Ep 6- Autonomous AI Agents in B2B SaaS, Building for RevOps, future AI interface, challenges + more
Summary
TLDRIn this thought-provoking discussion, Renee engages with a guest who shares insights into the AI industry, particularly the significance of innovative user interfaces beyond mere text inputs. They delve into the potential of specialized AI tools tailored to specific use cases, exploring the integration of probabilistic systems and embracing their inherent quirks. The conversation touches on the challenges faced by sales teams in adopting AI, the need for open-mindedness, and the optimism surrounding AI's evolution towards more natural and intuitive interfaces. Additionally, they explore the guest's diverse interests, including urban planning, startups, and the captivating realms of psychology and consciousness.
Takeaways
- 🤖 AI agents like ChatGPT provide generalists with 'superpowers' to tackle complex projects and tasks beyond their expertise.
- 💬 Text input interfaces like chatboxes are limited and frustrating ways to interact with AI systems. More intuitive interfaces like buttons and visual builders are needed.
- 🧩 Specialized, task-oriented AI tools with simple user interfaces tailored to specific use cases will likely be more successful than general-purpose AI assistants.
- 🤝 Collaboration between humans and AI systems that leverage human feedback loops (e.g. reinforcement learning) will become more common.
- ⏳ Overcoming hesitancy around AI systems taking unpredictable or incorrect actions will take time as people get more comfortable with probabilistic outputs.
- 🔮 The guest believes AI assistants' capabilities will rapidly improve, increasing their accuracy and usefulness over time.
- 🏢 Enterprise sales teams are key targets for AI-powered sales intelligence tools that can streamline research and strategy.
- 🌐 Online communities like Twitter and Reddit are valuable for learning about and discussing the latest AI developments.
- 🤖 The guest is interested in eventually working more technically, learning areas like robotics engineering and woodworking.
- 🔑 Interfaces beyond just text/voice input are crucial for unlocking AI's potential across diverse use cases.
Q & A
What was the key frustration highlighted by the speaker regarding AI and text input interfaces?
-The speaker expressed frustration with using text boxes and voice input as the primary interface for interacting with AI systems, finding them too limiting and unintuitive. The speaker believes that text boxes and voice input alone are not the best ways to interact with most software tools.
How did the speaker's experience with Anthropic's Omni AI agent differ from using vanilla ChatGPT or other language models?
-The speaker found Omni's AI agent to be more sophisticated and capable of providing detailed and insightful outputs compared to vanilla ChatGPT or other language models. While the outputs from other models were sometimes inconsistent or off-base, the speaker saw glimpses of 'gold' in Omni's responses that showed real potential.
What were the three main objections or concerns that the speaker encountered from potential Omni customers?
-The three core objections were: 1) Concern about hallucinations or inaccuracies in the AI's outputs; 2) Reluctance to change from established tech stacks and sales workflows; and 3) Skepticism from teams accustomed to traditional, relationship-based selling methods.
How did the speaker view the role of user interfaces and specialized tools in the future of AI adoption?
-The speaker believes that successful AI adoption will require more specialized, purpose-built tools with intuitive user interfaces tailored to specific use cases, rather than relying solely on generalized text or voice input. Diverse interfaces beyond just text boxes will be necessary to make AI more accessible and user-friendly.
What did the speaker find intriguing about the work of Carl Jung, the psychoanalyst?
-The speaker found Carl Jung's theories on consciousness, identity, and the origins of his ideas fascinating, especially in relation to discussions around generative AI and general intelligence. Jung's framework for understanding consciousness within non-organic systems was particularly compelling to the speaker.
How did the speaker's background in urban planning and affordable housing influence his career path?
-After studying urban planning and working in affordable housing development, the speaker became interested in social entrepreneurship and community-driven initiatives. This led him to explore startups, which he found to be a faster way to drive impact compared to the slow pace of government policy work.
What was the speaker's perspective on the trade-offs between open-source and closed-source technologies?
-The speaker acknowledged that there can be valid reasons for choosing open-source or closed-source technologies, and that neither approach is inherently better or more virtuous. The choice depends on the specific goals, problems, and use cases being addressed.
How did the speaker view the role of probabilistic systems and human feedback in the development of AI tools?
-The speaker believed that more people will become comfortable with probabilistic AI systems that may not be perfect but can still provide significant value most of the time. Incorporating human feedback through techniques like reinforcement learning will be crucial for improving these systems over time.
What were the speaker's thoughts on the impact of AI on the physicality of day-to-day experiences?
-The speaker expressed concern that the "software eating the world" prophecy has led to a loss of physicality in daily experiences. He wished for more innovation in hardware and tangible interfaces to complement the advancements in software and AI.
If given an extra five hours per day, how did the speaker plan to spend that time?
-The speaker said he would spend three hours learning robotics engineering, specifically focusing on linear algebra, as he sees himself pursuing more technical work in the future. The remaining two hours would be dedicated to learning woodworking, an art and craft he has been interested in for a long time.
Outlines
🌐 Exploring Innovative User Interfaces for AI Interaction
The speaker expresses frustration with text-based interfaces for interacting with AI systems, as they often require learning specific prompts like 'magical spells'. The speaker advocates for more intuitive and user-friendly interfaces beyond just text input, such as buttons and graphical interfaces tailored to specific use cases. This would allow users to interact with AI agents more naturally and effectively.
💡 The Generalist's Superpower: Augmented Knowledge with AI
The speaker shares their experience as a generalist without deep expertise in any particular area. By using tools like ChatGPT, they felt empowered to take on more complex projects and tasks that would typically require specialized skills. AI agents and language models act as knowledge augmentation tools, enabling generalists to explore broader domains and tackle bigger problems. The speaker also touches on their background in urban planning and the transition towards startups.
🛠️ Embracing AI for Community-Driven Entrepreneurship
The speaker recounts their journey from affordable housing and urban planning to exploring social entrepreneurship and community-driven initiatives. This exposure led them to appreciate the potential of startups and new technologies to drive positive change more rapidly than traditional government policies. The speaker shares their optimism about the opportunities AI presents for doing good while also achieving business success.
🎯 Contextual Interfaces: The Future of AI Interaction
The speaker envisions a future where AI systems will be integrated into specialized tools with tailored interfaces specific to the user's goals and use cases. Rather than relying solely on text prompts, these tools would allow users to interact with AI agents through intuitive interfaces like buttons and drag-and-drop features. This approach would enable more natural and efficient collaboration between humans and AI, aligning the system's outputs with the user's desired outcomes.
🤖 Overcoming Objections to AI Adoption in Enterprise Sales
The speaker discusses the common objections and concerns that enterprise sales teams have about adopting AI solutions like Omni. These include concerns about the accuracy and reliability of AI-generated outputs, resistance to changing established sales processes and tech stacks, and a preference for maintaining control over every aspect of the workflow. The speaker explains how Omni addresses these concerns through ongoing model improvements, flexibility in integrating with existing systems, and probabilistic decision-making capabilities.
🤝 Human-in-the-Loop: Bridging the Gap with Reinforcement Learning
The conversation touches on the concept of reinforcement learning with human feedback, often referred to as "human-in-the-loop." This approach involves users providing feedback (e.g., thumbs up/down) to AI systems, enabling them to learn and improve continuously based on human input. The speaker acknowledges that while some users demand near-perfect accuracy, others are open to working with probabilistic systems that may occasionally make mistakes but offer significant value overall.
📐 Strong Opinions on AI Interface Design and Specialization
The speaker shares their strong opinion that text-based and voice interfaces for interacting with AI systems are limited and not the best approach for most use cases. Instead, they advocate for more specialized, purpose-built tools with intuitive interfaces tailored to specific contexts and user needs. This aligns with their belief that a diverse tech stack with specialized tools will emerge, rather than a few dominant platforms attempting to serve every use case.
🚀 Personal Interests: Robotics, Woodworking, and More
When asked about how they would spend an extra five hours per day, the speaker expresses their keen interest in learning robotics engineering, particularly the hands-on aspects like linear algebra. Additionally, they mention a desire to explore woodworking and arts and crafts, showcasing their diverse range of interests beyond their professional pursuits in the AI space.
Mindmap
Keywords
💡Prompting
💡Interfaces
💡AI Agents
💡Hallucination
💡Generalists
💡Reinforcement Learning with Human Feedback (RLHF)
💡Probabilistic Systems
💡Special-Purpose Tools
💡Multidimensional Interaction
💡Robotics Engineering
Highlights
When I first started using Omni it like there was just this like holy moment where um you know, you put in your your query and then at the time was just this research tool so, you would put in your query and it would, go off and do research and you know two, minutes later you'd get this whole, report that would have taken you, probably half an hour to put together by, yourself
And when then when we started, to build the sales tool so this was a, little bit uh later on um same moments, happened where the anal would it would, go off and do research on these uh you, know prospects that that you were trying, to sell to um and it would make these, inferences about how to sell to them uh, what messaging is going to be most, effective for various buyers
And it was, it was still early on and so the tech, was a little bit inconsistent sometimes, the answer would be a little bit out of, left field but sometimes there would, just be gold in there and like I knew, seeing some of these um outputs that, were so much more sophisticated and so, much more detailed than what you would, get from vanilla chat GPT or bar there's, really something here that's special
I think the thing that um and then your, prior guest who who we were talking, about earlier the account executive um, he he put it in in such a perfect way, that that uh I also really um resonate, with like when I started using chat GPT, to write code I'm somewhat technical I, would say right I have a background in, programming through undergrad and, independent projects in grad school but, like by no means am I an engineer or, data scientist or anything and when I, got my hands on chat chat GPT and, started to build out projects with it, felt like I had superpowers
My undergrad I I, didn't know really have any sort of uh, plans going out of school I didn't want, to be a consultant I didn't want to be a, banker I didn't want to be an engineer, uh but I was really interested in cities, and urban planning and fell into that, kind of career path
Ended up working internships and, through some startups with various, companies and and Founders and investors, that were in that space uh and that was, kind of like a gateway drug into, startups in general where I just felt, like so much more at home being a, startup operator than working in like a, traditional government policy setting, which is just so slow
And there are a lot of other, tools that are philosophically in in, kind of the same same boat it makes me, think of um like I've used a lot of I, want to say like no code web scraping, tools where it's like they and I've just, leared the word alignment and what that, means in AI and that's like the AI or my, definition I'm going to butcher it but, that it's doing the thing that I want it, to do in the way that I want to do it
So like that that's like the, direction that we're building at Omni, for example and there are a lot of other, tools that are philosophically in in, kind of the same same boat it makes me, think of um like I've used a lot of I, want to say like no code web scraping, tools where it's like they and I've just, leared the word alignment and what that, means in AI and that's like the AI or my, definition I'm going to butcher it but, that it's doing the thing that I want it, to do in the way that I want to do it
Interestingly I I never, really especially wanted to work at an, AI company I was more just drawn by um, the really interesting technology and, the opportunity to work with these tools, that I you that are just so fascinating, um and have so much, possibility
Um and you know actually what's really, interesting is that a lot of these teams, are the ones that are most eager to, adopt a tool like Omni or something in, our in our realm once they kind of get, comfortable with it I use it um and tral, it out because they don't even have to, learn all this super complex automation, right they don't have to have a revops, team they don't have to do all of this, it's it's literally like a plug-and, playay system that works
I think what, we're definitely encountering is like, some people are are very open to using, these systems and are comfortable to, like deal with the underlying models, which are unpredictable inherently, they're probabilistic systems and I, think some teams just require absolute, certainty that everything that gets, output is what they expect it to be but, yeah these these the technolog is always, improving and I think you know similar, to how every kind of technological era, comes with you know a lot of people who, are uncomfortable using different, technology or thinking about different, workflows or just like different ways of, solving problems and then there are, people who are very comfortable in those, modes um we'll see the same things uh, here where I think over time more and, more people will just start to, understand probabilistic systems better
I think my strongest, opinion is um around interfaces other, than um chat input uh to interact with, these systems and when I say chat I both, Voice and text I I truly think that, while that's a great way of interacting, with language models and certainly it's, it's kind of like like you know text is, the fundamental unit of interacting with, language models of course but I think, from like a user perspective you'll see, more and more interfaces that are you, know I think more comfortable and more, natural to whatever the use case and the, context is
And along with that I think, what what uh met necessitates is more um, special purpose tools so rather than, going to chat GPT for everything you, want to do I think it'll be look much, more like yeah like software prior to uh, chat gbt where you had you know your, tool that does this and your tool that, does that and and you know you you had, this like more diverse Tech stack that, you would go to
I really don't think, we'll see uh you know just like a, handful of software platforms dominate, everything um when it comes to like, where users spend their time to uh get, work done or or get play done or, whatever I I do think that we'll see, quite a bit of diversity still um and, that'll just be necessitated by like, it's impossible to build for every, single use case well that there's a lot, of value in building for specific person, and um that will just then necessitate, different design, decisions
So so actually I, wish I had way more than three hours you, can have five I'll give you five five, okay well i' spent three of those hours, I've been really interested in robotics, and I I want to learn Robotics and, specifically like robotics engineering I, think longterm I see myself doing work, that's much more technal technal than, what I do today so robotics engineering, and like I've been learning uh spending, some time self learning linear algebra
Transcripts
but it's like one of my Crusades is as
as long as I work in this space is
certainly to show that the text box is
is you know and text is just not the
only way to inter interact with these
tools Renee here at UNS superb learning
your easy listening podcast for bleeding
edge open source Tech no I think there
is something to like like physical
things so I spoke to someone the other
day that uses a stream deck to do home
automation and he said that he like
twists a thing and then the lights come
on and I was like oh that's amazing yeah
that's what I don't know what rabbit
does at all but that's like piece of
Hardware so that's one of my wondering
if Hardware is going to be a thing in
the future I don't know yeah Hardware is
I think there's so much it's one of like
those things that has really
disappointed me actually if you if you
want to say like like another hot take
about tech an AI I've been so more Tech
but like I've been so disappointed about
how little like like Innovation there's
been in Hardware you know over the last
like 20 years like yeah of course I mean
we have like VR glasses you know VR AR
stuff and we have iPhones and like
there's like some great things but those
are are like singular inventions in like
a decade right um when you think about
that compared to how many different like
typ of software we have and and you know
it's a matter of Economics it's a matter
of Supply chains and difficulty of
building new hardware um I wish there
was more because it's so something about
it just being tangible makes it so
satisfying like to hold to to interact
with I
think yeah that's one downside I think
to the sort of software eating the world
Prophecy from you know andreon like
which has probably played out to be more
or less true so far um
but we've lost something about the
physicality of our day-to-day
experiences that um I wish we could get
back you know what I'm going to title
this
video what man angry at lack of
hoverboards that shakes fists because
there is no flying cars J promised me
flying cars yeah but no I get what
you're saying so I'm sitting here today
with film star Natalie Portman I'm
kidding you know the Lonely Island what
Lonely Island like the the band like the
SNL thing yeah yeah yeah yeah yeah that
was from the Natalie Portman rap in like
2009 my God and every time I hear I'm
sitting here today I think a film with
film star Natalie Portman soya this is
the thing I've never said your last name
out loud middle ear oh like middle ear
yeah yeah like so middle ear who is
working as chief of staff at Omni an AI
agent for you still
BB sales BB sales and do you want to
kick it off maybe some background into
how you got into the AI space was Omni
your gateway drug yeah so I actually
first got into the AI space building
independently um so when I worked at the
company I was at prior to Omni uh was
seeing chat GPT launch and a lot of cool
AI tools launch and I've always sort of
been a tinkerer when it comes to new
technology and and a lot of stuff that's
been open sourced and just available
online and so was really eager to get my
hands on the open AI API um and started
to build some independent projects with
it pretty much as soon as it came out
and so that was my first foray into all
of this and built some uh little little
projects which I can talk about later on
I guess but uh no otherwise I'm like a a
kind of proper work capacity Omni was
the first time I got to work with
generative Ai and prior to Omni the only
experience that I had had with uh
machine learning and AI systems was uh
pricing optimization models um that I
worked on at at an e-commerce company
before that um yeah so we joined Omni
working with uh at the time the solo
founder David back in late May early
June um really just doing the very early
stages of um user research market
research and then eventually um you know
built it into a full company and where
are you at now with with Omni like who
do you serve so right now Omni we serve
uh customers um in B2B sales but the the
unifying thing is that these are
companies in organizations that sell to
larger midmarket Enterprise buyers so we
really support these more complex um
longer sales cycles that are very
research driven and very kind of
consultative in nature and I only found
out the other day that did you say
you're a python teachers assistant I was
yeah in grad school uh was ta for our
data analytics with python class class
ES that's really cool I remember I think
I don't know if it was a tweet that you
that you did that was like um said
sequel is unlock to I'm just going to
make up a quote that you said and just
put words in your mouth but it's
essentially like sequel is like an
unlock for Ops people and I sat I sat
with myself and I was like I don't know
sequel but it was a great point I feel
like python is something like
foundational that is great to know going
into AI you just explained how you made
the decision to to go with your ICP but
you surprised by how much these AI
agents could do or like when you joined
Omni what did you think you were joining
early on I honestly had no idea um it
was pretty amazing to see this vibrant
and like super passionate community of
users just from the beginning I mean
this was the height of the hype and
craze around at the time I think it was
GPT 3.5 which was out and maybe GP GT4
at that point um and there was just so
much excitement around it so it was
super fun to talk to users where I DM
somebody or email somebody and of course
they would want to talk to me and would
interview them uh and yeah it was a
really great experience so it started
off like I said sort of just doing
interviews and market research to try to
figure out like what direction should we
point the ship in um and then uh it
became something that was a little bit
more L and marketing oriented um and
also just the basic operations starting
up the company and getting our
accounting in order getting our legal in
order I think interestingly I I never
really especially wanted to work at an
AI company I was more just drawn by um
the really interesting technology and
the opportunity to work with these tools
that I you that are just so fascinating
um and have so much
possibility uh when I first started
using Omni it like there was just this
like holy moment where um you know
you put in your your query and then at
the time was just this research tool so
you would put in your query and it would
go off and do research and you know two
minutes later you'd get this whole
report that would have taken you
probably half an hour to put together by
yourself and when then when we started
to build the sales tool so this was a
little bit uh later on um same moments
happened where the anal would it would
go off and do research on these uh you
know prospects that that you were trying
to sell to um and it would make these
inferences about how to sell to them uh
what messaging is going to be most
effective for various buyers and it was
it was still early on and so the tech
was a little bit inconsistent sometimes
the answer would be a little bit out of
left field but sometimes there would
just be gold in there and like I knew
seeing some of these um outputs that
were so much more sophisticated and so
much more detailed than what you would
get from vanilla chat GPT or bar there's
really something here that's special
CU I know we met through generalist
World which is a community online
and I think that there is like a really
big cross-section of people interested
in Ai and very generalist mindsets or
very um potentially like neurod
Divergent people not labeling you but
definitely um yeah so I I don't know if
you want to start with urban planning or
your own projects or whatever sure uh
well I actually let me start with the
general World thing and then I can talk
more about the urban planning so I I
think the thing that um and then your
prior guest who who we were talking
about earlier the account executive um
he he put it in in such a perfect way
that that uh I also really um resonate
with like when I started using chat GPT
to write code I'm somewhat technical I
would say right I have a background in
programming through undergrad and
independent projects in grad school but
like by no means am I an engineer or
data scientist or anything and when I
got my hands on chat chat GPT and
started to build out projects with it
felt like I had superpowers like you
know here I am like it would take me
probably a month to build the things
that with chat GPT I could put together
in a weekend and so as a generalist with
a lot of different interests and you
know no super deep expertise certainly
in any technical area or any area of
like subject matter the most part um
being able to have this like
augmentation really of of knowledge um
that you know and then when you have ai
agents that layer on even more kind of
ability to S sort of support you in
workflows that are more complex than
just kind of prompting something and
getting an answer back these tools are
so exciting because it it lets me
without any of those uh specialized
skills um really take on bigger problems
and projects umly so so that's been
great and yeah the urban planning thing
I mean you know I think it's a a pretty
typical story for anybody who's got a
kind of generalist skill set and and
background where um my undergrad I I
didn't know really have any sort of uh
plans going out of school I didn't want
to be a consultant I didn't want to be a
banker I didn't want to be an engineer
uh but I was really interested in cities
and urban planning and fell into that
kind of career path uh first in the
private sector doing uh affordable
housing and mixed income housing
development and then went to grad school
to do research around affordable housing
and um Community Development and when I
was in grad school got very interested
in social entrepreneurship and a lot of
the work that was going on in Chicago
focused on kind of community-driven
Entrepreneurship local entrepreneurship
and ended up working internships and
through some startups with various
companies and and Founders and investors
that were in that space uh and that was
kind of like a gateway drug into
startups in general where I just felt
like so much more at home being a
startup operator than working in like a
traditional government policy setting
which is just so slow right like I was
like kir was slighting in policy School
seeing you know wh Mo hit the streets
with autonomous vehicles and Airbnb was
having huge impact on the property
market and city and state governments
were just like twiddling their thumbs
with no budget to do anything um and you
know as somebody who's fairly impatient
I became a fairly easy choice to say hey
there's this other career path where
perhaps it's not as like Mission driven
per se but there's a lot more
opportunity to actually have an impact I
felt and yeah that's what sort of taken
me in this direction absolutely have
like a healthy cynicism around this
stuff that like I think at the time I
was a bit naive to but I I honestly do
and you know perhaps still naively
believe that like there are a lot of
opportunities to do a lot of good in
this space and still you know make
shareholders happy and all that all that
stuff doesn't have to be just you know
all one or all the other um I think it
was I say Dan from Jan Daniel the
co-founder of Jan he mentioned it was
like in a public discussion on GitHub of
all places that there is like a little
bit of virtue signaling with the open
source space and it's like just because
something's open source not proprietary
technology doesn't mean that it's
inherently better or virtuous or there's
there's a lot of um I I think I am a
professional
offence and it's it's not for lack of
conviction it's just for openness for
whole strong opinions loosely held and
so I feel like I think it's something
that we potentially both struggle with
as generalists you're so open to so many
different things that it can seem like
oh you've got no opinions and it's like
no I do I've got Direction Just lots of
different directions all at the same
time absolutely or it could be like I
have you know there there might be a
goal that I want to achieve or a set of
outcomes that I want to achieve or
problem spaces that I'm really excited
about working on but I I think I bring a
more diverse tool set then somebody else
who might say hey look I've got a wrench
and a screwdriver like I I can only use
these two things whereas I'm coming in
with a wrench a screwdriver a set of
paints you know a computer over here all
this other random stuff and and so you
get to be a little bit more creative but
I think at the same time you always have
to like be able to answer that question
of like why do you need to bring these
tools to this particular problem like
are so yeah there's always a trade-off
that you make right and it's the same
thing there's also a trade-off that you
make with open source versus closed
Source there are good reasons why you
might choose one versus the other yeah
well you you mentioned about
frustrations and this isn't I feel like
this should be a question that I ask
people often what frustrates you most
about using like ai ai agent or any part
of the process oh what frustrates me the
most that's an interesting question I my
mind goes to prompting uh I don't want
to be what's the word suggestive though
I don't want to give you no I think
that's it I I think what really
frustrates me the most about a lot of
using a lot of these tools today is that
like text input uh text box is just not
the best interface to interact with most
software tools it's the same thing that
frustrates me about like you know voice
activated like Alexa and stuff like it's
great for some tasks right I love my
parents Al Alexa I can tell it to play
music but I can't ask it to do much else
for me right um For Worse the computer
screen with the mouse and keyboard and
buttons and and all of that uh is a
really really good user interface um and
not to say that there aren't others and
I think VR that's all really cool and
and will come up and and I just think
that like a text box is so limited um
and in particular it's not so much that
it's like um only one way of interacting
with something but there's so much it's
so difficult sometimes to actually
Express what you want uh through that
simple input um you have to learn what
are basically these magical spells that
that you need to input to this machine
to get it to work right and it's it's
not as if there's like that much logic
to it necessarily like there is a lot of
logic and their structure and like there
there are a lot of great guides on
prompt engineering out there um but
still there's like the peculiarities of
how these systems are trained and and
the fact that many of them are black
boxes means that in order to prompt them
Well there's almost this like trial and
error that reminds me of um when I used
to study history in school and would
read about how the ancient Romans would
learn all these like magical spells in
order to make sure that their crops
would grow correctly and that their
armies would win in battle they they had
to learn all these intricate little
steps and words to say just because
these things are of course very
difficult to influence um and it's the
same thing with these these models in a
kind of strange way that's how I always
feel using them like I just want to
click a few selection boxes and it'll
make my life so much easier but um as as
general purpose tools they need to be
flexible right they can't like the the
chaty BTS and Bs right if if that's all
you have is input this one text box that
you use to do everything it's on the one
hand unlimited and totally open sandbox
which is great but on the other hand
it's so difficult to interact with
sometimes if if there's a specific
output that you're looking for it's kind
of like needing um it's like if you're
working at I don't know any SAS and it's
like you need to be an expert in hub
spot and air table and whatever else
suddenly knowledge workers are all that
more valuable because like yeah you can
have the engineering tool but who's
going to drive it and this is like me
battling for revops people everywhere
because I feel like they're so valuable
um yeah but imagine like if in order to
like you know put together a particular
HubSpot uh like I don't know
customization or something like yeah it
works automatically which is great but
you have to spend half an hour trying to
figure out how do I you know prompt this
thing just to get this exactly correct
output and it's fun don't get me wrong I
love tinkering with this stuff and
exploring it and there are people I'm
sure who are much better account
Engineers than I but it's like one of my
Crusades is as as long as I work in this
space is certainly to show that the text
box is is you know and text is just not
the only way to inter interact with
these tools and neither is voice like
there there has to be some kind of
multi-dimensional interaction mechanism
like neurot Tech like no no no I just me
something super simple like like uh
buttons and interface I think and this
is why like and you can only make this
happen if if you have more special
purpose tools where you can as um a
designer and as an engineering team or
as as a product team anticipate what are
my users trying to accomplish with this
tool so that I can build an interface
that supports it right that provides
these mental shortcuts these like uh
metonyms so to speak right the these
analogies within user interface so that
a user rather than having to type out in
words every single thing that they want
to do and want to accomplish they can
simply just click here drag there
whatever and it just works uh the way
that they intend to I'm thinking about
those gesting like the almost the no
code Builders where it's like you drag a
block and it's like this block is a I'm
actually thinking of something a little
bit different which is not so much a no
code Builder so much as it is very very
simple user interfaces
where the the reason why you come to
this tool is to accomplish a specific
task right and you have let's say an AI
agent within the tool that understands
what your goals are right you're able to
tell this this software that you're
collaborating with what goals you're
trying to accomplish what data you have
access to in order to make decisions
about how to accomplish those goals and
then the AI is intelligent enough to
actually accomplish them and make
decisions about how to do it right and
so rather than having to put together as
you're describing these fairly
complicated uh flowcharts if then rules
about um how to build out these these
decision trees and and workflows it's
actually something much simpler which is
to say like hey I want to be able to
click a button here or maybe even not
take any action at all and the AI system
should be intelligent enough to use the
information it has to help me accomplish
my goal so like that that's like the
direction that we're building at Omni
for example and there are a lot of other
tools that are philosophically in in
kind of the same same boat it makes me
think of um like I've used a lot of I
want to say like no code web scraping
tools where it's like they and I've just
leared the word alignment and what that
means in AI and that's like the AI or my
definition I'm going to butcher it but
that it's doing the thing that I want it
to do in the way that I want to do it
and it know like if I'm like grab me
content of the latest Reddit posts it it
knows that I want it to go onto this
subreddit and only grab like the top
five most relevant it's not going to go
and grab the whole page and all of that
sort of thing and the other other thing
is I'm thinking
is that does that mean that process
automation is AI like not necessarily I
mean I think it's kind of the reverse
which is that the best AI systems are a
much more advanced version of process
automation than I think many people who
don't work te in technical spaces are
used to right so I think a lot of folks
who work for example in revops are very
accustomed to these workflow Builders or
they're accustomed to these spreadsheet
Integrations where there's a lot of
configuration that you need to do ahead
of time and I think what a lot of people
don't appreciate is that when you are
building those workflows and these
automations you're building in a lot of
assumptions about the decisions that one
should make using the data right but in
reality humans tend to be very bad at
integrating a ton of data and making
decisions about what filter criteria
make the most sense or what sorts of
decisions are optimal based on the
information that I have and rather than
building those assumptions into the
system I think a lot of people will see
that it's a lot better to say here's the
data I have here's the outcome that I'm
trying to achieve let's say it's you
Revenue right this as an obvious one and
here's the the tools that I have to work
with and the AI can be much more
intelligent to actually make decisions
about how how best to do that right it
can either suggest and collaborate with
a user to accomplish those goals or in
some cases where it's very low stakes
decisions it can just take those actions
by itself and like one simple example
right is um let's say you have a
research agent that's um you know
helping you for example ly does right we
we aggregate a bunch of information
about the the companies that you're
trying to sell to from a bunch of
different data sources and the internet
and our agent is smart enough to to
understand based on that information
which of those pieces of data are most
relevant for the seller to use within
let's say a discovery call or something
right we're not explicitly telling it
look for this keyword we're not explicit
explicitly telling it look for
information within these dates rather
what it's doing is saying given all this
information and the objective of selling
to this person what information actually
is best and that's just like a very
simple example but I think as these
systems get more Advan and people get
more comfortable working with them
you'll see that kind of
um uh that that kind of system become
more and more commonplace it's
interesting like I think it was a I want
to say predy pry Bas pretty Bas they're
in the UK and they had a survey that
like 220 something people and it was who
um like why people the uptake of llms
aren't isn't great in businesses and
it's like all the different reasons like
oh it hallucinates I don't want to give
it access to my data all these different
things and given that Omni is primarily
B2B sales lead focused in Enterprise and
small to medium businesses what kind of
jections do you like if any I'm assuming
um or like do you have to overcome tyal
usually there is like there really Three
core things that we hear over and over
um and they're all understandable I mean
the first one is like concern around
hallucination right where something just
the effect of um oh the AI suggested X
but you know in my opinion I would do y
right and um it works 80% of the time
that 20% of the time I would do it
differently uh and that's really
understandable I think that that
definitely mirrors a lot of the
discussion that I've heard around like
say autonomous vehicles right where I
mean obviously what we're doing is much
lower Stakes uh much um you know making
mistakes is less you know destructive in
our case luckily but it's interesting
because I think a lot of times people
get very cut up on the negative and kind
of deemphasize or underappreciate
the value that even if we're only
correct 80% of the time uh that 80% adds
a ton of value um but even so we
actually tend to be right more often and
I think typically what happens is that
people value their own experience and
they value their own like yeah they
value their own judgment uh sometimes at
the expense of data and um so it takes a
very open-minded person I think to be
okay to like start to work with one of
these systems I think some people will
demand that their system be perfect you
know 99 or 100% of the time in order to
feel like they can trust it but I think
a lot of uh people certainly our early
customers are you know perfectly fine
they can see the value with um all the
value that we add in terms of time
savings and Improvement on the accuracy
and quality of the information they get
and like the the strategies that we're
able to build for them you know and if
we sometimes uh pull slightly out of
data information or the insights aren't
exactly what they would have said like
they trust the system that it's um
either working as intended or you know
they're okay to sort of work out the
Kinks I guess and kind of let because
the systems are getting better all the
time and frankly our our AI agent like I
said 8020 we're not 8020 anymore I mean
I'd say that we get it right far more
often than we get it wrong uh and we're
only improving as the models improve and
as we just get a lot better at training
these agents so that the second thing is
um sort of related uh which we
definitely hear a lot more around um
more mature sales organizations which is
like some sales teams have these Tech
stacks of like 30 different tools you
know not really it's probably like eight
different tools but these things are all
wild wired together and they have like
their way of selling right and they have
so much invested both in terms of money
and um training and you know also
probably a little bit of like ego in
doing it their way that sometimes like
there definitely people who just are not
interested in thinking about oh maybe I
could sell differently right like maybe
I don't have to send you know a thousand
emails per you know inbox a day to hit
my number maybe I can do it much better
with say fewer emails or maybe I can you
know drop a few of these Point Solutions
and pick up something that builds a lot
of the functionality into one and
inherent in that is not relying so much
on having so like like micro level
control over everything that happens but
you know being tolerant of a
probabilistic system um within your
workflow which I think could be really
challenging for some people um and then
the last thing is just that there are a
lot of teams that like see an AI system
and they've been selling you know their
their sales teams uh especially at like
larger Enterprises Legacy companies
they've been selling one way for 30
years you know they don't use like any
sales Tech that's launched in the last
probably eight to 10 years like that
they have their relationships they meet
face to
face um
and you know actually what's really
interesting is that a lot of these teams
are the ones that are most eager to
adopt a tool like Omni or something in
our in our realm once they kind of get
comfortable with it I use it um and tral
it out because they don't even have to
learn all this super complex automation
right they don't have to have a revops
team they don't have to do all of this
it's it's literally like a plug-and
playay system that works um and almost
like without that baggage of like the
last 10 years of sales Tech um they're
they're a lot more tolerant of working
with these systems and and you know it's
just sort of a learning curve issue I
think people think like there is a lot
of oh AI has been around for so long
it's like well actual
usable no like I'm I I feel like a large
majority of people think that have just
suddenly it's almost suddenly come into
Consciousness since like chat GPT was
only what like a few years ago so to
expect I think it's so right to expect a
level of um almost like Grace not
lenience but Grace and understanding
that it's collaborative but then how do
you move that and like align that with
the whole like everything needs to be
Roi right now if it doesn't work like I
was doing a almost like a self study on
how quickly I will churn or leave a
product if it doesn't fit my exact
expectations and I was like I'm a
horrible end user I was mentioning to
someone on a call earlier today that
last year I tried 174 tools who like
Renee that's insane I went through like
my receipts my old signups and
everything because I'm an earlier doctor
of a lot of different stuff like really
enjoy it but I think my um I I
understand like on a on a not a just on
a level that it's like yeah you you do
need to have understanding for these
teams like it's a startup you you kind
of got like a window of expecting bugs
or lack of functionality but it made me
think about like the whole human in the
loop thing because you mentioned I know
that there's a right term for it and I'm
missing it right now where it's like it
will check what's that called do you
know what that's called um yeah like
like uh human feedback basically I mean
or or are you talking about like
reinforcement learning I don't really
know what I'm talking about yeah I mean
like like like yeah you'll hear like rhf
right so like okay yeah like
reinforcement learning uh with human
feedback yeah yeah yeah reinforcement
learning from Human feedback so it's
like you know the simple example is like
if you're using chachy BT there's the
thumbs up thumbs down and yeah I mean I
think maybe a better way of putting what
I was saying before is like I think what
we're definitely encountering is like
some people are are very open to using
these systems and are comfortable to
like deal with the underlying models
which are unpredictable inherently
they're probabilistic systems and I
think some teams just require absolute
certainty that everything that gets
output is what they expect it to be but
yeah these these the technolog is always
improving and I think you know similar
to how every kind of technological era
comes with you know a lot of people who
are uncomfortable using different
technology or thinking about different
workflows or just like different ways of
solving problems and then there are
people who are very comfortable in those
modes um we'll see the same things uh
here where I think over time more and
more people will just start to
understand probabilistic systems better
and say hey like this is going to work
um 95% of the time and 5% of the time
it'll throw some kind of weird response
but I'm kind of aware enough of that
that'll happen and I can catch it and
regenerate that response and just go
about my day that's such a good point
you started the call I said that you
were a little bit you struck me as like
very serious and like I I I know from
knowing you that like you're a pretty
realist person but that's a very
optimistic take for you to have um where
are you keeping up with like because
you're always online you're always awake
uh just for anyone actually really good
recently about getting my eight hours of
sleep oh well done yeah um but no I'm
definitely sort of a night owl sometimes
yeah where do I keep up I honestly like
Twitter is a great source of information
like as as much of a cesspool as it is
as everybody says like I hate it but I
also find it really valuable Reddit as
well and more and more I think I've just
been like trying to be more like
directed in my learning and so you know
when something peques my interest say on
Twitter then I go down the rabbit hole
of like looking at product documentation
if it's like a technological tool or
I'll go on YouTube and and try to find
longer form say video content so I I
think I've been like I try to spend as
little time on Twitter frankly as
possible uh but I I've enjoyed kind of
going there finding some interesting
things and then pursuing uh you know
more learning elsewhere that's very fair
do you have someone that you would
interview that you would love to
interview one of my classic questions oh
I don't know about on Twitter no they
don't have to be on Twitter okay okay
okay I mean in AI in general oh in
general um can it be a like a past
person like for person from history
because yeah so the person that that
comes to mind immediately is Carl Young
uh the psychoanalyst yeah he's so
interesting I'm reading an autobiography
of his where he just talks about like he
analyzes his own dreams and talks about
the origins of his theories on
Consciousness and identity and it's so
fascinating and I think when you go down
the rabbit hole of a lot of um
generative Ai and kind of the
discussions around um like you know kind
of um like when you go down the rabbit
hole of conversations around like
general intelligence um like his name
always comes up and his theory is always
come up as sort of this like framework
for understanding Consciousness within
like non-organic systems um yeah I I
think he'd be such a great uh
conversationalist strong opinions in AI
do you have strong opinions opinions I
do yeah I mean I think my strongest
opinion is um around interfaces other
than um chat input uh to interact with
these systems and when I say chat I both
Voice and text I I truly think that
while that's a great way of interacting
with language models and certainly it's
it's kind of like like you know text is
the fundamental unit of interacting with
language models of course but I think
from like a user perspective you'll see
more and more interfaces that are you
know I think more comfortable and more
natural to whatever the use case and the
context is and along with that I think
what what uh met necessitates is more um
special purpose tools so rather than
going to chat GPT for everything you
want to do I think it'll be look much
more like yeah like software prior to uh
chat gbt where you had you know your
tool that does this and your tool that
does that and and you know you you had
this like more diverse Tech stack that
you would go to um I really don't think
we'll see uh you know just like a
handful of software platforms dominate
everything um when it comes to like
where users spend their time to uh get
work done or or get play done or
whatever I I do think that we'll see
quite a bit of diversity still um and
that'll just be necessitated by like
it's impossible to build for every
single use case well that there's a lot
of value in building for specific person
and um that will just then necessitate
different design
decisions I've got a question that has
no relation to that if you had an extra
three hours a day what would you do oh
easy I'm really into uh so so actually I
wish I had way more than three hours you
can have five I'll give you five five
okay well i' spent three of those hours
I've been really interested in robotics
and I I want to learn Robotics and
specifically like robotics engineering I
think longterm I see myself doing work
that's much more technal technal than
what I do today so robotics engineering
and like I've been learning uh spending
some time self learning linear algebra
and so I'd spend more time to do that
and then the other one um is I love like
art and and arts and crafts and things
and um I've been wanting to learn how to
do woodworking for a long time and so I
think I would do that that's awesome you
can't say oh maybe you can um you say
the the wand up there yes that is a
Snape's hand with a wand from Harry
Potter and my dad wood whittel that my
dad whoa that's awesome my dad wood
whittles he I've got like most of my
cupboard back there is so cool wood
Wht say it probably that word it's
hilarious but yeah um where so you don't
live on Twitter I was going to say you
live on Twitter where are you able to be
found feel free to plug something well
you can find me on Twitter if you want
uh but I'm probably more often on link l
in uh just at my name um also check out
Omni docomo M ni.com
um yeah and come say hi we love to chat
with folks awesome thank you so much
that wraps up this week's episode of
unsupervised learning I'm your host
Renee and I've had a great time chatting
with you as always links to everything
we discussed will be in the show notes
make sure you reach out to our guests
questions or feedback reach out to pod
unsupervised learning. until then leave
a like follow or writing on Spotify
Apple podcast or YouTube and until next
week stay curious
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