Basically, it adds a bunch of functions to Sheets that help interface with OpenAI (in both directions). Every cell can run it’s own API call (in parallel). You can reference other cells. Combine, list, split, it’s really nuts.
If LLMs weren’t already capable of generating more text than anyone could possibly read or use, this really seals the deal. Quantity: Check ✅. See below for about 20 question and answer pairs generated using this plugin in under 1 minute, from my initial input of just 4 questions (and no answers).
Q&A Pairs, as far as the eye can see.
Quality: In Progress ⌛. This is more work. Especially if there is too much content to have a human editor. Stay tuned. 📻
Here’s a “deep work” 1,2 punch that I have had some good results with.
Walk and talk out a very clear plan. Record a voice memo. I use the Yealink BH71 Pro headset, which has amazing noise cancelling (for the microphone) and I look like a telemarketer on a hike. Later you can transcribe this with your favorite voice transcription tool. (Optionally, get ChatGPT to format the transcription for you.) It is very important to resist the urge to use your phone, just talk out the steps, talk out the framework, talk out the plan for what you will do. When you get distracted, bring it back to the plan. Make sure you have a clear outcome in mind.
Block 90-120 minutes of “deep work” time to execute the plan. Try to get to the outcome, try to follow the steps. Maybe the plan was too ambitious, maybe you need to adjust the plan. But try to get to the outcome. Maybe you don’t need 99% of the structure you thought that you did (that’s what happened to me today). But you incept in yourself the idea of what you want to do, and then you do it. When you get distracted, bring it back to the outcome.
That’s it. Go get ’em, champ!
Go get 'em, champ.
P.S. - I came up with an interesting theory while performing Step 1 this morning (a distracting thought from the plan I was formulating), which is that Cal Newport is actually an AI being sent to us from the future to teach us how to focus like a machine. (Think: The Terminator of “Deep Work”.) I’m not sure how to test this hypothesis.
After watching it, I realized that many of the AI applications where I thought I would need plug-ins, or special function calling set-ups, or a proprietary/paid solution, etc — these can be solved with better prompting. It’s also helpful to see them build up to more complex use cases, step-by-step.
One of the points that Andrew Ng makes in the intro is that there is no “best prompt for X”. So instead this course teaches you the fundamentals, and more importantly - how to iterate to get to a solution that works for your application.
With these prompting fundamentals and a basic RAG pipeline (which is getting easier and easier every day) - you can really accelerate a ton of business tasks.
I am now convinced that there is something for everybody.
Clearly someone likes this, there is only one left in the box.
I could imagine a point in time where I would be excited to identify as a “slime-licker”. But licking toxic waste? No thank you.
P.S. - In case this is for you, a quick search seems to indicate that this particular form factor of “sour rolling liquid candy” is no longer for sale online. (Hit me up and I’ll tell you where the physical location of this last roller is.) But don’t worry - you can still squeeze various flavors of toxic waste onto your tongue with two-day delivery 😛.
Here are some lessons learned from today’s attempts into social media automation workflows:
When soliciting creative input from Language Learning Models (LLMs), consider asking for more than four variations. This is particularly useful if the workflow involves human selection at some point. (It makes sense that most of the generative image tools do it this way.)
I’ve decided to move away from IFTTT as it no longer serves my needs. I’ve transitioned to using Postman for simple webhooks and Make.com for more intricate routing.
Currently, I’m utilizing Buffer. However, they’ve ceased the addition of new apps to their API, forcing me to use Make > Buffer. In the future, I might consider posting directly to social media via the individual platform APIs. This is especially feasible with function calling and having LLMs write the function calls for me. I’m finding that API-replacement apps like Zapier, Make.com, and IFTTT are becoming more of a hassle than they’re worth.
A significant time-saving tip: use GPT-4 to generate regex patterns for you.
Today was my kickoff call with Athena. I’ve been really impressed by the intentionally of their onboarding process.
Each step of their sales funnel was very clear and effective. Each stage of the on-boarding has a clear purpose and structure. The first 100 days are planned out in detail, which provides a nice framework and sense of certainty and security.
I’m excited to see how it goes! I will keep you posted.
Are you at the cutting edge of your field? Or are you at the bleeding edge?
Most of the time, I think I’m at the cutting edge. But then I notice that I’m bleeding.
I get so caught up in the excitement and novelty that I don’t realize that I have crossed over to the bleeding edge. It’s hard to get paid at the bleeding edge, even harder to be profitable. It’s even more exciting than the cutting edge, and even more draining.
In silicon valley, the saying is “pioneers get arrows in their backs, settlers get land.” This is the distinction that I’m trying to make between the cutting edge and the bleeding edge. Both the pioneers and the settlers had the same vision, the same excitement. One was just a little too soon (and it’s really hard to know when the timing is right).
Part of what originally drew me to 3D printing was the theme of commuting between the digital and physical realms. When I first started, I knew nothing about CAD, a category of software that continues to frustrated me to this day. (I’m just not into graphical programming languages.)
There are a few cool new tools that I’ve been playing with that make commuting between the physical to digital worlds a little easier. Two that I’m really into right now are Commonsense Machines (CSM.ai) and Luma AI from LumaLabs. Both companies offer text-to-3D and video-to-3D. CSM also offers 2D-to-3D, which is getting better every month.
A couple of Christmases ago, I accidentally ended up on the bleeding edge of web-based Augmented Reality. What I thought would be pretty straightforward involved hiring and firing at least 3 different professional WebAR developers. But we ended up building polySpectra AR - which I still think is pretty nifty. The idea was to give users a free massless preview of their .STL, before they would upload it to a 3D printer or 3D printing service.
Fast forward to this morning, something clicked and I realized that we could pretty quickly tweak polySpectra AR to give users a completely CAD-free workflow to both visualize 3D models and then manufacture them with 3D printing.
I’ve spent a lot of time banging my head against the wall trying to quickly get started with a bunch of new AI tools recently. The quickstart guides have not been so quick.
In particular, it was interesting to see the Poe team watch their quickstart get (mis)interpreted in real time at the Hackathon on Saturday. There were a few really common hiccups where people got stuck, even though it was clearly in the docs, almost every single team got stuck at the same problem and had to ask for help.
I definitely have a new appreciation for the importance of a good quickstart guide. Today I decided that we should build one for polySpectra. We started with our go-to printer: the Asiga Pro 4K.
By using a template with common variables, we can now pretty quickly generate a new quickstart guide for any printer we support. The first one took about 3 hours, the second one about 10 minutes.
I really think one of the most important superpowers of AI tools is making it easier for people to interact with code.
I’m also getting into Zoom Clips, which means I don’t need to pay Loom and Zoom.
Poe has the goal of becoming “the YouTube of AI Bots”. Part of the thesis is that they can leverage their experience building Quora to create the infrastructure necessary to help bot creators focus on the creative parts of bot creation.
At the AGI House Poe Hackathon on Saturday, Quora CEO Adam D’Angelo stated that his goal with Poe’s new creator monetization strategy was to have bot creators be able to quit their jobs because they are making enough money on Poe. As you might imagine, this went over very well with the audience. I’m sure everyone was imagining themselves as part of a new class of creator, like being a professional YouTuber or Twitch streamer. (Sounds more fun than either of those to me!)
Poe’s strategy currently involves:
Distribution: Poe ensures that its bots reach a large audience by implementing a bot recommendation system and allowing users to share chats with bots both internally and externally. They also encourage bot creators to drive traffic to their bots from outside of Poe, as this increases the likelihood of the bot being recommended on-platform.
Monetization: Poe provides a way for bot creators to generate revenue by setting a price per message that the bot creator will be paid for every message to their bot, and by offering referral fees when a bot brings new users to Poe. Poe also allows bot creators to monetize their bots through alternative means, such as placing ads in their content or asking users to visit their website to make donations or payments.
Costs: Poe covers all model inference costs and any other significant per-message costs involved in operating any bot on Poe. This is done by using the bot query API or by working with the bot creator to pay their model inference costs if they want to use a model that is not currently available on Poe. (This is a really big deal for individual bot creators.)
Multi-platform UI: Poe ensures that users have a great, consistent experience with bots no matter what device they are on. This is achieved by having a native presence on all major platforms (Web, iOS, Android, MacOS, etc) and by taking care of login and synchronized history.
Model independence: Poe allows bot creators to build their product using models from all different providers. This enables bot creators to adapt their product to use any combination of the best technologies as they are created.
I’m sure that the Poe team is already thinking about this, but I think there is one final missing piece: analytics. The only way you end up with “Mr. Beast”-level creators is by giving creators direct insight into the engagement data. For example, see how 18-year-old YouTube phenom Jenny Hoyos breaks down her “creator science”. (Spoiler alert: she literally plans everything out to the second.)
To truly become the “YouTube of AI Bots”, Poe should provide creators with a comprehensive analytics dashboard. This dashboard would allow creators to track the performance of their bots, understand user engagement, and gain insights into how their bots are being used.
Features of this dashboard could include:
Usage Statistics: Display the number of interactions, active users, session length, and other key metrics that help creators understand how their bots are being used.
Engagement Metrics: Show which parts of the bot are most engaging to users. This could include metrics like response rate, user retention, and session duration.
Error Logs: Provide detailed logs of any errors or issues that occur during bot interactions. This would help creators identify and fix problems in their bots.
User Feedback: Collect and display feedback from users. This could include ratings, reviews, and direct user feedback. At the very least, the stats on the “thumbs up” and “thumbs down” user responses.
Demographic Information: If appropriate and privacy-compliant, show demographic information about the users interacting with the bot. This could help creators understand their audience better and tailor their bots to user needs.
By providing these analytics and insights, Poe would empower creators to continually improve their bots, make data-driven decisions, and ultimately create better experiences for users.
Maybe I’m still sleep deprived from Saturday’s hackathon, but I think this is going to be a really big deal. I’m excited to see what the Poe team does next. I don’t think I’ll be quitting my job anytime soon, but I can’t wait to meet the first bot creator who does!
Find me on Poe! Here’s my Poe profile link and my two currently active Poe bots:
