26 September 2024

How I Use Loom + Ai To Automate Everything I Do - Steph Smith

2Frameworks

9Insights

Frameworks in this episode

Productivity6 steps

Async Week Process Automation

Document work, let AI critique it, then automate the highest-value steps.

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Innovation6 steps

Codified Taste Learning Loop

Turn subjective preferences into variables you can study, test, and refine.

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Insights & moments

The myth-busts, hot takes, explainers, and tools worth keeping.

Myth Buster· 1

Myth Buster14:00

The Best AI Use Is Accelerated Learning, Not Copy-and-Paste

The hosts reject the framing of AI as a simple replication tool. Newer models can analyze why successful work succeeds, allowing creators to isolate skills they want to practice, while direct copying produces generic work and makes lazy users easier to commoditize.

Use models to explain why strong work succeeds.
Older models often returned averaged internet best practices.
Selectively practice extracted attributes instead of copying outputs.
Creative learning and creative expansion are complementary uses.
Generic replication accelerates commoditization.

“people get stuck that hey this is a copy and paste tool we think it's an accelerated learning tool”
Kieran Flanagan · 14:00

“the creative unlock and the accelerated learning are the two parts that I am most excited by by AI”
Kieran Flanagan · 16:00

#accelerated learning#content creation#commoditization

Hot Take· 2

Hot Take09:00

Part of Your Future Job Is Teaching AI Your Job

Kieran argues that knowledge workers will increasingly divide their time between performing tasks and teaching AI systems how those tasks work. Better documentation and specificity improve the assistant's ability to reproduce work, although the shift creates uncomfortable questions about roles and employment.

Work time may split between execution and AI instruction.
Detailed documentation determines assistant quality.
Teaching an AI requires making tacit judgment explicit.
The efficiency upside comes with difficult workforce questions.

“what percentage of your time is doing your job and what percentage of your time is teaching an AI to do your job”
Kieran Flanagan · 09:00

“the more you can document what a human does and really be specific about that the better the AI assistant will be”
Kieran Flanagan · 09:00

#future of work#ai assistants#documentation

Hot Take21:30

AI Will Make Creative Trends Saturate Faster

As people learn and reproduce successful formats more quickly, distinctive styles may lose novelty sooner. Taste remains difficult to predict because cultural context, live experience, and counterculture can make objectively imperfect work more appealing than polished alternatives.

Faster learning causes successful formats to spread rapidly.
Creative saturation curves will become steeper.
Technical quality does not fully determine preference.
Popular trends generate countercultures.
Taste remains worth studying because it is context-dependent.

“taste is going to change faster”
Kit Bodner · 21:30

“anytime something trends like AI like there will be counterculture Associated”
Steph Smith · 22:00

#taste#trends#counterculture#creative saturation

Explainer· 1

Explainer11:00

AI Enables Art Forms That Previously Could Not Exist

Steph highlights creative formats that depend on generative AI rather than merely using it to make cheaper stock assets. Iterative escalation prompts, visual anagrams, and transformed musical podcast clips illustrate how AI can expand the available creative space.

AI can enable formats rather than merely accelerate old production.
The 'make it more' trend uses iterative generation as the creative mechanism.
Visual anagrams can present different portraits under rotation.
Podcast speech can become musical material.
New creative lanes are more consequential than generic generated assets.

“people should be paying attention to the very interesting ways that people have created new art forms with AI”
Steph Smith · 11:00

“you're actually extending the lane of creativity in some way”
Steph Smith · 13:00

#generative art#visual anagrams#music#creativity

Story· 1

Story10:00

Why Smarter Humans Made Steph Smith Less Afraid of AI

Steph connects her experience in a gifted program with her lack of fear about AI-assisted creation. She has always known that smarter and more creative people exist, yet she has still been able to make worthwhile things, so another capable creative force does not eliminate her opportunity to contribute.

Being surrounded by smarter people did not prevent creative contribution.
Relative capability is not the same as personal irrelevance.
Creators can remain distinctive despite stronger competitors.
AI does not erase the value of individual perspective.

“ignore AI absolute people who are way smarter than you like right in front of you”
Steph Smith · 10:30

“I've still been able to create interesting things”
Steph Smith · 11:00

#creativity#ai anxiety#mindset

Tool· 4

Tool03:30

Building an AI Chief of Staff for Operational Scale

Kieran describes teaching an LLM an existing operating model by uploading its documents, templates, and schedule. The model reproduced templates, follow-ups, and a meeting calendar, with a proposed next step of processing meeting transcripts and routing action items to responsible people.

Pair deep domain expertise with operational support.
Optimize operating models for speed, momentum, and accountability.
Use weekly sprints, templates, follow-ups, and asynchronous work.
Reserve live discussion for the most important topics.
Feed meeting transcripts into an agent to extract and distribute actions.

“they should solve for Speed of speed of execution momentum and accountability”
Kieran Flanagan · 04:30

“it created the templates it told me the follow-ups it told me it built me the calendar of all of the meetings to put into…”
Kieran Flanagan · 05:00

#ai agents#operations#chief of staff#meetings

Tool06:00

Ask Coding Agents What to Build, Not Just How to Build It

Coding agents can help non-programmers move from an automation requirement to several possible applications. Supplying API documentation lets the agent propose products and optional features, reducing both ideation and implementation barriers.

Describe the outcome instead of prescribing the implementation.
Ask for three to five application options.
Provide API documentation as available building material.
Review agent-proposed features that extend the original idea.
Use no-code tools when custom code is unnecessary.

“can you give me ideas for the best ways to build applications to solve this problem and it will give you three three to five…”
Kit Bodner · 06:30

“you can just give the repet agent a bunch of API docs and say what shall I build”
Kieran Flanagan · 07:00

#coding agents#automation#apis#no-code

Tool08:15

Audit Whether Your Calendar Matches Your Goals

Calendar data, meeting transcripts, and stated goals can be analyzed together to expose how a team actually allocates its attention. This gives managers a more evidence-based way to decide whether the team has spare capacity or is already focused on its priorities.

Combine calendar events with meeting recordings and transcripts.
Provide weekly, monthly, or quarterly goals as evaluation criteria.
Compare actual time allocation with declared priorities.
Use the result to assess team capacity.
Distinguish lack of capacity from misplaced focus.

“looking at time allocation am I actually like how am I actually spending my time and doing my work versus what I'm trying to accomplish”
Kit Bodner · 08:30

“does the team really have capacity to do more or do they not”
Kit Bodner · 08:30

#time allocation#calendar#team capacity#goals

Tool20:30

Use Community Upvotes to Find What People Care About

Platforms such as Reddit expose large-scale preference signals inside specific communities. Tools including subreddit statistics and Gummy Search can surface the most resonant posts over different time ranges, giving creators concrete material to study and build upon.

Treat upvotes as imperfect but useful resonance signals.
Compare top content over weekly, monthly, yearly, and all-time windows.
Analyze niche communities rather than relying only on aggregate trends.
Ask why a specific format earned exceptional engagement.
Build new work from the underlying insight rather than copying the post.

“you can see what millions of people like buy care about”
Steph Smith · 20:30

“you can go to something like a Gummy Search and just see in the last week month year all time what was the most upvoted”
Steph Smith · 21:00

#reddit#audience research#trend analysis#content