The more enterprises I talk to about AI agent transformation, the more it’s clear that there is going to be a new type of role in most enterprises going forward. The job is to be the agent deployer and manager in teams. Here’s the rough JD: This person will need to figure out what are the highest leverage set of workflows on a team are (either existing or new ones) where agents can actually drive significantly more value for the team and company. In general, it’s going to be in areas where if you threw compute (in the form of agents) at a task you could either execute it 100X faster or do it 100X more times than before. Examples would be processing orders of magnitude more leads to hand them off to reps with extra customer signal, automating a contracting review and intake process, streamlining a client onboarding process to reduce as many straps as possible, setting up knowledge bases than the whole company taps into, and so on. This person’s job is to figure out what the future state workflow needs to look like to drive this new form of automation, and how to connect up the various existing or new systems in such a way that this can be fulfilled. The gnarly part of the work is mapping structured and unstructured data flows, figuring out the ideal workflow, getting the agent the context it needs to do the work properly, figuring out where the human interfaces with the agent and at what steps, manages evals and reviews after any major model or data change, and runs and manages the agents on an ongoing basis tracking KPIs, and so on. The person must be good at mapping the process and understanding where the value could be unlocked and be relatively technical, and has full autonomy to connect up business systems and drive automation. This means they’re comfortable with skills, MCP, CLIs, and so on, and the company believes it’s safe for them to do so. But also great operationally and at business. It may be an existing person repositioned, or a totally net new person in the company. There will likely need to be one or more of these people on every team, so it’s not a centralized role per se. It may rile up into IT or an AI team, or live in the function and just have checkpoints with a central function. This would also be a fantastic job for next gen hires who are leaning into AI, and are technical, to be able to go into. And for anyone concerned about engineers in the future, this will be an obvious area for these skills as well.

We are open sourcing Dolly, a ChatGPT-like model that can do instruction following, created for $30, trained 3 hours on 1 server. The secret in magical human-like interactivity probably lies in a small dataset. databricks.com/blog/2023/03/…

We need to get ‘Waiter Productivity’ recognised as an Olympic sport. This gentleman would be a contender for Gold in that event…

"35 is the new 25!" 😂 Age is only a number, @djokernole! #AusOpen • #AO2023

And the 'Father Of The Year' award goes to this guy.....🤣🤣🤣

Before today, Lakshya Sen had not won a game against Viktor bhai on tour. Today, came back from 8-15 down in the decider to win the match. 3-mins or so doesn't do justice to the quality of this match in the later stages, but here are the highlights.

Early career years are painful. You feel like an idiot 98% of the time - lost, confused and insecure. I wish I had a cheat sheet of principles for my first job. So I put one together. Here are 20 things about building a career I wish I knew sooner: