
dennylee retweeted
Ben Horowitz on Databricks CEO Ali Ghodsi: "You just don't get this good of a market opportunity with this good of an entrepreneur. That's the rarest of rare things."
Despite surpassing a $7 billion run rate and growing 80% year over year, Databricks might be the most under the radar story in Silicon Valley.
Three years ago, every interaction on Databricks involved a human. Today, the company is seeing more queries from agents than people.
Ali believes AGI is already here. Yet inside most companies today, AI still isn't trusted to reliably update records in Salesforce.
"AI does not have an intelligence problem," Ali explains. "It has a context problem."
Even the smartest human would be all but useless without access to the company's data, permission to act, feedback, or the knowledge in other employees' heads. Ali's answer is what he calls a "system of record for agents."
But the bigger question is how agents will change the firm itself.
85 years ago, James Burnham's The Managerial Revolution described how a small class of professional managers centralized the decision-making inside of companies. Today, thanks to a new wave of technology, the craft practitioners at the front lines are regaining responsibility again. The irony is that the decline of managerialism may look more like everyone becoming a manager.
In this issue of Profiles of the Future, @bhorowitz and @mikemcg0 explain how seven Berkeley academics built Databricks, and why it will power the future of the firm: a16z.news/p/databricks-and-t…
dennylee retweeted
"Not today."
📺: Seahawks Central
Thursdays 9:30pm KONG-TV
Fridays 7:30pm KING-5
🤝 Paid partnership
dennylee retweeted
Following a PR used to mean switching back to GitHub for reviewers and comments.
Omnigent’s Pull Requests panel now shows pending reviewers, review state, and a Comments tab with a count, plus color-coded authors in the thread.
🔗 Learn more: omnigent.ai/docs/interact/we…
dennylee retweeted
Macklemore at his show last night at Red Rocks: “Being a human being in this moment is not complicated. It is not political. It is human to have a heart. To watch others suffer and to say not anymore. So I say Free Palestine. I say Free Palestine! I say Free Sudan, I say Free Congo, Lebanon to Haiti to all the people that are affected by ICE in America that are afraid to leave their houses. The message will always be love” (Video: hey.itslizzz / TikTok)
dennylee retweeted
No wonder Apple is a 5 trillion dollar company.
UPS delivery guy: "Are you waiting by the door for this?"
me: "Yes!"
him: "I never run into people when I deliver, but on iPhone release date, everybody is home waiting."
dennylee retweeted
If you keep custom agents in a Git repo and run Omnigent on more than one machine, install an agent once with omnigent agent add and pick it from the new-session picker on every host you use.
Until now, a custom agent only became available by running a session with its spec file, and it belonged to that session. Installed agents are stored on the server under your account, so they sit beside the built-in agents on every host, with no server restart.
GitHub installs ask you to confirm first, since the repo’s config runs in your sessions.
👉 Learn more: omnigent.ai/blog/install-cus…
dennylee retweeted
Omnigent 0.19: a managed MCP gateway, keyless Git for sandboxed agents (approved repos over SSH, no key in the sandbox, push optional per repo), and agent editing in Settings
omnigent.ai/releases/0.19.0
dennylee retweeted
Just to prove we shot it practically🥲
No AI, shot in-camera.
Big thanks to @umoco2020 for providing the robotic arm!
Check out the full review to see the final shots➡️xitter.cf/mediastorm_en/status/2…
dennylee retweeted
Great work on fast long-context prefill. TokenGate is a trainable module that works with existing models to make long-context inference much more efficient.
dennylee retweeted
📣 Join us Nov 4: Graph Reasoning for AI Agents.
Danfeng Xu, CTO of @puppyquery, will walk through Omnigent + PuppyGraph: graph reasoning on your existing tables, in real time, without moving a row. Skip the ETL. Keep unified governance.
Register 👇
luma.com/omnigent-bnib
#Omnigent #PuppyGraph
dennylee retweeted
Databricks and @nvidia are expanding our collaboration so enterprises can customize open models on their own data and take them all the way to production.
With AI Runtime, developers can use NVIDIA NeMo, NGC containers and new Nemotron cookbooks to train and fine-tune models on serverless NVIDIA GPUs alongside governed enterprise data. Nemotron 3.5 lightning and Super VL are also ready to load, adapt and serve on Databricks from day one.
Customize with governed enterprise data. Serve in production. All on Databricks.
databricks.com/blog/databric…
dennylee retweeted
Incredible work by @veronica3207 and team!
Introducing MemCurrent, a persistent memory architecture designed to help production agents stop starting from zero.
MemCurrent combines episodic memory with derived memory across three access patterns:
• Plugins to log and load context automatically
• Tools the agent calls on demand
• An offline “dreaming” pipeline that consolidates memory in the background
Agents carry forward user preferences, prior corrections, metric definitions and successful workflows instead of rediscovering them every session.
On our internal benchmark built from real enterprise data, MemCurrent triples the agent's pass rate while using 31% fewer tokens and running 26% faster. It's built into Agent Bricks' Memory offering and already powers memory in Genie.
Read the research: databricks.com/blog/memcurre…
dennylee retweeted
Databricks AI Runtime (AIR) is now GA, offering an easy and super-fast way to launch GPU workloads. Unlike provisioning your own GPU servers, you get GPUs with your code in seconds, with easy access to all your data. This is especially relevant now that agents can automate much of AI training, and want to scale up/down experiments quickly. Read how companies like Robinhood, Superhuman, Factset and Merck have been using AIR to accelerate AI training: databricks.com/blog/ai-runti…
dennylee retweeted
Great conversation with @BrendanFoody talking about the main bottleneck to enterprise adoption of AI and AGI: knowing whether AI is doing what you want it to. The hard part is creating a measurable specification for qualitative tasks in the real data context, i.e., an eval.
We’ve automated a very low percentage of enterprise tasks with AI.
That’s @jefrankle’s estimate, and he thinks the models are already smart enough to do significantly more.
Jonathan is the Chief AI Scientist at Databricks, co-founder of MosaicML, and my latest guest on The Frontier.
We talked about why evals are the biggest bottleneck to enterprise AI adoption. The intelligence is increasingly there, but enterprises need to figure out how to define what they want agents to do and measure whether they’re doing it well.
Full episode below 👇
dennylee retweeted
Databricks is investing in New York for the long haul. Very excited to continue growing our AI research lab in NYC, now one of the largest in the city!
New York is becoming one of Databricks’ biggest AI hubs. 🗽
We’re expanding at 5 Bryant Park to ~120,000 square feet across five floors, including a dedicated Engineering and Research floor.
With teams building technologies behind Genie, Unity Gateway and CustomerLake, our momentum in NYC is only growing.